TY - JOUR T1 - English speaking practice with conversational AI: Lower secondary students' educational experiences over time AU - Ericsson, Elin AU - Johansson, Stefan JO - Computers and Education: Artificial Intelligence VL - 5 SP - 100164 PY - 2023 DA - 2023/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100164 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000437 KW - Conversational artificial intelligence KW - Dialogue-based computer-assisted language learning KW - Longitudinal educational experience KW - Spoken dialogue system KW - Virtual human AB - Conversational artificial intelligence enables opportunities for practicing speaking the target language while giving individualized feedback in a low-anxiety environment offered in spoken dialogue systems with conversational agents. In this paper, we present results from a longitudinal study conducted on Swedish lower-secondary students who used a spoken dialogue system as an integrated part of their ordinary English lessons. They interacted orally with embodied conversational agents to solve given tasks in everyday-life scenarios and self-reported their experiences in questionnaires and systematic logbook reflections. Analytical methods were mainly non-parametric tests. Results revealed that the students sustained practicing, socially and emotionally engaged with a slightly positive trend in their educational experience. These insights can inspire teachers and stakeholders in the integration of conversational artificial intelligence in language education and designers in the development of such systems for this age group. ER - TY - JOUR T1 - Initial teacher training for twenty-first century skills in the Fourth Industrial Revolution (IR 4.0): A scoping review AU - Teo, Timothy AU - Unwin, Siobhan AU - Scherer, Ronny AU - Gardiner, Veronica JO - Computers & Education VL - 170 SP - 104223 PY - 2021 DA - 2021/09/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2021.104223 UR - https://www.sciencedirect.com/science/article/pii/S0360131521001007 KW - Preservice teachers KW - Initial teacher training KW - 21st century skills KW - Technology integration KW - IR 4.0 AB - The Fourth Industrial Revolution (IR 4.0) is characterized by rapidly changing technologies and workforce demands. Educational systems seek to respond to these changes. Little is known about ways in which Teacher Training Institutions (TTI) are preparing preservice teachers to address these educational demands. This scoping review examines the high-quality literature with respect to initial teacher training activities and challenges, specifically focusing on 21st century skills and technology integration in the context of IR 4.0. The results show TTI requires coherence throughout the organization to effectively respond to shifting needs and contexts. The development of IR 4.0 technologies move swiftly, providing new opportunities for developing preservice teachers' 21st century skills. Such technologies could reframe the role of TTIs and teacher educators. Contrastingly, the pressure for TTI and teacher educators to maintain required skills increases alongside technologies. This scoping review concludes that research on this topic remains valuable and critical to further inform initial teacher training in IR 4.0 to facilitate the development of preservice teachers’ 21st century skills. ER - TY - JOUR T1 - Disclosing Chinese college students’ flow experience in GenAI-assisted informal digital learning of english: A self-determination theory perspective AU - Wu, Hanwei AU - Wang, Yongliang JO - Learning and Motivation VL - 90 SP - 102134 PY - 2025 DA - 2025/05/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2025.102134 UR - https://www.sciencedirect.com/science/article/pii/S0023969025000414 KW - Flow experience KW - GenAI KW - Informal digital learning of English KW - Basic psychological needs AB - The role of flow experience in enhancing GenAI-assisted informal digital learning of English (GAI-IDLE) has recently gained increasing attention. However, the mechanisms underlying the achievement of flow experience in this context remain underexplored. Grounded in Self-Determination Theory (SDT), this study investigates how GAI-IDLE influences flow experience through the lens of three basic psychological needs: autonomy, competence, and relatedness. Specifically, we aim to examine the mediating effects of these psychological needs on the relationship between GAI-IDLE and flow experience. To achieve this, we conducted a survey among 333 English as a Foreign Language (EFL) learners from various colleges in China. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS 4.0 software, our results show that GenAI literacy and English proficiency positively and directly impacted flow experience, while gender had no direct effect. GAI-IDLE directly predicted flow experience and positively influenced autonomy and relatedness, which in turn directly enhanced flow experience. Thus, GAI-IDLE indirectly affected flow experience through the mediation of autonomy and relatedness. However, contrary to SDT, GAI-IDLE did not directly affect competence, and competence did not directly influence flow experience, resulting in an insignificant mediating role for competence. We discuss potential explanations for these findings and conclude with educational implications. ER - TY - JOUR T1 - Making sense of generative AI for assessments: Contrasting student claims and assessor evaluations AU - Fischer, Isabel AU - Sweeney, Simon AU - Lucas, Matthew AU - Gupta, Neha JO - The International Journal of Management Education VL - 22 IS - 3 SP - 101081 PY - 2024 DA - 2024/11/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.101081 UR - https://www.sciencedirect.com/science/article/pii/S1472811724001526 KW - Generative AI KW - GenAI KW - Assessment KW - Sensemaking KW - Critical thinking KW - Higher education AB - The rapid growth of generative AI usage in higher education has left educators looking urgently for insights into student usage and guidance on good practice. This case study examines an experiential exercise involving 118 postgraduate management students at a UK business school, where students were asked to write a 500-word reflection on their use of AI for a 2500-word essay-style assessment. Using sensemaking as a theoretical lens, we compare students' claims with assessors' evaluations of students' AI usage. Our findings indicate that students predominantly use generative AI for writing, paraphrasing, and rephrasing, rather than for fostering critical thinking or engaging in the more advanced stages of sensemaking, a level achieved by only one-tenth of the cohort. The consistency between this study's findings and pre-generative AI research suggests that higher education has yet to adapt adequately in ways to integrate AI to mitigate, rather than exacerbate, current sector deficiencies. We call on university leaders to develop institutional strategies that allow for effective and responsible integration of generative AI, and on educators to develop students' critical evaluation and academic writing skills that build on generative AI's affordances, with several specific recommendations made in this article. ER - TY - JOUR T1 - Exploring Chinese EFL learners’ engagement with large language models: A self-determination theory perspective AU - Wang, Xiaochen AU - Wang, Siyi JO - Learning and Motivation VL - 87 SP - 102014 PY - 2024 DA - 2024/08/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2024.102014 UR - https://www.sciencedirect.com/science/article/pii/S0023969024000560 KW - EFL learners KW - Engagement KW - LLMs KW - SDT KW - Chinese context AB - Large language models (LLMs) greatly affect language learning, but research on Chinese EFL (English as a Foreign Language) learners’ engagement is limited. In this sense, the present study draws upon Self-Determination Theory (SDT) and employs a mixed-methods approach to explore how 210 Chinese EFL Learners engage with LLMs. Findings showed that most of the basic psychological needs (BPNs) play a critical role in predicting behavioral, cognitive, and emotional engagement. However, perceived autonomy did not emerge as a predictor for behavioral engagement, and perceived competence was not found to be a predictor for either behavioral engagement or cognitive engagement. Furthermore, our qualitative interviews showed that the influence of BPNs on EFL learners’ engagement with LLMs can be categorized into six thematic areas: self-directed learning empowerment, goal-oriented learning challenges, individual performance enhancement, limited knowledge advancement, collaborative learning access, and interpersonal connection gaps. The findings of this study could provide insights for foreign language teachers in their instructional design and for policymakers in formulating relevant policies. ER - TY - JOUR T1 - An early investigation of collaborative problem solving in conversational AI-mediated learning environments AU - Aslan, Sinem AU - Alyuz, Nese AU - Li, Belle AU - Durham, Lenitra M. AU - Shi, Meng AU - Sharma, Sangita AU - Nachman, Lama JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100393 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100393 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000335 KW - Early childhood education KW - Collaborative problem solving KW - Game-based learning KW - Intelligent tutoring systems (ITSs) KW - Multimodal conversational artificial intelligence (AI) AB - Collaborative problem solving (CPS) encourages children to communicate effectively and fosters creativity and critical thinking. New digital technologies can potentially provide opportunities for innovative ways to promote CPS at an early age. However, one key challenge of such technologies is to be engaging and effective while also pedagogically adapting to developmental needs of young learners. In this paper, we propose that a multimodal conversational AI system, Kid Space, providing interactive learning experiences could enrich CPS and promote positive educational outcomes. Kid Space combines multimodal classroom sensing with a projected 3D virtual environment and an animated conversational agent to engage with children via spoken dialogue and physical interactions. Within an exploratory case study, we formatively evaluated CPS behaviors of a set of children engaged with Kid Space to inform design modifications for the type of CPS learning analytics educators could benefit from and improved support of CPS behaviors in conversational AI-mediated learning environments. Our quantitative results indicate that there were significant correlations between CPS behaviors and (1) joint engagement of students working together and (2) pedagogical interventions provided by the instructional assistant facilitating the learning experience. The results imply that, with necessary design augmentations, Kid Space could potentially play a valuable role in supporting CPS processes of young learners. ER - TY - JOUR T1 - Dynamic interplays between self-regulated learning and computational thinking in primary school students through animations and worksheets AU - Kong, Siu-Cheung AU - Wang, Yi-Qing JO - Computers & Education VL - 220 SP - 105126 PY - 2024 DA - 2024/10/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105126 UR - https://www.sciencedirect.com/science/article/pii/S0360131524001404 KW - Cognitive development KW - Computational thinking KW - Mixed methods design KW - Reciprocal dynamics KW - Self-regulated learning AB - Recent studies identify Self-Regulated Learning (SRL) as a key factor in enhancing cognitive development, particularly within Computational Thinking (CT) literature. However, research gaps remain in understanding how SRL and CT interact from a developmental perspective. Our study designed a program with tailored animations and worksheets to specifically foster students' learning and cognitive development. Using a mixed-methods approach, we administered surveys among 1235 students from 29 Hong Kong primary schools to investigate a dynamic learning system comprising SRL and CT in a large-scale CT program. Additionally, semi-structured interviews were conducted with 15 students to further probe insights. Quantitative findings revealed a mutually reinforcing relationship in the dynamic system, suggesting that higher SRL skills enhance cognitive CT abilities, and vice versa. Complementing these results, qualitative findings showed that integrating animations and worksheets into the CT program significantly boosted students' SRL and cognitive development. These findings have significant implications for educational practices and curriculum design. Schools should consider implementing SRL strategies, such as proactive goal setting and reflective evaluation, within their curricula to promote students’ cognitive development. Furthermore, strategic investments in educational technology, including collaborations with EdTech developers, are essential to create effective, pedagogically sound tools that enhance learning outcomes. These insights provide valuable guidance for creating a supportive SRL environment that fosters cognitive development in primary school education. ER - TY - JOUR T1 - Synthesizing cognitive mathematics learning taxonomies AU - Gun, Ozge AU - Bossé, Michael J. JO - Thinking Skills and Creativity VL - 57 SP - 101796 PY - 2025 DA - 2025/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2025.101796 UR - https://www.sciencedirect.com/science/article/pii/S1871187125000458 KW - Taxonomy KW - Mathematical learning KW - Mathematical understanding KW - Problem solving AB - This paper synthesizes twenty-one educational taxonomies tailored primarily for mathematics education. By integrating general cognitive frameworks such as Bloom's Taxonomy and Webb's Depth of Knowledge with mathematics-specific models like Smith et al.’s MATH Taxonomy and Pirie-Kieren's Model of Mathematical Understanding, we develop a synthesized taxonomy (ST) that bridges the gap between content mastery and higher-order cognitive processes. The ST features six hierarchical levels to promote deeper cognitive engagement, support curriculum design, enhance assessments, and foster interdisciplinary integration. The ST addresses gaps in existing taxonomies by aligning task complexity with cognitive processes, accommodating non-linear learning, and emphasizing real-world applications and creativity. It offers practical implications for curriculum differentiation, teacher professional development, adaptive learning technologies, and research on learning progressions. In conclusion, this synthesized taxonomy advances mathematics education by offering a flexible, comprehensive framework that supports foundational knowledge and complex problem-solving skills, better preparing students for the demands of a rapidly evolving world. While promising, the ST faces challenges related to implementation complexity, resource needs, and empirical validation. ER - TY - JOUR T1 - Enhancing digital literacy in foreign language teaching in Chinese universities: Insights from a systematic review AU - Jiang, Baohong JO - Teaching and Teacher Education VL - 154 SP - 104845 PY - 2025 DA - 2025/02/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2024.104845 UR - https://www.sciencedirect.com/science/article/pii/S0742051X24003780 KW - Digital literacy KW - Foreign language teaching KW - Chinese universities KW - The PRISMA framework KW - Nvivo12 AB - For foreign language teachers to successfully transition to digital education, it is crucial to enhance their digital literacy. This study reviews 72 articles (2013–2024) on digital literacy among foreign language teachers in Chinese universities, utilizing the PRISMA framework to filter literature from four databases. Combining Grounded Theory with NVivo12 for data analysis, the study reveals that enhancing the digital literacy of teachers involves four dimensions: national, institutional, team, and individual. The first three dimensions provide critical external supports, while the individual dimension emphasizes the intrinsic motivation of teachers. Therefore, effective enhancement requires a synergistic interaction between external supports and individual motivation. ER - TY - JOUR T1 - Evaluating the AI dialogue System's intercultural, humorous, and empathetic dimensions in English language learning: A case study AU - Zhai, Chunpeng AU - Wibowo, Santoso AU - Li, Lily D. JO - Computers and Education: Artificial Intelligence VL - 7 SP - 100262 PY - 2024 DA - 2024/12/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100262 UR - https://www.sciencedirect.com/science/article/pii/S2666920X24000651 KW - Dialogue systems KW - Interculture KW - Humor KW - Empathy KW - Language learning AB - The rise of artificial intelligence (AI) technologies has been notable in supporting English as an Additional Language (EAL) learners, particularly in offering interactive assessments. AI-driven dialogue systems that produce culturally relevant humor and empathy, bridging the native language (L1) and the target language (L2), have been employed to engage EAL learners more effectively and boost their learning results. However, there's a noticeable gap in research concerning the fusion of humor, empathy, and intercultural dimensions in language learning. Intercultural dimensions encompass acquiring crucial knowledge, communication skills, and the values essential for meaningful interactions across cultures. This case study examines the effectiveness of an AI dialogue system, termed the Multidimensional Approach Culture, Humor, and Empathy Bot (MACHE-Bot), in elevating the English language learning experience and its potential to enhance EAL proficiency. Using convenience sampling, 37 individuals were selected from an English language learning group on Facebook. Following a two-week pilot study, semi-structured interviews were conducted. The results revealed that MACHE-Bot adeptly initiated and reciprocated with humor, empathy, and cultural nuances in a manner well-received by participants. Additionally, the study identified five pivotal factors in EAL learning with MACHE-Bot: (1) intercultural dimensions, which include culturally humorous interaction and culturally empathetic support; (2) user trust comprising both affective and cognitive elements; (3) anthropomorphism; (4) reciprocal self-disclosure; and (5) higher engagement and motivation. These five factors collectively contribute to creating an engaging, relatable, and supportive learning environment, facilitating a more natural learning process, and fostering a deeper learner-bot connection, thereby potentially enhancing motivation and investment in the learning process. ER - TY - JOUR T1 - How can we improve AI competencies for tomorrow's leaders: Insights from multi-stakeholders’ interaction AU - Gupta, Shashank AU - Jaiswal, Rachana JO - The International Journal of Management Education VL - 22 IS - 3 SP - 101070 PY - 2024 DA - 2024/11/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.101070 UR - https://www.sciencedirect.com/science/article/pii/S1472811724001411 KW - Artificial intelligence education KW - Artificial intelligence competencies KW - Learning theories KW - Management students KW - Topic modelling KW - Machine learning AB - This study investigates factors influencing artificial intelligence (AI) competencies in higher education for sustainable development using learning theories. Utilizing a mixed-method approach, it analyzes responses from 525 students and interviews with 35 faculty members from five Indian universities. The study employs confirmatory factor analysis (CFA) and structural equation modeling (CB-SEM) to explore relationships between various learning approaches and AI competencies. Findings indicate that collaborative learning, problem-solving, and cognitive competence significantly contribute to AI proficiency. Human-tool collaboration and self-learning also enhance students' understanding of AI concepts, fostering strategic decision-making in business contexts. Additionally, thematic analysis from qualitative interviews identifies critical themes for developing an AI curriculum framework, including curriculum design, pedagogical strategies, ethical considerations, and global perspectives. The research provides an integrated theoretical model and offers practical recommendations for enhancing AI education, emphasizing the importance of interdisciplinary collaboration and ethical AI usage in management education. ER - TY - JOUR T1 - AI-powered education: Driving entrepreneurial spirit among university students AU - Zulfiqar, Salman AU - Sarwar, Binesh AU - Huo, Chunhui AU - Zhao, Xuanwei AU - ul Mahasbi, Haris JO - The International Journal of Management Education VL - 23 IS - 2 SP - 101106 PY - 2025 DA - 2025/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.101106 UR - https://www.sciencedirect.com/science/article/pii/S1472811724001770 KW - Artificial intelligence value KW - Artificial intelligence ease of use KW - Artificial intelligence usefulness KW - Entrepreneurial intention AB - This study explores the influence of artificial intelligence (AI) on the entrepreneurial mindset and intentions of university students by utilizing a comparative approach anchored in the technological acceptance model (TAM) and the theory of planned behavior (TPB). The authors investigated how perceived values, perceived usefulness, and perceived ease of use of AI tools change students’ attitudes and intentions toward entrepreneurial learning. The prime novelty of this study lies in its comparative analysis of the effectiveness of AI tools in entrepreneurial education before and after their implementation. The data were collected from recognized institutes of the Higher Education Commission based in Lahore and Islamabad, Pakistan. We employed a two-stage, time-lagged data collection approach. The initial phase (T1) involved the participation of 275 entrepreneurship students, followed by a second collection (T2) of 234 responses suitable for analysis. The data were analyzed and compared in a two-stage process (before and after) through partial least squares structural equation modeling (PLS-SEM). The study revealed that artificial intelligence tools embedded in teaching methods dramatically improved students' entrepreneurial attitudes and learning by offering useful and automated solutions. It further concluded that AI serves as a dynamic and effective educational tool for shaping entrepreneurial intentions, thus offering actionable insights for core curriculum development in academia. Finally, this study contributes significantly by bridging the gap in the literature on the direct impact of AI on cultivating an entrepreneurial spirit among university students. ER - TY - JOUR T1 - ChatGPT: The brightest student in the class AU - Vázquez-Cano, Esteban AU - Ramírez-Hurtado, José M. AU - Sáez-López, José M. AU - López-Meneses, Eloy JO - Thinking Skills and Creativity VL - 49 SP - 101380 PY - 2023 DA - 2023/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2023.101380 UR - https://www.sciencedirect.com/science/article/pii/S1871187123001487 KW - ChatGPT KW - Summarizing KW - Assessment KW - Content, Style AB - This paper presents a research study that evaluated the score ChatGPT would get when summarizing a reading comprehension text from the PISA international tests with a prompt that made it simulate doing this as if it were a 15-year-old student. For this purpose, the text was camouflaged among 30 other summaries made by real 15-year-old students and was evaluated by 30 Spanish language teachers with different profiles in terms of age, professional experience, and gender who were unaware that one of the texts was made by artificial intelligence (AI). The evaluation of the summary, for which a homogeneous rubric is used, is based on two fundamental criteria: content and style. For the data analysis descriptive and inferential statistical techniques were used. The results show that the ChatGPT summary obtained the best marks in terms of content and style, with its respective marks being 3 and 2.5 points higher than those of the students. Therefore, we can deduce that the style and content of the ChatGPT summary greatly exceeded those presented by the students. These results are independent of the ages, levels of professional experience, and genders of the teachers who corrected the summary. The integration of AI tools such as ChatGPT must be based on solid methodological proposals that integrate their use from a creative and critical perspective that allows learning with the support of these tools and not using them as substitutes for the development of basic student competencies. ER - TY - JOUR T1 - Stem accounting: Effects of traditional and big data education, learning and intelligence on the accounting student's achievement AU - Namazi, Mohammad AU - Raiessi, Zohreh JO - The International Journal of Management Education VL - 23 IS - 2 SP - 101069 PY - 2025 DA - 2025/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.101069 UR - https://www.sciencedirect.com/science/article/pii/S147281172400140X KW - Accounting education KW - Traditional teaching KW - Big data method KW - Academic achievement KW - Intelligence KW - Learning AB - STEM accounting has emerged as a significant accounting profession's evolution. Big data, as a part of pivotal technology part of STEM, has become ubiquitous and can revolutionize traditional accounting education. This study, in alliance with the STEM paradigms, aims to empirically compare the effect of “traditional accounting education” and “Big Data-based accounting education” on accounting students' achievement (ASA) in various accounting courses, when students' “learning” and “intelligence”, as mediating and moderating variables, are incorporated in this relation. By developing an accounting education's moderated - mediation model, adopting the pretest-posttest design and utilizing the experimental approach, we formed two experimental groups with traditional and Big Data-based methods participating in various accounting courses. For each course, one group was also considered as a “control” group. The study population encompasses all accounting students studying at the undergraduate level of a big university in Iran. The study sample includes 330 students. Applying structural equation modeling, our findings indicate that both Big Data-based and traditional education methods maintain a significant positive effect on ASA; but, the Big Data-base's effect is greater. However, when “learning” is used as the mediating variable, the Big Data's effect is not significant for any of the courses, and there is a very minor mediation; while the traditional method's effect is significant and leads to a medium mediation. Emotional intelligence, as a moderating variable, has no significant effect on the relationship between traditional and Big Data-based methods and the ASA. However, cognitive intelligence has an effect on some accounting courses. When intelligence and teaching methods' interaction is examined, the situation does not change and the emotional intelligence's variable is still unaffected. Although Big Data is useful for STEM accounting education, it is not always statistically significant and preferred in the education's process and its significance is contingent on the type of accounting courses and student's cognitive characteristics (such as learning). The findings' implications for educators and the future of accounting education are to synthesize Big Data and other contemporary IT information techniques in accounting courses and teaching. The role of the student's cognitive intelligence is also potent in this context. This study not only contributes to the extant research on Big Data accounting education but also sheds light on the STEM's accounting literature. ER - TY - JOUR T1 - The role of growth mindset, self-efficacy, and environmental support in ICT practices for creative thinking development AU - Zeng, Chengze JO - International Journal of Educational Research VL - 132 SP - 102631 PY - 2025 DA - 2025/01/01/ SN - 0883-0355 DO - https://doi.org/10.1016/j.ijer.2025.102631 UR - https://www.sciencedirect.com/science/article/pii/S0883035525001053 KW - Creative thinking KW - Creative self-efficacy KW - Creative environments KW - ICT self-efficacy KW - ICT information practices KW - PISA 2022 AB - Creativity is regarded as an essential skill of the 21st century. In technological advancement, fostering students’ creativity is particularly crucial. This study examines how creative growth mindsets, Information and Communication Technologies (ICT) self-efficacy, creative environments, ICT availability, and ICT information practices influence creative self-efficacy (CSE) and creative thinking. The study conducted path analyses on 16,148 secondary school students in Hong Kong, Macau, and Taiwan, China in PISA 2022. The results showed that growth mindsets, ICT self-efficacy, and creative environments can directly promote their creative self-efficacy and thinking, while school environments negatively impact creative thinking. Besides, online information practices mediate the relationship between predictors, CSE, and creative thinking. However, ICT feedback and support do not serve as mediators for creative thinking. ICT availability at school positively affects CSE through ICT feedback, while ICT availability outside of school has a negative effect. This study highlights the combined influence of individual traits, behaviors, and external environments on students’ creative thinking, providing valuable insights for educators to take a holistic approach to fostering student development. ER - TY - JOUR T1 - “I just think it is the way of the future”: Teachers' use of ChatGPT to develop motivationally-supportive math lessons AU - Rutherford, Teomara AU - Rodrigues, Andrew AU - Duque-Baird, Santiago AU - Veng, Sotheara AU - Mykyta-Chomsky, Rosa AU - Cao, Yiqin AU - Chisholm, Kristin AU - Bergwall, Ekaterina JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100367 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100367 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000074 KW - Generative AI KW - ChatGPT KW - Motivation KW - Elementary school KW - Technology KW - Mathematics AB - ChatGPT has quickly infiltrated the educational landscape and teachers are engaging with this tool to support their teaching activities, including lesson development. In this study, eight elementary school teachers are guided in the development of motivationally-supportive mathematics lessons using ChatGPT as a tool to support student positive mathematics emotions, motivation, and engagement as theorized within Control Value Theory (CVT). Results reveal that teachers found ChatGPT useful for this purpose and that the lessons implemented demonstrated some success in fostering motivationally-supportive math activities. Compared to non-ChatGPT lessons, in lessons developed with ChatGPT, the same teachers used more utility value messages, more non-standard examples, and more specific feedback while engaging in less lesson-irrelevant chit-chat. Within these lessons, students also reported feeling less bored and provided fewer negatively-valenced comments compared to non-ChatGPT lessons. The results have implications for the use of ChatGPT as a lesson development tool and demonstrate the success of a CVT-framed intervention. ER - TY - JOUR T1 - A personalized learning system-supported professional training model for teachers' TPACK development AU - Chaipidech, Pawat AU - Srisawasdi, Niwat AU - Kajornmanee, Tanachai AU - Chaipah, Kornchawal JO - Computers and Education: Artificial Intelligence VL - 3 SP - 100064 PY - 2022 DA - 2022/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2022.100064 UR - https://www.sciencedirect.com/science/article/pii/S2666920X22000194 KW - Andragogy KW - TPACK KW - Personalized learning KW - In-service teacher KW - Teacher development AB - In contrast to traditional teacher professional development (TPD), the importance of individualized professional learning and expert content delivery is increasingly focused on as a challenge to transform the TPD. This study investigated the effects of an andragogical design of TPD with an embedded personalized learning system on technological pedagogical and content knowledge (TPACK) of in-service teachers. One hundred sixty-one in-service science teachers from 92 secondary schools located Northeastern region of Thailand voluntarily participated in the proposed TPD program. Results indicated that the in-service teachers significantly improved their TPACK. These findings add to the limited body of research on TPD that facilitates adult teachers' professional learning with the support of a personalized learning system to be equipped with the know-how to pedagogically apply digital technology into students’ learning experience in science. ER - TY - JOUR T1 - A metaphor-based robot programming approach to facilitating young children’s computational thinking and positive learning behaviors AU - Zhang, Xinli AU - Chen, Yuchen AU - Hu, Lailin AU - Bao, Yiwei AU - Tu, Yun-Fang AU - Hwang, Gwo-Jen JO - Computers & Education VL - 215 SP - 105039 PY - 2024 DA - 2024/07/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105039 UR - https://www.sciencedirect.com/science/article/pii/S0360131524000538 KW - Teaching/learning strategies KW - Improving classroom teaching KW - Pedagogical issues KW - Interactive learning environments KW - Metaphors KW - Computational thinking KW - Early childhood education AB - In the artificial intelligence age, cultivating young children's computational thinking (CT) has sparked tremendous attention. Programmable robotics is a developmental-appropriate and screen-free means that provides young children with great opportunities to learn programming and develop CT. However, it is reported that young children might have difficulties learning abstract CT concepts. As a helpful pedagogical facilitator, metaphors can help turn abstract concepts into more concrete and clear concepts that learners are familiar with. Therefore, this research proposed a metaphor-based robot programming (MRP) approach and explored its impact on young children's CT and behavioral patterns. A total of 118 children aged 5–6 were recruited in this experiment with two conditions: the experimental group adopted the metaphor-based robot programming (MRP) approach while the control group used the conventional robot programming (CRP) approach. Results revealed that children who adopted the MRP approach outperformed children who adopted the CRP approach on CT. In addition, behavioral analysis indicated that the proposed MRP approach could facilitate children's superior learning performance and more positive learning behaviors, so as to help them achieve learning objectives. Accordingly, this study can provide insightful guidance and inspiration for future research on effective programming teaching and CT development for young children. ER - TY - JOUR T1 - Governmental neoliberal teacher professionalism: The constrained freedom of choice for teachers’ professional development AU - Pereira, Andrew Joseph AU - Tay, Lee Yong JO - Teaching and Teacher Education VL - 125 SP - 104045 PY - 2023 DA - 2023/04/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2023.104045 UR - https://www.sciencedirect.com/science/article/pii/S0742051X23000331 KW - Professional development KW - Governmentality KW - Teachers' autonomy KW - Neoliberalism KW - Singapore AB - This study examines teachers' professional development (PD) decisions through the lens of governmental neoliberalism. Situated in the neoliberal paradigm of advancing free market ideals and principles, the study examines the paradox of teachers' constrained decisions in PD activities within the sociocultural context of Singapore. The findings help to illuminate some of the issues teachers face in PD decision-making. Recommendations are also discussed to enhance teachers’ autonomy for a governmentality to broaden education horizons. ER - TY - JOUR T1 - Can generative AI motivate management students? The role of perceived value and information literacy AU - Jose, Emily Maria K AU - Prasanna, Akshara AU - Kushwaha, Bijay Prasad AU - Das, Madhumita JO - The International Journal of Management Education VL - 22 IS - 3 SP - 101082 PY - 2024 DA - 2024/11/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.101082 UR - https://www.sciencedirect.com/science/article/pii/S1472811724001538 KW - KW - KW - KW - KW - KW - AB - Generative Artificial Intelligence (GenAI) is a disruptive technology that has started to be used among students in management education. However, the question is whether the utilisation of GenAI in educational settings stimulates students to engage in learning activities and broaden their knowledge base. Hence, this study investigates student motivation and perception of using GenAI (ChatGPT) technology in management education. A random sampling technique was employed to survey 478 students from various educational institutions in the southern region of India. The outcomes revealed that GenAI presents both prospects and hurdles in the domain of management education. The disruptive nature of this technology brings forth numerous opportunities for acquiring knowledge and augmenting one's cognitive capacity. Nonetheless, a cautious and accountable approach is imperative for the successful integration of GenAI into the of management education. Consequently, this study provides pragmatic implications for students, educators, and educational institutions. The effectiveness of GenAI in practical settings can be heightened by arranging interactive training sessions led by AI experts, devising easily accessible online educational modules, embedding AI proficiencies into educators through collaborative endeavors or specialized training programs, and establishing systematic assessment protocols to ensure continual improvement. ER - TY - JOUR T1 - A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomes AU - Lee, Sang Joon AU - Kwon, Kyungbin JO - Computers and Education: Artificial Intelligence VL - 6 SP - 100211 PY - 2024 DA - 2024/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100211 UR - https://www.sciencedirect.com/science/article/pii/S2666920X24000122 KW - Artificial intelligence KW - AI education KW - Systematic review KW - K-12 AB - AI education aims to teach AI concepts, essential knowledge, and skills related to the fundamental ideas in AI. As AI becomes increasingly prevalent in our daily lives, schools and educators have started to recognize the importance of AI education in K-12 schools. However, there have been a limited number of studies reporting on the implementation of AI education in classrooms. This systematic review aimed to provide an overview of the current state of AI education in K-12 schools, exploring topics, instructional approaches, and learning outcomes. Twenty-five peer-reviewed journal articles published between 2018 and 2023 were selected for this systematic review. The findings highlighted that various topics were covered in K-12 AI education, including fundamental AI concepts, different types of AI, AI applications, and ethical considerations related to AI. To facilitate meaningful learning experiences, educators frequently integrated hands-on activities and project-based learning. The findings supported the benefits of AI education in enhancing students' AI literacy, problem-solving skills, and ethical reflections on AI's societal impact. Furthermore, it fostered motivation, positive attitudes toward AI, and an interest in technology while inspiring career aspirations. It is recommended to develop tailored AI curricula, instructional strategies, and appropriate tools and resources that seamlessly integrate into various subjects within the standard school curriculum. ER - TY - JOUR T1 - Rewilding Curriculum: Cultivating Affective Dispositions for Co-agency, Collective Creativity, and Wellbeing with Children through Drama Pedagogy AU - Stephenson, Lisa JO - Thinking Skills and Creativity SP - 101823 PY - 2025 DA - 2025/04/15/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2025.101823 UR - https://www.sciencedirect.com/science/article/pii/S1871187125000720 KW - creativity KW - Creativity in Education KW - Arts and Humanities KW - imagination KW - Pedagogy AB - Research highlights the importance of providing learners with wellbeing literacy providing learners with the tools (competence) to understand and communicate their feelings and experiences and recognise the feelings of others (fostering relatedness). These aspects of learning are felt rather than taught. Whilst global organisations such as OECD Learning Compass 2030 and UNESCO Framework for Action 2030, provide normative discourses on the Global skills, knowledge, and attitudes that should be taught to equip young people to become ‘change agents’, this is yet to be reflected in educational policy in England. Drawing from longitudinal action research undertaken over eighteen months in an English primary school (ANON, 2023), the paper systematically explores children's affective engagement and meaning-making through drama pedagogy, inquiry, and story-making (Drama Worldbuilding). The concept of co-agency is applied to explore pupil engagement and action within the workshops. The paper responds to a critical need to understand and include pupils’ perspectives of learning through the arts addressing methodological gaps in empirical research into creative learning. The research evidences new ways to recognise and understand how collaborative drama pedagogy activates and distributes relational learning. Drawing from learners' perspectives, the data analysis reveals a set of malleable creativity and wellbeing dispositions (values, attitudes, mindset) that support a deeper articulation of how creative pedagogy works through meta-affect. The data also presents a model of affective knowledge co-creation evidencing how learners experience collective creativity. ER - TY - JOUR T1 - Stalemate? The complex relationship between educational chess and students’ skills AU - Choi, Álvaro AU - Hurtado, Marta AU - Santín, Daniel AU - Sicilia, Gabriela AU - Simancas, Rosa JO - Thinking Skills and Creativity VL - 57 SP - 101819 PY - 2025 DA - 2025/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2025.101819 UR - https://www.sciencedirect.com/science/article/pii/S1871187125000689 KW - Chess KW - Student evaluation KW - Primary education KW - Cognitive and non-cognitive skills AB - Over the last decade, an increasing number of countries have integrated chess as a pedagogical tool and even as core content of their academic curricula. Nonetheless, the evidence regarding the causal effects of chess on a range of skills remains inconclusive. We report new evidence of the impact of learning chess in school on a set of cognitive and non-cognitive skills of 12-year-old students to shed light on this matter. To do this, we take advantage of the implementation of a phase-in program introducing chess into a set of schools in Catalonia (Spain). This experimental setting enables us to estimate the causal effects of practicing educational chess at school on critical thinking, attention, patience, and risk aversion. Results show that, after one academic year, the differences between the treated and control group are not statistically significant for any of these outcomes. Students who took part in the chess program significantly outperformed the students in the control group only in terms of their chess-playing knowledge and proficiency. ER - TY - JOUR T1 - AI-powered personalized learning: Enhancing self-efficacy, motivation, and digital literacy in adult education through expectancy-value theory AU - Lyu, Wenwen AU - Salam, Zarina Abdul JO - Learning and Motivation VL - 90 SP - 102129 PY - 2025 DA - 2025/05/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2025.102129 UR - https://www.sciencedirect.com/science/article/pii/S0023969025000360 KW - AI-powered personalized learning KW - Digital literacy KW - Expectancy-value theory KW - Motivation, Self-efficacy KW - Adult EFL learners AB - Although the implementation of artificial intelligence (AI) in educational contexts has gained increasing prominence, empirical research specifically examining its influence on crucial learner-related variables (e.g., self-efficacy, motivation, and digital literacy) among adult male learners of English as a Foreign Language (EFL) in China remains limited. The present study addresses this gap by investigating the effects of AI-powered personalized learning interventions on these key constructs. A total of 183 intermediate-level Chinese male EFL learners were randomly assigned either to an experimental group (EG), which received AI-personalized instruction, or to a control group (CG), which engaged in traditional instruction methods. Data were gathered through pre- and post-intervention surveys and analyzed using independent t-tests. Results indicated that compared to participants in the CG, learners in the EG exhibited statistically significant improvements in self-efficacy, motivation, and digital literacy. These findings offer robust empirical evidence supporting the effectiveness of AI-personalized instructional strategies in enhancing essential learner attributes within the adult male EFL context in China. Thus, the study advocates for the strategic integration of AI-powered personalized learning, highlighting its considerable potential to optimize language learning outcomes within adult EFL education. ER - TY - JOUR T1 - Identity discourse in teacher education: Developments in national-cultural identities of pre-service teachers in Israel AU - David, Ohad JO - Teaching and Teacher Education VL - 153 SP - 104850 PY - 2025 DA - 2025/01/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2024.104850 UR - https://www.sciencedirect.com/science/article/pii/S0742051X24003834 KW - Identity discourse KW - Collective identity KW - National identity KW - Multicultural education KW - Teacher education KW - Portfolio AB - In our multi-cultural world, it is crucial that teachers have the ability to engage in dialogical and pluralistic discourse on identities. This qualitative study aimed to characterize the process that preservice teachers underwent in their course, “Identity Discourse in the Classroom,” in a teacher education college in Israel. The analysis focused on the development of their national-cultural identity. The results demonstrated that the students moved from ambiguity to clarity and reflexivity concerning their national-cultural identity. They also demonstrated that the course created an infrastructure for the emergence of a non-essentialist identity consciousness, one that reflects a moderate constructivist view. ER - TY - JOUR T1 - Meta-competences in complex environments: An interdisciplinary perspective AU - Zenk, Lukas AU - Pausits, Attila AU - Brenner, Barbara AU - Campbell, David F.J. AU - Behrens, Doris A. AU - Stöckler, Eva Maria AU - Oppl, Stefan AU - Steiner, Gerald JO - Thinking Skills and Creativity VL - 53 SP - 101515 PY - 2024 DA - 2024/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101515 UR - https://www.sciencedirect.com/science/article/pii/S1871187124000531 KW - Meta-competence KW - Interdisciplinarity KW - Complexity KW - VUCA KW - Expert round table KW - Transdisciplinarity KW - Dynamic capability KW - Improvisation KW - Higher education KW - Innovation AB - In today's increasingly complex, uncertain environments, disciplinary knowledge alone is no longer sufficient to cope with new societal challenges and real-world problems. Meta-competences, which include advanced thinking skills and creativity, go beyond these domain-specific competences. Along those lines, a methodological question arises regarding how such a complex phenomenon can be investigated and adequately described. In our research, we applied proposition-based expert round tables, a method developed to analyze complex real-world problems. In a two-year project, eight experts from the University for Continuing Education Krems collaborated in an interdisciplinary approach including system and innovation research, management science, engineering, the arts and humanities, and higher education. Each expert proposed what meta-competences entail from their own perspective, and the different knowledge was subsequently reviewed, analyzed, and integrated following a collaborative approach over the course of several iterative discourses. As a result, the experts produced an integrative model with four interdependent factors of readiness: (1) iterative learning to continuously expand one's competences, (2) resilient improvisation to deal with unexpected events, (3) dynamic viability to cope effectively with volatile environments, and (4) sustainable innovation to co-creatively innovate. Those factors interact and reinforce each other and should ultimately enhance one's readiness to continually apply knowledge gained in new contexts and communicate that application accordingly. Meta-competences have, thus far, been discussed only in certain scientific disciplines. In our study we conducted expert round tables to continuously generate in-depth interdisciplinary knowledge that can be applied to other complex, real-world phenomena. The result is an initial interdisciplinary model that offers a relatively comprehensive view on the meta-competences required in today's increasingly complex environments. ER - TY - JOUR T1 - Exploring the role of intrinsic motivation in ChatGPT adoption to support active learning: An extension of the technology acceptance model AU - Lai, Chung Yee AU - Cheung, Kwok Yip AU - Chan, Chee Seng JO - Computers and Education: Artificial Intelligence VL - 5 SP - 100178 PY - 2023 DA - 2023/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100178 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000577 KW - Technology acceptance model KW - ChatGPT KW - Intrinsic motivation KW - Chatbot KW - Active learning AB - Background ChatGPT, a powerful artificial intelligence chatbot, has great potential for active learning because of its ability to generate instant responses to academic inquiries and foster spontaneous interactions. Purpose This exploratory study investigated the roles of intrinsic motivation and factors of the technology acceptance model that influence ChatGPT acceptance for active learning among undergraduates in Hong Kong. Method Using a structural equation modeling approach, we examined the extended technology acceptance model in the context of higher education. Using self-report questionnaires, we obtained useful responses from 473 undergraduate students in Hong Kong in July 2023. The reliability and validity of the data were measured using confirmatory factor analysis, followed by path analysis to investigate the hypotheses in the proposed model. Results We identified intrinsic motivation as the strongest motivator for ChatGPT use intention. Consistent with the prior literature on technology acceptance, perceived usefulness was found to be a strong predictor of behavioral intention. In contrast to extant research, the findings indicate no significant relationship between perceived ease of use and behavioral intention. Neither perceived usefulness nor perceived ease of use were significant mediators in the relationship between intrinsic motivation and behavioral intention. Conclusion These findings highlight the significant effect of intrinsic motivation on ChatGPT acceptance in supporting students’ active learning. They also provide inspiration for ChatGPT developers and educationalists regarding the importance of intrinsic and extrinsic motivation (perceived usefulness) in promoting the broader acceptance of chatbots in the educational context. Efforts should be made to improve students’ positive subjective experiences and the response quality of ChatGPT. ER - TY - JOUR T1 - Under the shadows of COVID-19: school principals’ leadership odyssey AU - Baloch, Fozia Ahmed AU - Jogezai, Nazir Ahmed JO - International Journal of Educational Management VL - 38 IS - 7 SP - 1925 EP - 1943 PY - 2024 DA - 2024/09/05/ SN - 0951-354X DO - https://doi.org/10.1108/IJEM-02-2024-0125 UR - https://www.sciencedirect.com/science/article/pii/S0951354X24000838 KW - Leadership KW - Educational leadership KW - Leadership orientation KW - Principals KW - COVID-19 KW - Pandemic KW - Pakistan AB - Purpose The COVID-19 pandemic, as well as its effects on education in general, has influenced the leadership landscape of school principals, which may have necessitated adaptations and transitions in their leadership orientation. To better comprehend any variations in the leadership orientation of school principals in response to the implications of the COVID-19 pandemic, this study examines leadership orientation in both the pre-pandemic and post-pandemic periods. Design/methodology/approach In this quantitative research, the authors collected data from 297 school principals in the Balochistan province of Pakistan using the leadership orientation survey (LOS) in a quantitative research approach. Findings The results indicated that principals’ leadership orientation underwent an observable transition before and after the pandemic. Principals’ preferred leadership orientation notably changed from solely political before the pandemic to a combination of highly political and symbolic after the pandemic. Research limitations/implications Using a survey, the study investigated the transition in school principals’ leadership orientation before and after the pandemic. However, the results do not explain what caused the transition in principals’ leadership orientation, which is the key limitation of this study. Future research within a qualitative approach can study the factors associated with changes in principles’ leadership frames. Practical implications The overall findings of the study have implications for scholars, policymakers and educational leaders to reexamine and gain a deeper understanding of the leadership roles of principals in the post-pandemic age. This is because principals now operate in a distinct context characterized by new difficulties and opportunities compared to the pre-pandemic period. Originality/value This is an original study that examined the transition of school principals’ leadership orientation before and after the pandemic. The body of literature related to the transition between pre- and post-pandemic is limited both in Pakistan and the rest of the world. This study illuminates the literature in this regard. ER - TY - JOUR T1 - Engagement as antecedent of academic achievement and the moderating impact of work-family-school inter-role conflict for online graduate students AU - Hernández González, Claudia Araceli AU - Blackford, Benjamin John JO - The International Journal of Management Education VL - 20 IS - 3 SP - 100676 PY - 2022 DA - 2022/11/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2022.100676 UR - https://www.sciencedirect.com/science/article/pii/S1472811722000787 KW - Graduate students KW - Online education KW - Student engagement KW - Inter-role conflict KW - Intrinsic motivation AB - Higher education has changed as the prevalence of online education has increased. More adults with full time jobs are returning for a graduate education and many of them choose the online modality due to their responsibilities, priorities, and sources of support. Therefore, we need to analyze factors that make online graduate students successful in their educational journey. Using a time-lagged sample of 244 online graduate students this study employed SEM to examine the role of intrinsic motivation, engagement, and work-school-family inter-role conflict in the success of online graduate students. Results show students' intrinsic motivation has a positive impact on student success measured by self-reported learning (β = 0.33, ρ < 0.01, R2 = 0.12) and grade (β = 0.21, ρ < 0.01, R2 = 0.05). Engagement partially mediates the relationship, greatly increasing the explanatory power of the model (learning R2 = 0.34, grade R2 = 0.09). Work-school-family inter-role conflict moderates this relationship, significantly weakening the positive relationship between intrinsic motivation and engagement (β = −.14, ρ < 0.01). These findings increase our understanding of elements impacting students’ success. Recommendations on how to maximize the positive impact of intrinsic motivation on engagement and reduce the negative impact of inter-role conflict, as well as suggestions for future research in the area, are provided. ER - TY - JOUR T1 - Digital competence in higher education research: A systematic literature review AU - Zhao, Yu AU - Pinto Llorente, Ana María AU - Sánchez Gómez, María Cruz JO - Computers & Education VL - 168 SP - 104212 PY - 2021 DA - 2021/07/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2021.104212 UR - https://www.sciencedirect.com/science/article/pii/S0360131521000890 KW - Digital competence KW - Higher education KW - 21st century abilities AB - In the information and knowledge society, where technology develops rapidly and penetrates deeply into our lives, the discussion about digital competence has become a hot topic today. After the emergence of the Coronavirus (Covid-19) and with its huge impact on the education industry, the concern about digital competence has reached a new height. This systematic literature review uses Web of science and Scopus as databases to store and analyze the existing research on digital competence in higher education settings. The purpose of this review is to provide the scholar community with a current overview of digital competence research from 2015 to 2021 in the context of higher education regarding the definition of digital competence, dimensions used to evaluate digital competence, research purposes, methodologies, and results and limitations. Major findings include that the majority of publications cited both research and EU policy in describing the definition of digital competence. The review indicates that most university students and teachers have a basic level of digital competence. Besides, the institutions of higher education are encouraged to focus on the development students and teachers’ digital competence, create relevant learning strategies and use appropriate tools to improve the quality of education. ER - TY - JOUR T1 - Exploring creativity in mathematics assessment: An analysis of standardized tests AU - Bicer, Ali AU - Aldemir, Tugce AU - Krall, Geoff AU - Quiroz, Fay AU - Chamberlin, Scott AU - Nelson, Jana L. AU - Lee, Yujin AU - Kwon, Hyunkyung JO - Thinking Skills and Creativity VL - 54 SP - 101652 PY - 2024 DA - 2024/12/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101652 UR - https://www.sciencedirect.com/science/article/pii/S1871187124001901 KW - Mathematical creativity KW - Assessment for creativity KW - Creativity-directed tasks AB - This paper aims to investigate whether US standardized tests provide opportunities for students to demonstrate their creative thinking abilities through the inclusion of creativity-directed problems in their mathematics assessments. Our results indicated that two commonly used standardized national tests (i.e., PARCC and SBAC) do offer students some opportunities to exhibit their creative thinking skills by incorporating creativity-directed problems (e.g., multiple solution tasks) in their assessments. However, not all creativity-directed tasks are present at every grade level. The findings of this paper are significant not only because they reveal the potential of these tests to include creativity-directed tasks but also because they underscore the importance of assessment materials in fostering students’ creative thinking skills in mathematics, as assessments significantly influence teachers’ instructional practices and curriculum materials. ER - TY - JOUR T1 - The Googlization of the classroom: Is the UK effective in protecting children's data and rights? AU - Livingstone, Sonia AU - Pothong, Kruakae AU - Atabey, Ayça AU - Hooper, Louise AU - Day, Emma JO - Computers and Education Open VL - 7 SP - 100195 PY - 2024 DA - 2024/12/01/ SN - 2666-5573 DO - https://doi.org/10.1016/j.caeo.2024.100195 UR - https://www.sciencedirect.com/science/article/pii/S2666557324000351 KW - Google Classroom KW - Children's rights KW - Educational technology KW - Data protection KW - Commercial exploitation KW - Socio-legal analysis AB - There has been an explosion in uses of educational technology (EdTech) to support schools’ teaching, learning, assessment and administration. This article asks whether UK EdTech and data protection policies protect children's rights at school. It adopts a children's rights framework to explore how EdTech impacts children's rights to education, privacy and freedom from economic exploitation, taking Google Classroom as a case study. The research methods integrate legal research, interviews with UK data protection experts and education professionals working at various levels from national to local, and a socio-technical investigation of the flow of children's data through Google Classroom. The findings show that Google Classroom undermines children's privacy and data protection, potentially infringing children's other rights. However, they also show that regulation has impacted on Google's policy and practice. Specifically, we trace how various governments’ deployment of a range of legal arguments has enabled them to regulate Google's relationship with schools to improve its treatment of children's data. Although the UK government has not brought such actions, the data flow investigation shows that Google has also improved its protection of children's data in UK schools as a result of these international actions. Nonetheless, multiple problems remain, due both to Google's non-compliance with data protection regulations and schools’ practices of using Google Classroom. We conclude with a blueprint for the rights-respecting treatment of children's education data that identifies needed actions for the UK Department for Education, data protection authority, and industry, to mitigate against harmful practices and better support schools. ER - TY - JOUR T1 - Enhancing academic performance of business students using generative AI: An interactive-constructive-active-passive (ICAP) self-determination perspective AU - Gao, Ziyi AU - Cheah, Jun-Hwa AU - Lim, Xin-Jean AU - Luo, Xi JO - The International Journal of Management Education VL - 22 IS - 2 SP - 100958 PY - 2024 DA - 2024/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.100958 UR - https://www.sciencedirect.com/science/article/pii/S1472811724000296 KW - ChatGPT KW - Technology integration KW - ICAP framework KW - Self-determination theory KW - Academic performance KW - Epistemic curiosity AB - Generative artificial intelligence (GAI) tools, such as ChatGPT, have emerged as valuable assets in higher education. Despite their potential benefits in academic support, questions persist about the concrete advantages of integrating this technology into learning processes and its impact on academic outcomes. This research addresses this gap by investigating the influence of technology integration on academic performance, employing the Interactive-Constructive-Active-Passive (ICAP) framework and self-determination theory. The empirical findings from Chinese business students using Wenjuanxing platform reveal a positive impact of technology integration on business students' motivation, encompassing their learning desires, self-efficacy, and future beliefs, ultimately leading to enhanced academic performance. Notably, while epistemic curiosity augments the effects of technology integration on learning desires and future beliefs, its influence on self-efficacy is not significant. This suggests that curiosity alone might not be enough to alter deeply ingrained beliefs about one’s capabilities. In conclusion, this study underscores the academic significance of these findings and their practical implications for educators and business students in optimizing ChatGPT’s potential for academic success. ER - TY - JOUR T1 - Unlocking the secrets of STEM success: Exploring the interplay of motivation to learn science, self-regulation, and emotional intelligence from a perspective of self-determination theory AU - Lei, Yumei JO - Learning and Motivation VL - 87 SP - 102012 PY - 2024 DA - 2024/08/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2024.102012 UR - https://www.sciencedirect.com/science/article/pii/S0023969024000547 KW - Emotional intelligence KW - Motivation to learn science KW - Self-determination theory KW - Self-regulated learning KW - STEM AB - The key to excellence in Science, Technology, Engineering, and Mathematics (STEM) disciplines requires mastery of the dynamics that underlie student learning and achievement. Among these factors, self-regulated learning, motivation, and emotional intelligence play critical but distinct roles in attaining academic outcomes. However, the relationships among these educational and psychological factors are not fully understood from the perspective of self-determination theory. This study delves into the intricate relationship between emotional intelligence, motivation to learn science, and self-regulated learning among Chinese STEM students. A sample of 650 undergraduate STEM students from various universities in China participated in this study. The pilot test was conducted before distributing the questionnaires, including the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), the Science Motivation Questionnaire II (SMQ-II), and the Motivated Strategies for Learning Questionnaire (MSLQ). Using the structural equation modeling, this study found a significant correlation between self-regulated learning, motivation to learn science, and emotional intelligence. Moreover, the study showed the predictive role of self-regulated learning in determining STEM students’ emotional intelligence and motivation to learn science. This study provided some important implications for policy-makers and instructors in considering self-determination theory in STEM education and developing STEM students’ motivation, emotional intelligence, and self-regulated learning to enhance educational outcomes. ER - TY - JOUR T1 - An integrated framework for Gen AI-assisted management learning: Insights from Kolb's learning cycle theory and knowledge types perspectives AU - Kuo-Wei, Lee JO - The International Journal of Management Education VL - 23 IS - 2 SP - 101164 PY - 2025 DA - 2025/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2025.101164 UR - https://www.sciencedirect.com/science/article/pii/S1472811725000345 KW - Management learning KW - Gen AI-Assisted learning KW - Learning cycle theory KW - Knowledge types KW - ChatGPT AB - Generative Artificial Intelligence (Gen AI), particularly through advanced models such as ChatGPT developed on the foundation of sophisticated Large Language Models (LLMs), has shown the potential to revolutionize management education. Nevertheless, a comprehensive framework for employing Gen AI in this context remains to be developed. This study proposes a theoretical framework utilizing Gen AI, with a specific focus on ChatGPT, based on Kolb's learning cycle theory and the knowledge type perspective to facilitate systematic integration into management learning. Analyzing data from 348 business students through structural equation modeling, the study demonstrates that the Gen AI -assisted learning process enhances the acquisition of diverse knowledge types. The findings also highlight that teacher support partially strengthens the effectiveness of the Gen AI -assisted learning process in knowledge acquisition. The study contributes to the academic discourse by developing an integrated framework and practical guidelines for integrating Gen AI into management learning, thereby addressing an existing gap in current research. ER - TY - JOUR T1 - A profession in crisis? Teachers' responses to England's high-stakes accountability reforms in secondary education AU - Towers, Emma AU - Gewirtz, Sharon AU - Maguire, Meg AU - Neumann, Eszter JO - Teaching and Teacher Education VL - 117 SP - 103778 PY - 2022 DA - 2022/09/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2022.103778 UR - https://www.sciencedirect.com/science/article/pii/S0742051X22001524 KW - Profession in crisis KW - Secondary school reforms KW - Teacher wellbeing KW - Teacher attrition AB - There has been a tendency to construct the teaching profession through a narrative of ‘crisis’ which places particular emphasis on high rates of attrition and poor wellbeing driven by a demanding work culture. Drawing on qualitative data from a mixed-methods study, this paper examines teachers' responses to reforms to English secondary education. It presents evidence that supports a ‘profession in crisis’ narrative with many of the research participants expressing negative attitudes towards the reforms and concerns about staying in teaching. However, the paper also illuminates a counter-narrative that highlights teachers' job satisfaction and their desire to remain in the profession. ER - TY - JOUR T1 - Exploring the potential of GenAI for personalised English teaching: Learners' experiences and perceptions AU - Kohnke, Lucas AU - Zou, Di AU - Su, Fan JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100371 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100371 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000116 KW - Artificial intelligence KW - Generative artificial intelligence KW - Personalised learning KW - English language education KW - ChatGPT AB - Artificial intelligence has become seamlessly integrated into personal, professional, and educational spheres. Generative AI (GenAI), in particular, is revolutionising content creation in second language (L2) writing instruction through advanced machine learning models. This study examines the influence of GenAI on L2 learners' language competencies, focusing on tools commonly used by first-year English for Academic Purposes students. Through qualitative and quantitative analysis, including surveys and interviews, this research explored students’ experiences and perceptions of GenAI tools, including Grammarly and Quillbot. The findings revealed that two-thirds of the students (66.7%) regularly used these tools, which they found particularly helpful for improving grammar, writing, vocabulary, and reading skills. Interview insights indicated that the students appreciated the personalised feedback and creative support provided by GenAI tools, although they also acknowledged risks such as irrelevant feedback and potential overreliance. We suggest that while GenAI tools enhance language learning by providing personalised and adaptive support, they should complement rather than replace traditional methods. Our results underscore the need for professional development for educators and the establishment of guidelines to address academic integrity and data privacy. ER - TY - JOUR T1 - The shifting landscape of student engagement: A pre-post semester analysis in AI-enhanced classrooms AU - Bognár, László AU - Khine, Myint Swe JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100395 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100395 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000359 KW - AI-based chat tools KW - Student engagement KW - Academic self-efficacy KW - Autonomy KW - Self-regulation KW - Intrinsic motivation KW - Pre-post study KW - Educational technology KW - Personalized learning KW - AI-Enhanced learning AB - The rapid integration of AI-based tools in education calls for a critical assessment of how these technologies impact student engagement. This study explores the perceived effects of AI chat tools by analyzing pre- and post-semester survey data from 724 to 642 students, respectively, across diverse disciplines and demographic groups. Initially, students reported high levels of engagement in key areas such as academic self-efficacy, autonomy, interest, and self-regulation. However, by the semester's end, all these areas showed a noticeable decline. This suggests that while AI tools offer initial benefits, their long-term effectiveness in maintaining engagement may be limited due to challenges in integrating the tools consistently or the novelty effect fading. To capture and quantify these trends effectively we used four latent engagement factors—Academic Self-Efficacy and Preparedness, Autonomy and Resource Utilization, Interest and Engagement, and Self-Regulation and Goal Setting—identified in our previous comprehensive factor analysis. Despite the overall decline, certain groups of students and specific conditions led to not only maintaining but even improving engagement levels. This study highlights the importance of tailored strategies that consider aspects such as age, discipline, usage frequency, duration of use, quality of teacher support, and the type of AI used to maximize the benefits of AI in education. These strategies can sometimes counterbalance the decline, ensuring the long-term effectiveness of AI-enhanced learning environments. ER - TY - JOUR T1 - Digital ambitions vs. classroom reality in Norwegian lower secondary schools: What digital competencies are students developing over time? AU - Kure, Astrid Elisabeth AU - Blikstad-Balas, Marte AU - Brevik, Lisbeth M. JO - Teaching and Teacher Education VL - 153 SP - 104843 PY - 2025 DA - 2025/01/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2024.104843 UR - https://www.sciencedirect.com/science/article/pii/S0742051X24003767 AB - Despite high political ambitions, the increased use of digital technology in lower secondary school has resulted in little indication of the advanced use of digital skills. Drawing on video-recorded lessons (N = 29) from five schools in Norway over time and across two national curricula, this study mapped the opportunities students had to develop digital skills in English classrooms. The findings provide nuanced insight into the instruction of digital skills in highly digitalised schools. Despite a slight increase in digital skills after the 2020 reform, our findings indicate that digital ambitions in the curriculum were not reflected in classroom reality. ER - TY - JOUR T1 - Unplugged activities in the elementary school mathematics classroom: The effects on students’ computational thinking and mathematical creativity AU - Hu, Linlin AU - Wang, Hao JO - Thinking Skills and Creativity VL - 54 SP - 101653 PY - 2024 DA - 2024/12/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101653 UR - https://www.sciencedirect.com/science/article/pii/S1871187124001913 KW - Mathematics KW - Unplugged activities KW - Computational thinking KW - Mathematical creativity AB - The rapid development of artificial intelligence technology has led to the proliferation of computational thinking (CT) education. However, research on unplugged activities’ influence in elementary math classrooms is limited, despite some exploring programming's cognitive benefits. This study presents both qualitative and quantitative analyzes stemming from a ten-week quasi-experimental research endeavor, specifically tailored for third-grade students. The research devised a series of unplugged activities, encompassing mathematical games, hands-on construction of mathematical logic boards, and calculating shopping discounts. The overarching objective was to investigate the impact of these unplugged activities on students’ mathematical creativity and CT. Students participating in a mathematics curriculum based on unplugged activities (N = 47) were compared with students participating in a traditional lecture-based mathematics curriculum (N = 46). The results indicated that unplugged activities exhibited significant advantages in fostering students’ CT and mathematical creativity across three dimensions, namely, problem-posing creativity (t = 5.830, p < 0.01), problem-solving creativity (t = 6.633, p < 0.01), and creative self-efficacy (t = 7.554, p < 0.01). Furthermore, the study revealed a relationship between students’ mathematical creativity as a predictor of CT. The results of the quantitative analysis were supported by the teacher's and students’ interview data, and the students felt excited and interested in the unplugged activities, whereas some students using the lecture-based method reported boredom and lack of interactivity. This research offered valuable insights for mathematics and CT education practice, underscoring unplugged activity as an innovative instructional approach that brings forth new possibilities for traditional mathematics teaching, with potential applications in the K-12 curriculum. ER - TY - JOUR T1 - Effects of AI understanding-training on AI literacy, usage, self-determined interactions, and anthropomorphization with voice assistants AU - Markus, André AU - Pfister, Jan AU - Carolus, Astrid AU - Hotho, Andreas AU - Wienrich, Carolin JO - Computers and Education Open VL - 6 SP - 100176 PY - 2024 DA - 2024/06/01/ SN - 2666-5573 DO - https://doi.org/10.1016/j.caeo.2024.100176 UR - https://www.sciencedirect.com/science/article/pii/S266655732400017X KW - Voice assistant KW - AI learning KW - AI literacy KW - Machine Learning KW - Anthropomorphism KW - AI education AB - Intelligent voice assistants (IVAs) such as Alexa or Siri are voice-based Artificial Intelligence systems that help users with various everyday tasks using simple voice commands. However, users often only have a superficial understanding of how the Artificial Intelligence (AI) integrated into IVAs works, which leads to misunderstandings and potential risks of use. To promote self-determined interaction with IVAs, the development of specific AI-related skills, such as a comprehensive understanding of AI, is crucial. Based on learning psychology and media pedagogy principles, two online training modules were developed to deepen the understanding of AI concerning IVAs and enable self-determined interaction. A total of 99 participants took part in the training. The results show that the training promotes both understanding of AI and AI literacy. It also increases the intention to use IVAs, promotes a positive attitude, and enhances the willingness for self-determined interaction. In addition, the training contributes to a more realistic assessment of the IVAs' capabilities and reduces anthropomorphic perceptions. Overall, the study emphasizes the relevance of specific AI skills and shows how targeted training can contribute to improving these skills. Thus, the present work contributes to improving the availability of digital education programs. ER - TY - JOUR T1 - Behavioral-pattern exploration and development of an instructional tool for young children to learn AI AU - Hsu, Ting-Chia AU - Abelson, Hal AU - Lao, Natalie AU - Tseng, Yu-Han AU - Lin, Yi-Ting JO - Computers and Education: Artificial Intelligence VL - 2 SP - 100012 PY - 2021 DA - 2021/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2021.100012 UR - https://www.sciencedirect.com/science/article/pii/S2666920X21000060 KW - Artificial intelligence education KW - Interdisciplinary instructional tool KW - Behavioral patterns AB - This study aimed at developing an instructional tool for the artificial intelligence education of young students, and used learning analytics to identify the sequential learning behavioral patterns of students during the process of learning with the instructional tool. The instructional experiment took 9 weeks. The first stage of the course was 5 weeks spent on individual learning of MIT App Inventor and Personal Image Classifier. The second stage was 4 weeks spent on cooperative learning to make a robot car and play a computational thinking board game. In the second stage, the students worked in pairs to make the robot car. Finally, they played the computational thinking board game with the personal image classification application they developed in the first stage and the robot car they made in the second stage. The innovative studies found meaningful behavioral patterns when the young students learned the application of artificial intelligence with the instructional tool developed and proposed in the study. ER - TY - JOUR T1 - Effect of a person-centred, tailor-made, teaching practice-oriented training programme on continuous professional development of STEM lecturers AU - Brouwer, Natasa AU - Joling, Erik AU - Kaper, Wolter JO - Teaching and Teacher Education VL - 119 SP - 103848 PY - 2022 DA - 2022/11/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2022.103848 UR - https://www.sciencedirect.com/science/article/pii/S0742051X22002220 KW - Professional development KW - Higher education KW - STEM lecturers KW - University teaching qualification AB - This study contributes to the understanding of the effects of a person-centred, tailor-made, teaching practice-oriented professional development programme on the continuous professional development of university lecturers in STEM (Science, Technology, Engineering and Mathematics). A mixed qualitative and quantitative method was used. A significant proportion of the participants showed a shift in their ambitions for their further professional development toward the competence of organising teaching. Semi-structured interviews with five representative participants, five years after obtaining the University Teaching Qualification (UTQ), showed a long-term effect. All five interviewed lecturers followed their intentions and some even exceeded them. ER - TY - JOUR T1 - Self-determination theory perspectives on the influence of digital learning engagement on motivation in extracurricular learning activities: Considering the mediating role of digital self-efficacy AU - Dong, Diwen JO - Learning and Motivation VL - 90 SP - 102135 PY - 2025 DA - 2025/05/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2025.102135 UR - https://www.sciencedirect.com/science/article/pii/S0023969025000426 KW - Digital learning engagement KW - Digital self-efficacy KW - EFL learners KW - Extracurricular learning activities KW - Motivation KW - Self-Determination Theory KW - Structural Equation Modeling AB - The increasing integration of digital media in educational settings has generated considerable interest in exploring its effects on learners' engagement, motivation, and digital self-efficacy, particularly within extracurricular learning activities (ELAs). Understanding how these constructs interact in extracurricular settings is crucial. This research, anchored in Self-Determination Theory (SDT), aimed to investigate the connection between engagement with digital media and motivation in the ELAs, emphasizing the mediating function of digital self-efficacy in China. Utilizing a quantitative research methodology, data collected from 286 secondary school students through validated survey instruments that measured their engagement with digital media, digital self-efficacy, and online learning motivation. The study implemented Structural Equation Modeling (SEM) to analyze the interrelations among these constructs. Results indicated a strong positive relationship between digital media engagement and motivation for online learning, suggesting that the students who actively utilize digital tools tend to demonstrate greater motivation in the ELAs. Additionally, a significant association exists between digital media engagement and digital self-efficacy, indicating that regular interaction with digital platforms enhances learners’ self-confidence regarding their ability to navigate these environments efficiently. Crucially, digital self-efficacy acts as a mediator between digital media engagement and motivation, underscoring the critical role of perceived competence in maintaining student motivation in technology-enhanced learning settings. These results carry practical implications for educators, policymakers, and curriculum developers. Specifically, they stress the importance of creating interventions that enhance digital self-efficacy, such as targeted training programs and supportive digital learning environments, ultimately amplifying learners’ engagement and their motivation in their learning experiences. ER - TY - JOUR T1 - The role of ChatGPT and grammarly in promoting emotion regulation, psychological well-being, motivation, and academic writing in Chinese college students: A self-determination theory perspective AU - Wang, Caili AU - Wang, BingCheng AU - Xu, Duoshu JO - Learning and Motivation VL - 90 SP - 102131 PY - 2025 DA - 2025/05/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2025.102131 UR - https://www.sciencedirect.com/science/article/pii/S0023969025000384 KW - Artificial Intelligence KW - Emotional regulation KW - Motivation KW - Academic writing KW - Psychological well-being KW - Self-determination theory KW - China AB - The increasing integration of artificial intelligence (AI)-powered tools in educational settings necessitates empirical examination of their impact on students' holistic development, particularly within the context of higher education in China. This study aimed to investigate the efficacy of ChatGPT and Grammarly in enhancing emotional regulation and its subsequent effects on motivation, psychological well-being, and academic writing proficiency among Chinese college students. Utilizing a quasi-experimental design, the research involved 94 participants from a major Chinese college, selected through convenience sampling to ensure accessibility and feasibility. Participants were divided into three groups: an experimental group using Grammarly, an experimental group using ChatGPT, and a control group receiving traditional instruction. The required data collected using validated questionnaires were analyzed using a one-way ANOVA. Findings documented that both AI-powered tools significantly improved emotion regulation and psychological well-being while positively impacting the students' motivation and the quality of their academic writing. These results lend support to the potential of AI-powered tools to foster holistic student development within the specific context of Chinese higher education and offer valuable insights for stakeholder seeking to integrate AI effectively into similar learning environments. ER - TY - JOUR T1 - Exploring students’ experience of ChatGPT in STEM education AU - Valeri, Federico AU - Nilsson, Pernilla AU - Cederqvist, Anne-Marie JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100360 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100360 UR - https://www.sciencedirect.com/science/article/pii/S2666920X24001632 KW - ChatGPT KW - Secondary education KW - Artificial intelligence KW - AI literacy KW - Large language models KW - Prompting strategies AB - The rapid advances in AI technologies showed a disruptive potential in educational practices, presenting new challenges and generating new opportunities. This phenomenon has been exacerbated since the release of ChatGPT in 2022, which has permanently transformed various educational activities and sparked widespread scientific interest. Research suggests that ChatGPT can help students navigate the complexities of STEM subjects. However, only a few studies have directed attention to the use of ChatGPT in STEM subjects in upper secondary education. With the purpose of addressing this gap, the aim of this study is to explore how students experience ChatGPT for their STEM studies, encompassing their usage, perceptions, and general knowledge about this technology. Using a mixed methods approach, the data collected included a survey and semi-structured interviews involving upper secondary students. The results show widespread adoption of ChatGPT across STEM subjects among participants, particularly in biology and especially as a tool to support the understanding of concepts. Although students exhibited limited knowledge of AI, they demonstrated some effective prompting strategies to generate relevant content and tackle potential inaccuracies and hallucinations. The findings in this paper provide insights to support the exploration of students’ experiences of ChatGPT, presenting relevant topics to further research the applications of these AI technologies within STEM subjects, given their importance for future societal development. ER - TY - JOUR T1 - Unfolding key factors of resilience in ICT cognitive-motivational engagement: Global evidence from machine learning techniques AU - Zheng, Jia-qi AU - Cheung, Kwok-cheung AU - Sit, Pou-seong AU - Lam, Chi-chio JO - International Journal of Educational Research VL - 131 SP - 102607 PY - 2025 DA - 2025/01/01/ SN - 0883-0355 DO - https://doi.org/10.1016/j.ijer.2025.102607 UR - https://www.sciencedirect.com/science/article/pii/S0883035525000813 KW - ICT engagement KW - Machine learning KW - Pisa;Resilience AB - With the rapid growth of information and communication technology (ICT), educational resilience in the digital world has gained increasing scholarly attention. Nevertheless, few studies regarded ICT engagement as an adjustment outcome in the process of resilience. Based on the self-determination theory, ICT engagement involves ICT interest, perceived ICT competence, perceived autonomy related to ICT use, and perceived social interaction in ICT use. Using data from 53 countries/economies in the Programme for International Student Assessment (PISA) 2018 dataset, our study aims to unfold key factors of resilience in ICT engagement from a global perspective and compare the classification performance of four machine learning models to discriminate resilient students from non-resilient students. By implementing four machine learning techniques [i.e., Logistic Regression (LR), Decision Tree (DT), Random Forests (RF), Support Vector Machine (SVM)], 15 key factors were selected from 102 contextual features to discriminate resilient students from non-resilient students in ICT engagement. Surprisingly, the results indicated that ICT usage for entertainment was the most predominant factor. Rather than the amount of ICT resources, intrinsic motivation in ICT usage was identified as the fundamental factor of resilience in ICT engagement. In addition, SVM and RF showed better stability and classification abilities than LR and DT. Our research findings not only broaden the operational definition of educational resilience but also develop a methodological paradigm for implementing machine learning techniques in resilience research. This study provides significant implications for educators to foster students’ intrinsic motivation with ICT-supported teaching strategies, which further enhances their resilience in ICT engagement. ER - TY - JOUR T1 - How Do ChatGPT's Benefit–Risk Paradoxes Impact Higher Education in Taiwan and Indonesia? An Integrative Framework of UTAUT and PMT with SEM & fsQCA AU - Hsu, Wen-Ling AU - Silalahi, Andri Dayarana K. AU - Tedjakusuma, Adi Prasetyo AU - Riantama, Dalianus JO - Computers and Education: Artificial Intelligence SP - 100412 PY - 2025 DA - 2025/04/24/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100412 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000529 KW - artificial intelligence KW - benefit-coping-risk KW - chatgpt in education KW - fsqca KW - education KW - technology adoption AB - The integration of ChatGPT into higher education in Taiwan and Indonesia presents both opportunities and challenges, creating a paradox of benefits and risks that must be carefully managed. While previous studies have explored its applications, the complexities of ChatGPT's impact on education have not been fully addressed. This study fills that gap by combining the Unified Theory of Acceptance and Use of Technology (UTAUT) with Protection Motivation Theory (PMT) to examine ChatGPT’s role through a benefit-risk-coping mechanism. Data were collected from higher education users in Taiwan and Indonesia. The Structural Equation Modeling (SEM) results reveal distinct patterns in the two countries. In Taiwan, perceived severity negatively influences the intention to use ChatGPT, while self-efficacy plays a key role in adoption. In contrast, Indonesian users emphasize response efficacy and performance expectancy as stronger predictors of usage intention. Task efficiency and performance expectancy enhance usage intention in both countries, with Indonesia showing a stronger link between intention and actual use. Additionally, the fuzzy sets Qualitative Comparative Analysis (fsQCA) identifies diverse configurations for actual usage and disusage of ChatGPT. Task efficiency and performance expectancy are key drivers of usage in both Taiwan and Indonesia. However, disusage in Taiwan is mainly due to task inefficiency, while multiple factors, including low self-efficacy, contribute to disusage in Indonesia. These findings offer practical insights for higher education institutions, providing strategies to optimize ChatGPT’s benefits while minimizing risks and ensuring its responsible use in educational settings across Taiwan and Indonesia. ER - TY - JOUR T1 - Exploring English language learning via Chabot: A case study from a self determination theory perspective AU - Annamalai, Nagaletchimee AU - Eltahir, Mohd Elmagzoub AU - Zyoud, Samer H. AU - Soundrarajan, Deepa AU - Zakarneh, Bilal AU - Al Salhi, Najeh Rajeh JO - Computers and Education: Artificial Intelligence VL - 5 SP - 100148 PY - 2023 DA - 2023/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100148 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000279 KW - Chatbot KW - Motivation KW - Self-determination theory KW - English language AB - This study applied Self Determination Study to understand 25 undergraduate students' motivation to learn the English language via chatbot. The data collected from interviews were categorized based on three psychological needs of learners: autonomy, competence and relatedness. The interview data were categorized based on the thematic analysis suggested by Braun and Clarke. The findings revealed that chatbots support competence, autonomy, and relatedness. However, the findings also revealed that chatbots lack an emotional environment and give inaccurate English language learning information. To address these problems, students suggested that chatbots should be used solely for assessment during teaching. They also recommended a blended learning approach or a traditional classroom teaching that will clear their doubts after the use of chatbots. Overall, this study adds to the body of knowledge on chatbots and English language learning by highlighting their potential as useful teaching aids and providing guidance for researchers, educators, and developers on how to further improve chatbot-based language learning. ER - TY - JOUR T1 - Exploring and validating the componential model of students’ scientific critical thinking in science education AU - Hu, Xinyang AU - Bi, Hualin JO - Thinking Skills and Creativity VL - 55 SP - 101695 PY - 2025 DA - 2025/03/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101695 UR - https://www.sciencedirect.com/science/article/pii/S1871187124002335 KW - Componential model KW - Construct validity KW - Scientific critical thinking AB - Critical thinking (CT) is an essential 21st-century skill and a key competence. In recent years, the importance of scientific critical thinking (SCT) in scientific literacy has been increasingly emphasized in science education. However, the SCT componential model has not been thoroughly explored or empirically tested. Based on an exploratory sequential design, an inductive content analysis was conducted from the descriptions of SCT-related literature to construct a componential model of SCT, which was validated through expert focus group interviews. Subsequently, survey data on SCT were collected from 1041 high school students in China. The subcomponents (1) scientific critical thinking skills (SCTS), (2) scientific critical thinking dispositions (SCTD), and (3) scientific critical thinking background knowledge (SCTBK) were quantitatively validated using exploratory and confirmatory factor analyses. The questionnaire related to these three components of SCT had satisfactory reliability and validity, demonstrating the compositional nature of the model. Finally, we developed a compositional model including three components and 11 subcomponents. The SCT componential model provides detailed conceptual indicators for each subcomponent, providing a theoretical basis for measuring SCT. ER - TY - JOUR T1 - A synthetic review of learning theories, elements and virtual environment simulation types to improve learning within higher education AU - Hari Rajan, Manisha AU - Herbert, Cristan AU - Polly, Patsie JO - Thinking Skills and Creativity VL - 56 SP - 101732 PY - 2025 DA - 2025/06/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101732 UR - https://www.sciencedirect.com/science/article/pii/S1871187124002736 KW - Virtual learning environments KW - Immersive environments KW - Learning and teaching KW - Student experience KW - Higher education AB - Virtual learning environments have been an area of interest for the past two decades, and are a pedagogical method considered for improving student learning. Importantly, VLEs are predicted to create a paradigm shift within higher education. The immersive environment in virtual reality has allowed students to explore and revise more complex phenomena in ways that traditional methods of teaching may not address. The COVID-19 pandemic highlighted this issue where disrupted traditional campus-based educational environments moved to online/digital learning and teaching with increased development and implementation of immersive virtual environments to engage learners. Learning and teaching with VLEs has proven to have both positive and negative impacts for both students and instructors in higher education. Current VLE simulations aim to provide improved student learning by increasing the quality, delivery of content and accessibility of materials, interactive learning opportunities between teachers and students, personalised, flexible education. The opportunity for students to build digital professional skills for use in a virtual ‘real-world’ environment is of particular value. The creation and implementation of VLEs has revealed practical concerns/limitations that restrict wide-spread dissemination. There is minimal research on learning outcomes, improvement in student performance and student motivation associated with virtual learning environments. This review will explore the role of virtual immersive environments, such as 360° interactive classes, virtual reality classes and hybrid/augmented reality classes, on influencing the quality of student learning, motivation and engagement and how they can support methods of teaching in higher education. ER - TY - JOUR T1 - Developing a holistic AI literacy assessment matrix – Bridging generic, domain-specific, and ethical competencies AU - Knoth, Nils AU - Decker, Marie AU - Laupichler, Matthias Carl AU - Pinski, Marc AU - Buchholtz, Nils AU - Bata, Katharina AU - Schultz, Ben JO - Computers and Education Open VL - 6 SP - 100177 PY - 2024 DA - 2024/06/01/ SN - 2666-5573 DO - https://doi.org/10.1016/j.caeo.2024.100177 UR - https://www.sciencedirect.com/science/article/pii/S2666557324000181 KW - AI literacy KW - Domain-specific AI literacy KW - AI ethics literacy KW - Instruments KW - Assessment AB - Motivated by a holistic understanding of AI literacy, this work presents an interdisciplinary effort to make AI literacy measurable in a comprehensive way, considering generic and domain-specific AI literacy as well as AI ethics. While many AI literacy assessment tools have been developed in the last 2-3 years, mostly in the form of self-assessment scales and less frequently as knowledge-based assessments, previous approaches only accounted for one specific area of a comprehensive understanding of AI competence, namely cognitive aspects within generic AI literacy. Considering the demand for AI literacy development for different professional domains and reflecting on the concept of competence in a way that goes beyond mere cognitive aspects of conceptual knowledge, there is an urgent need for assessment methods that capture domain-specific AI literacy on each of the three competence dimensions of cognition, behavior, and attitude. In addition, competencies for AI ethics are becoming more apparent, which further calls for a comprehensive assessment of AI literacy for this very matter. This conceptual paper aims to provide a foundation upon which future AI literacy assessment instruments can be built and provides insights into what a framework for item development might look like that addresses both generic and domain-specific aspects of AI literacy as well as AI ethics literacy, and measures more than just knowledge-related aspects based on a holistic approach. ER - TY - JOUR T1 - The concept of hybrid human-AI regulation: Exemplifying how to support young learners’ self-regulated learning AU - Molenaar, Inge JO - Computers and Education: Artificial Intelligence VL - 3 SP - 100070 PY - 2022 DA - 2022/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2022.100070 UR - https://www.sciencedirect.com/science/article/pii/S2666920X2200025X AB - Hybrid systems combining artificial and human intelligence hold great promise for training human skills. In this paper, I position the concept of Hybrid Human-AI Regulation and illustrate this with an example of a first prototype of a Hybrid Human-AI Regulation (HHAIR) system. HHAIR supports self-regulated learning (SRL) in the context of adaptive learning technologies (ALTs) with the aim to develop learners' self-regulated learning skills. This prototype targets young learners (10–14 years) for whom SRL skills are critical in today's society. Many of these learners use ALTs to learn mathematics and languages every day in school. ALTs optimize learning based on learners' performance data, but even the most sophisticated ALTs fail to support SRL. In fact, most ALTs take over (offload) regulation from learners. In contrast, HHAIR positions hybrid regulation as a collaborative task of the learner and the AI which is gradually transferred from AI-regulation to self-regulation. Learners will increasingly regulate their own learning progressing through different degrees of hybrid regulation. In this way HHAIR supports optimized learning and the transfer and development of SRL skills for lifelong learning (future learning). The HHAIR concept is novel in proposing a hybrid intelligence approach training human SRL skills with AI. This paper outlines theoretical foundations from SRL theory, hybrid intelligence and learning analytics. A first prototype in the context of ALTs for young learners is described as an example of hybrid human-AI regulation and future advancement is discussed. In this way, foundational theoretical, empirical, and design work are combined in articulating the concept of Hybrid Human-AI Regulation which features forward adaptive support for SRL and transfer of control between human and AI over regulation. ER - TY - JOUR T1 - What matters in AI-supported learning: A study of human-AI interactions in language learning using cluster analysis and epistemic network analysis AU - Wang, Xinghua AU - Liu, Qian AU - Pang, Hui AU - Tan, Seng Chee AU - Lei, Jun AU - Wallace, Matthew P. AU - Li, Linlin JO - Computers & Education VL - 194 SP - 104703 PY - 2023 DA - 2023/03/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2022.104703 UR - https://www.sciencedirect.com/science/article/pii/S0360131522002743 KW - Elementary education KW - Applications in subject areas KW - Learning communities KW - Human-computer interface AB - This study investigates how students interact with artificial intelligence (AI) for English as a Foreign Language (EFL) learning and what matters in AI-supported EFL learning. It was conducted in naturalistic learning settings, involving sixteen primary school students and lasting approximately three months. The students' usage data of an AI agent and their reflection essays about the interactions with the AI agent were analyzed using cluster analysis and epistemic network analysis based on the frameworks of community of inquiry and students' approaches to learning. The results suggest four clusters of students, each with its distinct way of interacting with AI for language learning. More importantly, the comparisons of the four clusters of students reveal that even in AI-supported learning, not everyone can benefit from the potential promised by AI. The deep approach to AI-supported learning may amplify the benefits of AI's personalized guidance and strengthen the sense of the human-AI learning community. Passively or mechanically following AI's instruction, albeit with high levels of participation, may decrease the sense of the human-AI learning community and eventually lead to low performance. This study contributes to and has implications for the educational implementation of AI, as well as the facilitation and graphical representation of learner-AI interactions in educational settings. ER - TY - JOUR T1 - Digital skilling of working adults: A systematic review AU - Mendoza-Chan, Joji AU - Pee, L.G. JO - Computers & Education VL - 218 SP - 105076 PY - 2024 DA - 2024/09/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105076 UR - https://www.sciencedirect.com/science/article/pii/S0360131524000903 KW - Teaching/learning strategies KW - 21st century abilities KW - Lifelong learning KW - Adult learning AB - Rapid development of artificial intelligence applications and widespread digital transformation are driving the need for employees to learn digital skills. The body of research on digital skills that working professionals need to thrive in an uncertain and ever-evolving workforce is fast accumulating. Although there have been literature reviews on the nature and types of such digital skills, an integrative overview of how digital skills are acquired remains lacking. This systematic literature review seeks to close the gap by focusing on digital skilling. A total of 39 journal articles published between January 2010 and June 2022 were identified using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Based on thematic coding of the articles, eleven digital skilling approaches were identified and conceptually organized into four categories. Findings regarding the contextual factors affecting digital skilling and impacts of digital skilling indicate an emerging framework of digital skilling. Emerging interests and opportunities for future research related to virtual worlds, learning analytics, and blockchain are discussed. ER - TY - JOUR T1 - Becoming epistemically active in online reading: Facilitating elementary school students’ multimodal multiple document reading via sourcing organizers AU - Lee, Yuan-Hsuan AU - Jhang, Jing-Ya AU - Hong, Huang-Yao JO - Computers & Education VL - 216 SP - 105048 PY - 2024 DA - 2024/07/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105048 UR - https://www.sciencedirect.com/science/article/pii/S0360131524000629 KW - Online multimodal and multiple document reading KW - Text integration KW - Source-content link KW - Reading interest KW - Reading ability AB - In the AI era, it has become crucial to evaluate information found on the Internet critically. This research aimed to investigate the impact of a sourcing organizer on sixth graders' online multimodal and multiple document reading (MMDR) abilities, focusing on aspects such as source-content link and text integration in relation to reading on the Internet. Cognitive and affective factors associated with MMDR were examined. The study involved 52 sixth-graders (55.77% males) from two typical elementary school classes in the northern region of Taiwan. Two intact classes were randomly assigned to either the experimental or control group with the quasi-experimental design. The experimental group (n = 26) received a pre-outlined sourcing organizer, guiding them to record the article title, author, publication date, website name, and major assertions from six assigned multimodal texts. In contrast, the control group (n = 26) received a regular organizer, prompting them to summarize the main ideas from the same six assigned multimodal texts. The study's findings indicated that employing sourcing organizers positively impacted students' performance in text integration. However, it was observed that both groups, regardless of whether they used regular organizers or sourcing organizers, experienced benefits in terms of source-content links. Furthermore, reading ability emerged as the sole significant predictor for source-content links, whereas both reading ability and the use of sourcing organizers predicted text integration. The implications of these findings were discussed to provide insights into instructional strategies to develop online MMDR competencies in elementary students. ER - TY - JOUR T1 - The development of critical thinking, team working, and communication skills in a business school–A project-based learning approach AU - Dias-Oliveira, Eva AU - Pasion, Rita AU - Vieira da Cunha, Rui AU - Lima Coelho, Sandra JO - Thinking Skills and Creativity VL - 54 SP - 101680 PY - 2024 DA - 2024/12/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101680 UR - https://www.sciencedirect.com/science/article/pii/S1871187124002189 KW - Education KW - Project-Based Learning KW - Management KW - Critical Thinking KW - Communication KW - Team working AB - This study presents a Project-Based Learning (PBL) approach – the Multidisciplinary Project I course (MPI) - conceived to improve critical thinking skills of first-year business students while also mobilizing teamwork and communication skills. The main goals are to 1) describe the methodological PBL approach of MPI and 2) analyze changes in critical thinking, team working, and communication skills during the semester (pre- and post-test) by comparing management and economics students enrolled in MP1 (n= 946) to a control group (n= 210) including students from other courses. Our findings show that, at the end of the semester, MPI students reported a greater reduction in their critical thinking difficulties and communication apprehension and improvements in teamwork skills. This study provides evidence supporting the inclusion of PBL approaches to promote skills in business students that can be transferable to real-world settings. ER - TY - JOUR T1 - Advancing young students’ computational thinking: An investigation of structured curriculum in early years primary schooling AU - Falloon, Garry JO - Computers & Education VL - 216 SP - 105045 PY - 2024 DA - 2024/07/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105045 UR - https://www.sciencedirect.com/science/article/pii/S0360131524000599 KW - Computational thinking KW - Coding KW - Kindergarten KW - Early years' education KW - Curriculum KW - Guided inquiry KW - Structured AB - In recent years, the development of computational thinking (CT) has become integral to many school curricula worldwide. This has been associated with calls for computational thinking to be considered a ‘21St Century’ competency, valuable to all students as a transferable process for solving problems and building understanding of human behaviour and systems. However, while computational thinking is a focus of most secondary school computer science curricula, proponents such as Jeanette Wing argue its relevance for younger students, indicating more work must be done investigating its development in early years' education. This study used a structured, problem-based curriculum supported by guided inquiry pedagogy, to explore 6 year old students' learning of basic computational thinking concepts and practices while coding programmable floor robots (Blue-bots and an iPad app). Results indicated improvement across the seven lessons in students' sequencing/algorithm authoring, error correction, and pattern recognition. Furthermore, they revealed evidence of higher order thinking such as identifying patterns in code, and how these can be transferred to help solve problems of different designs. While currently play-based approaches are used to introduce computational thinking concepts and practices in early years' education, results from this study suggest that more structured, problem-based methods should be seriously considered. Results challenge commonly understood developmental theories about what young children can and can't do, contextualised within the field of computer science, and hold implications for early years' teachers' professional knowledge and pedagogy if they are to promote their students' learning in this increasingly important area. Given rapid technological advancements such as artificial intelligence (AI) and increasingly earlier exposure of young children to digitally-mediated information, this study provides support for the earlier and more systematic introduction of basic digital literacy knowledge and skills in early years' education. ER - TY - JOUR T1 - Unveiling English school leaders’ intentional well-being cultivation practices during a global pandemic AU - Yeh, Chloe Shu-Hua AU - Ravalier, Jermaine AU - Chang, Kirk JO - International Journal of Educational Management VL - 39 IS - 1 SP - 107 EP - 125 PY - 2024 DA - 2024/12/10/ SN - 0951-354X DO - https://doi.org/10.1108/IJEM-10-2023-0520 UR - https://www.sciencedirect.com/science/article/pii/S0951354X24001157 KW - School leader well-being KW - Well-being cultivation KW - COVID-19 pandemic AB - Purpose There is an urge worldwide that school leaders’ mental health and well-being must be prioritised within the education recovery at the local, national and global policy levels. This research identified the intentional well-being practices that school leaders cultivated as they faced unprecedented challenges during the COVID-19 pandemic. Design/methodology/approach Data was collected through one-to-one in-depth semi-structured interviews with ten senior school leaders from primary and secondary schools in England. During the pandemic, online interviews were organised using Zoom. An inductive followed by deductive approach qualitative data analysis was employed to offer insights into the multidimensional and sensitive nature of school leaders’ well-being. Findings The findings indicated that despite a reported decline in well-being, the participants intentionally engaged in well-being cultivation practices which were both relational: developing multi-faceted support networks, and individual: developing self-care and self-regulation skills. These practices provided different psychological and practical needs necessary for maintaining their well-being and work functioning facing the pandemic. Originality/value This study affirms school leaders’ well-being cultivation is an intentional and effortful process involving relational and individual practices to support their multidimensional well-being during extreme challenges. These practices can be mindfully and strategically cultivated. This study enhances the theoretical understanding of school leader well-being and offers timely insights into well-being initiatives in leadership development programmes for educational leaders and policymakers amid global challenges. ER - TY - JOUR T1 - Learning motivation of college students in multimedia environment with machine learning models AU - Qianyi, Zhao AU - Zhiqiang, Liang JO - Learning and Motivation VL - 88 SP - 102046 PY - 2024 DA - 2024/11/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2024.102046 UR - https://www.sciencedirect.com/science/article/pii/S0023969024000882 KW - Machine Learning Models KW - Multimedia Environments KW - Learning Motivation Analysis KW - Improved Random Forest Models AB - As the main force of higher education, ensuring the learning status and quality of college students is undoubtedly an important task in the education industry. Analyzing their learning motivation can provide a good understanding of their learning status. Especially in the new educational environment supported by multimedia technology, efficient and convenient learning channels can eliminate students' concerns about educational facilities and instead strengthen the analysis of learning motivation in other aspects. As part of our comprehensive study of learning motivation, we draw on established learning theories, such as reinforcement theory, associative learning, and self-determination theory. Applying such learning theories encourages positive reinforcement, establishes constructive relationships with learning, and nurtures competence and autonomy. This article believed that using machine learning models to predict students' grades or behaviours and analyze their learning motivation is a good approach. Moreover, this article also tested the prediction accuracy by setting different improved random forest model runs, and concluded that the more runs, the higher the accuracy. Especially when the runs reached 100, the accuracy reached 99.98 %. ER - TY - JOUR T1 - AI-powered EFL pedagogy: Integrating generative AI into university teaching preparation through UTAUT and activity theory AU - Zaim, Muhammad AU - Arsyad, Safnil AU - Waluyo, Budi AU - Ardi, Havid AU - Al Hafizh, Muhd. AU - Zakiyah, Muflihatuz AU - Syafitri, Widya AU - Nusi, Ahmad AU - Hardiah, Mei JO - Computers and Education: Artificial Intelligence VL - 7 SP - 100335 PY - 2024 DA - 2024/12/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100335 UR - https://www.sciencedirect.com/science/article/pii/S2666920X24001383 KW - Generative AI KW - EFL pedagogy KW - UTAUT KW - Activity theory AB - This study explores the integration of generative AI into English as a Foreign Language (EFL) teaching preparation within Indonesian higher education, addressing the growing need to understand how emerging technologies can enhance pedagogical practices in a rapidly evolving educational landscape. By employing the Unified Theory of Acceptance and Use of Technology (UTAUT) and Activity Theory, the research provides a robust analytical framework to examine the factors influencing lecturers' adoption of generative AI. The study is particularly relevant as generative AI offers significant potential to improve teaching efficiency and content personalization, yet its adoption presents challenges in aligning outputs with educational standards and maintaining meaningful teacher-student interaction. Using a mixed-methods approach, the research combined quantitative data from structured questionnaires with qualitative insights from reflective compositions, where lecturers critically evaluated their experiences with generative AI. Structural Equation Modeling (SEM) revealed that performance expectancy and social influence significantly and positively influenced behavioral intention, while effort expectancy had no significant effect. Facilitating conditions, unexpectedly, negatively impacted behavioral intention, likely due to satisfaction with existing resources reducing the perceived necessity for new tools. A strong positive correlation between behavioral intention and actual use behavior demonstrated the critical role of intention in driving adoption. Thematic analysis provided further depth by emphasizing both the benefits and challenges of generative AI, accentuating the importance of balancing its use with human instruction to ensure quality teaching and interaction. The study stresses the need for the strategic integration of generative AI, offering practical and theoretical insights into its adoption and implications for advancing EFL teaching in higher education. ER - TY - JOUR T1 - Future research recommendations for transforming higher education with generative AI AU - Chiu, Thomas K.F. JO - Computers and Education: Artificial Intelligence VL - 6 SP - 100197 PY - 2024 DA - 2024/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100197 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000760 KW - Generative artificial intelligence KW - ChatGPT KW - Learning outcomes KW - AI literacy KW - Assessment AB - Higher education is crucial for producing ethical citizens and professionals globally. The introduction of generative AI (GenAI), such as ChatGPT, has posed opportunities and challenges to the traditional model of education. However, the current conversations primarily focus on policy development and assessment, with limited research on the future of higher education. GenAI's impact on learning outcomes, pedagogy, and assessment is crucial for reforming and advancing the workforce. This qualitative study aims to investigate student perspectives on GenAI's impact on higher education. The study uses an initial conceptual framework driven by a systematic literature review to investigate the opportunities and challenges of AI in education. This framework serves as an initial data collection and analysis framework. A sample of 51 students from three research-intensive universities was selected for this study. Thematic analysis identified three themes and 10 subthemes. The findings suggest that future higher education should be transformed to train students to be future-ready for employment in a society powered by GenAI. They suggest new learning outcomes—skills in learning and teaching with GenAI, AI literacy—and emphasize the significance of interdisciplinarity and maker learning, with assessment focusing on in-class and hands-on activities. They recommend six future research directions – competence for future workforce and its self-assessment measures, AI literacy or competency measures, new literacies and their relationships, interdisciplinary teaching, Innovative pedagogies and their evaluation, new assessment and its acceptance. ER - TY - JOUR T1 - Generative AI tools and assessment: Guidelines of the world's top-ranking universities AU - Moorhouse, Benjamin Luke AU - Yeo, Marie Alina AU - Wan, Yuwei JO - Computers and Education Open VL - 5 SP - 100151 PY - 2023 DA - 2023/12/15/ SN - 2666-5573 DO - https://doi.org/10.1016/j.caeo.2023.100151 UR - https://www.sciencedirect.com/science/article/pii/S2666557323000290 KW - Generative artificial intelligence KW - Assessment guidelines KW - Higher education KW - ChatGPT KW - Academic integrity AB - The public release of generative artificial intelligence (GAI) tools (e.g., ChatGPT) has had a disruptive effect on the assessment practices of higher education institutions (HEIs) worldwide. Concerns have largely been associated with academic integrity, cheating and plagiarism. HEIs have had to develop guidelines in response to GAI. As many of these guidelines were developed in haste and could affect a large number of instructors and students, there is a need to examine their content, coverage and suitability. This review examines the extent to which the world's 50 top-ranking HEIs have developed or modified their assessment guidelines to address GAI use and, where guidelines exist, the primary content and advice given to guide instructors in their GAI assessment design and practices. The findings show that just under half of the institutions have developed publicly available guidelines. The guidelines cover three main areas: academic integrity, advice on assessment design and communicating with students. Amongst the suggestions for teachers on assessment design, two appear particularly pertinent in helping develop effective assessment tasks and developing learners’ AI literacy: first, running assessment tasks through GAI to check the extent to which the tool can accomplish the task and, second, having students use GAI as part of the assessment process. Overall, the review suggests that HEIs have come to accept the use of GAI and drafted assessment guidelines to advise instructors on its use. In the article, we argue that it may be beneficial to embrace GAI as a part of the assessment process since this is the reality of today's educational and job landscape. This will require instructors to develop a new competence - generative artificial intelligence assessment literacy - which is conceptualised in this article. ER - TY - JOUR T1 - Promoting design thinking and creativity by making: A quasi-experiment in the information technology course AU - Liu, Shiyu AU - Li, Chengfeng JO - Thinking Skills and Creativity VL - 49 SP - 101335 PY - 2023 DA - 2023/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2023.101335 UR - https://www.sciencedirect.com/science/article/pii/S1871187123001049 KW - Design thinking KW - Creativity KW - Making KW - Information technology AB - Design thinking and creativity are instrumental elements of 21st century skills. In K-12 education, much is left to be known about how to develop curricula to more effectively foster students’ design and creative thinking. This study introduced maker education to the information technology course to investigate the effects of design-oriented making on students’ learning of programming, creativity, and design thinking. Seventy-two fifth-grade students from two classes at a rural primary school in China participated in this eight-week study. Both classes learned about programming a digital greeting card with Mind+, when the experimental group was taught with a design-oriented making pedagogy, whereas the control group learned through a conventional teaching approach. Questionnaires were used to assess students’ knowledge learning, creativity and design thinking competence. Findings showed that when embedded in an open-ended problem-solving context, integrating design thinking into making as a pedagogy can be conducive to the development of design thinking and creativity. Important implications are made to inform future endeavors in fostering student thinking in maker education. ER - TY - JOUR T1 - Effects of self-directed learning behaviors on creative performance in design education context AU - Liu, Bowen AU - Wang, Daiqi AU - Wu, Yonghe AU - Gui, Wendong AU - Luo, Heng JO - Thinking Skills and Creativity VL - 49 SP - 101347 PY - 2023 DA - 2023/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2023.101347 UR - https://www.sciencedirect.com/science/article/pii/S1871187123001165 KW - Design education KW - Self-directed learning KW - Creative performance KW - Non-experimental correlational research KW - Middle school students AB - Both creativity and self-directed learning (SDL) are key competences for us to survive better in the 21st century. Students’ creativity could be developed when they engage in design activities in an SDL way. Therefore, it is important to uncover the effect of SDL on creativity for better implementing SDL approach to enhance creativity. Although existing studies have shown a link between SDL and creativity, how SDL affects creativity is not well understood. This study aims to identify the relationship between actual SDL behaviors and creative performance, and further quantify the predictive effect of students’ SDL behaviors on their creative performance in design education context. The non-experimental correlational research was adopted, and a total of 193 middle school students in a self-directed 3D design class participated in the study. The results showed that there were significant differences of SDL behaviors between high-level creative performance students and low-level creative performance students. SDL behaviors significantly correlated with creative performance. Moreover, students’ SDL behaviors had significant predictive effect on their creative performance. This study enriches the current understanding of how SDL affects creativity from a behavioral perspective. The findings provide evidence for teachers to implement appropriate and effective strategies in design education by letting students engage in SDL behaviors to improve their creative performance. ER - TY - JOUR T1 - Beginning and first-year language teachers’ readiness for the generative AI age AU - Moorhouse, Benjamin Luke JO - Computers and Education: Artificial Intelligence VL - 6 SP - 100201 PY - 2024 DA - 2024/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100201 UR - https://www.sciencedirect.com/science/article/pii/S2666920X2400002X KW - Generative AI KW - ChatGPT KW - Beginning teachers KW - Initial teacher education KW - Language teacher education KW - Teacher readiness AB - The public release of ChatGPT in November 2022 ignited an intense debate about the effects generative AI (GAI) tools will have on language teaching. The advanced capability of GAI tools and their rapid uptake by students has brought both challenges and opportunities to language teachers. This qualitative study, using in-depth individual and group interviews with ten beginning teachers and seventeen first-year English language teachers, explored their readiness for using GAI tools in their professional work and their perceptions of GAI in language teaching. The study found that first-year teachers were generally ready for the use of GAI tools and could recognize its potential to support their professional work. This was largely due to their experiences using ChatGPT. However, beginning teachers were not ready to use GAI tools in their professional work and had little knowledge about them. The study provides insights into the participants’ GAI readiness; awareness of GAI tools and their capabilities and functions; utilization of GAI tools for language teaching; views towards students' use of GAI tools; and thoughts on how to prepare language learners to use GAI tools productively and critically. The study has implications for the preparation and professional development of early career teachers in the GAI-age. ER - TY - JOUR T1 - Text mining on green policies for integrating sustainability in higher education AU - Spada, Irene AU - Giordano, Vito AU - Chiarello, Filippo AU - Martini, Antonella AU - Fantoni, Gualtiero JO - The International Journal of Management Education VL - 23 IS - 2 SP - 101126 PY - 2025 DA - 2025/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.101126 UR - https://www.sciencedirect.com/science/article/pii/S1472811724001976 KW - Natural language processing KW - Skill KW - Higher education KW - Sustainable development goals KW - Sustainability AB - Green transition calls for a supply chain rethinking, considering the vulnerability of the environment and the effects of human activities on it. Education can push towards development of new growth models oriented towards sustainability. However, the identification of the key skills and competences for updating higher education offer is not a trivial task. Policies and regulations in employment focused on skills and mindset for sustainability can feed this process. Moreover, the pace and the complexity of the transition require trusted and integrated data sources to properly update educational offer for the emerging needs. A Natural Language Processing approach is thus presented to measure the alignment between policy-documents and to integrate and operationalize their content. Two European policies recently released are compared, namely the EU Taxonomy for Sustainable Activities (EU-TSA) and the Green Concepts of the European Classification of Skills/Competences, Qualifications and Occupations (ESCO). The results show the topics to include in the development of educational activities oriented to sustainability, that are the key enabling competencies, and the key disciplines in which priority action should be taken. The insights can therefore guide higher educational providers in curriculum development both for pedagogical aspects and learning tasks. ER - TY - JOUR T1 - Innovation in physical education: Teachers’ perspectives on readiness for wearable technology integration AU - Almusawi, Hashem A. AU - Durugbo, Christopher M. AU - Bugawa, Afaf M. JO - Computers & Education VL - 167 SP - 104185 PY - 2021 DA - 2021/07/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2021.104185 UR - https://www.sciencedirect.com/science/article/pii/S0360131521000622 KW - Kuwait KW - Physical education KW - Teachers' perspectives KW - Technology integration KW - Wearable technology AB - The purpose of this article is to explore physical education teachers' perspectives on their readiness to use and integrate wearable technology as an innovation in physical education. The article presents a case study grounded on an analytic induction logic with a constructivist epistemology and involves semi-structured interviews with 38 public school physical education teachers. Based on a thematic analysis of interview data, the study identifies eight themes on attitudinal shifts, adequate capabilities, convenient use, injury prevention, effective exercises, non-sedentary behavior, and system access. These themes reflect the technological and organizational conditions that enable physical education teachers’ readiness to use and integrate wearable technology in physical education. The article concludes with discussions on theoretical and practical implications of the research, limitations and future directions. ER - TY - JOUR T1 - Unpacking help-seeking process through multimodal learning analytics: A comparative study of ChatGPT vs Human expert AU - Chen, Angxuan AU - Xiang, Mengtong AU - Zhou, Junyi AU - Jia, Jiyou AU - Shang, Junjie AU - Li, Xinyu AU - Gašević, Dragan AU - Fan, Yizhou JO - Computers & Education VL - 226 SP - 105198 PY - 2025 DA - 2025/03/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105198 UR - https://www.sciencedirect.com/science/article/pii/S0360131524002124 KW - Data science applications in education KW - Human-computer interface KW - 21st century abilities KW - Information literacy KW - Human-AI interaction AB - Help-seeking is an active learning strategy tied to self-regulated learning (SRL), where learners seek assistance when facing challenges. They may seek help from teachers, peers, intelligent tu-tor systems, and more recently, generative artificial intelligence (AI). However, there is limited empirical research on how learners’ help-seeking process differs between generative AI and hu-man experts. To address this, we conducted a lab experiment with 38 university students tasked with essay writing and revising. The students were randomly divided into two groups: one seeking help from ChatGPT (AI Group) and the other from an experienced teacher (HE Group). To examine their help-seeking processes, we used a combination of statistical testing and process mining methods, analyzing multimodal data (e.g., trace data, eye-tracking data, and conversa-tional data). Our results indicated that the AI Group exhibited a nonlinear help-seeking process, such as skipping evaluation, differing significantly from the linear model observed in the HE Group which also aligned with classic help-seeking theory. Detailed analysis revealed that the AI Group asked more operational questions, showing pragmatic help-seeking activities, whereas the HE Group was more proactive in evaluating and processing received feedback. We discussed factors such as social pressure, metacognitive off-loading, and over-reliance on AI in these different help-seeking scenarios. More importantly, this study offers innovative insights and evidence, based on multimodal data, to better understand and scaffold learners learning with generative AI. ER - TY - JOUR T1 - Investigating co-teaching presence and its impact on student engagement: A mixed-method study on the blended synchronous classroom AU - Yan, Yujie AU - Zuo, Mingzhang AU - Luo, Heng JO - Computers & Education VL - 222 SP - 105153 PY - 2024 DA - 2024/12/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105153 UR - https://www.sciencedirect.com/science/article/pii/S0360131524001672 KW - Co-teaching presence KW - Teaching presence KW - Blended synchronous classroom KW - Student engagement AB - Co-teaching, a partnership between professional peers with different expertise to jointly deliver instruction and divide teaching responsibility, is recognized as an effective teaching strategy that has been widely implemented. The increased use of information and communication technologies in educational practices may expand the opportunities for potentially beneficial teacher collaboration across schools. How the online teacher and the on-site teacher co-teach in blended synchronous teaching and learning, as well as its effectiveness on student engagement, remains unclear. This paper presents the results from a sequential research design from the teaching presence perspective to shed light on the characteristics of co-teaching presence and its effect on student engagement in the blended synchronous classroom. In study one, qualitative data collected through ethnographic observation and interviews exhibited how the co-teaching presence was created and its elements: instructional design and organization, facilitating discourse, direct instruction, assessment, supplementary instruction, organization and management, and affective support. Study two was a quantitative study that applied a self-report questionnaire to 268 students to further verify the effects of elements of co-teaching presence on student engagement. Based on hierarchical regression analyses, the results provided evidence that student engagement benefits from collaborative teaching; the on-site teacher's affective support had the greatest influence on sustaining student engagement. Additional findings, implications, limitations, and research directions are discussed. ER - TY - JOUR T1 - A cross-country analysis of self-determination and continuance use intention of AI tools in business education: Does instructor support matter? AU - Ode, Egena AU - Nana, Rabake AU - Boro, Irene O. AU - Ikyanyon, Darius N. JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100402 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100402 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000426 KW - Artificial intelligence KW - Self-determination KW - Instructor support KW - Trust in AI KW - AI anxiety AB - This study builds on the recent interest in AI adoption research in academic settings by highlighting the need for culturally sensitive AI educational tools. The study achieved this by demonstrating how cultural differences shape students' motivation and AI use. This study adopts a cross-country comparative analytical approach to explore postgraduate students’ motivation to continue using AI tools in the context of higher education. The study developed a theoretical model based on Self-Determination Theory (SDT) and Expectation Disconfirmation Theory (EDT) to explore how perceived competence, perceived relatedness and perceived autonomy influence the continuance use intention of AI tools in two culturally unique higher education contexts – United Kingdom and Nigeria. The study also investigates how instructor support, AI anxiety and Trust in AI moderate the relationship between self-determination and AI continuance use intention of students. The data for this study was collected using Qualtrics online survey to generate responses from postgraduate students in the UK and Nigerian HEIs contexts. The questionnaire was designed using validated existing scales. Overall, 245 and 214 valid responses were received from Nigeria and UK postgraduate students respectively. The data was analysed using Structural Equation Modelling. The findings show that perceived relatedness and perceived autonomy are important predictors of AI tools continuance use intention in both countries. The findings reveal the role of cultural differences in AI use and the relative importance of relatedness and autonomy. The results also demonstrate that instructor support plays a fundamental role in AI use. The perceived impact of AI anxiety and trust in AI on competence, relatedness and autonomy vary between the different contexts. The findings emphasise the need for culturally adaptable AI systems capable of prioritizing either collaborative or individual characteristics based on the cultural setting. The findings provide useful insights for institutions and technology firms who are interested in developing globally acceptable AI tools for educational use. ER - TY - JOUR T1 - Exploring the effects of scaffolded reflective learning on student teachers' design performance and reflective thinking AU - Liu, Qingtang AU - Wang, Yanli AU - Chang, Yubei JO - Thinking Skills and Creativity VL - 56 SP - 101709 PY - 2025 DA - 2025/06/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101709 UR - https://www.sciencedirect.com/science/article/pii/S1871187124002475 KW - Reflective learning KW - Scaffolding KW - Design performance KW - Reflective thinking AB - Solving design problems requires designers to engage in a continuous process of reflection, gradually clarifying the problem and seeking the optimal solution. Promoting student to reflect on their design solutions through well-designed reflective learning activities and scaffolding is a key approach to improving design performance. However, few empirical studies have explored the design of iterative reflective learning activities for design tasks and their impact on design performance and reflective thinking. Therefore, this study presented a scaffolded reflective thinking model based on previous research and implemented a three-stage reflective learning activity with different scaffolds at each stage to help student teachers solve an instructional design task. Thirty-three student teachers participated in the study. A mixed methods approach of content analysis, statistical analysis, and epistemic network analysis was used to analyze their instructional design artifacts and reflective journals to investigate student teachers' design performance and development of reflective thinking. The results showed significant improvements in the quality, fluency, originality, and elaboration of student teachers' instructional design artifacts. Their reflections focused mainly on task-related content and problems in the design artifacts. The progression of their reflective thinking from descriptive to dialogic reflection was evident, with more in-depth reflection on problems, content, and potential solutions observed in the later stages. In addition, this study revealed a positive correlation between student teachers’ reflective thinking and design performance and identified the three key roles of scaffolding in enhancing reflection and design performance. These findings highlight the importance of iterative reflective practice and scaffolding in solving design tasks and provide valuable educational implications for improving design performance. ER - TY - JOUR T1 - Professional vision of teaching as a focus-specific or focus-integrated skill – Conceptual considerations and video-based assessment AU - Dückers, Christina AU - Hörter, Philip AU - Junker, Robin AU - Holodynski, Manfred JO - Teaching and Teacher Education VL - 117 SP - 103797 PY - 2022 DA - 2022/09/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2022.103797 UR - https://www.sciencedirect.com/science/article/pii/S0742051X22001718 KW - Professional vision KW - Teacher competence KW - Classroom management KW - Instructional support KW - Video-based assessment AB - In their professional vision (PV) of the classroom situation, teachers have to consider different foci such as classroom management (CM) and instructional support (IS) concurrently. However, in teacher education different foci of PV are taught almost always separately, raising the question whether PV is focus-specific or focus-integrated. Therefore, we developed a video-based assessment with an open response format for concurrently assessing student teachers’ PV of CM and IS (n = 177). We calculated structural equation models to identify the relationship between latent facets of PV. The comparison of the models revealed that a focus-specific conceptualization of PV fits data best. ER - TY - JOUR T1 - Navigating the ethical terrain of AI in education: A systematic review on framing responsible human-centered AI practices AU - Fu, Yao AU - Weng, Zhenjie JO - Computers and Education: Artificial Intelligence VL - 7 SP - 100306 PY - 2024 DA - 2024/12/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100306 UR - https://www.sciencedirect.com/science/article/pii/S2666920X24001097 KW - Responsible human-centered artificial intelligence KW - Educational contexts KW - Systematic mixed studies review AB - With the rapid development of artificial intelligence (AI) in recent years, there has been an increasing number of studies on integrating AI in various educational contexts, ranging from early childhood to higher education. Although systematic reviews have widely reported the effects of AI on teaching and learning, limited reviews have examined and defined responsible AI in education (AIED). To fill this gap, we conducted a convergent systematic mixed studies review to analyze key themes emerging from primary research. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, we searched Scopus and Web of Science and identified 40 empirical studies that satisfied our inclusion criteria. Specifically, we used four criteria for the screening process: (1) the study's full text was available in English; (2) the study was published before April 10th, 2024 in peer-reviewed journals or conference proceedings; (3) the study was primary research that collected original data and applied qualitative, quantitative, or mixed-methods as the study methodology; and (4) the study had a clear focus on ethical and/or responsible AI in one or multiple educational context(s). Our findings identified essential stakeholders and characteristics of responsible AI in K-20 educational contexts and expanded understanding of responsible human-centered AI (HCAI). We unveiled characteristics vital to HCAI, encompassing Fairness and Equity, Privacy and Security, Non-maleficence and Beneficence, Agency and Autonomy, and Transparency and Intelligibility. In addition, we provided suggestions on how to achieve responsible HCAI via collaborative efforts of stakeholders, including roles of users (e.g., students and educators), developers, researchers, and policy and decision-makers. ER - TY - JOUR T1 - Enhancing learning by Open Learner Model (OLM) driven data design AU - Kay, Judy AU - Bartimote, Kathryn AU - Kitto, Kirsty AU - Kummerfeld, Bob AU - Liu, Danny AU - Reimann, Peter JO - Computers and Education: Artificial Intelligence VL - 3 SP - 100069 PY - 2022 DA - 2022/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2022.100069 UR - https://www.sciencedirect.com/science/article/pii/S2666920X22000248 KW - Open Learner Models (OLMs) KW - Learner models KW - Student models KW - Scrutability KW - Ontologies KW - Self-regulated learning KW - Learning analytics AB - There is a huge and growing amount of data that is already captured in the many, diverse digital tools that support learning. Additionally, learning data is often inaccessible to teachers or served in a manner that fails to support or inform their teaching and design practice. We need systematic, learner-centred ways for teachers to design learning data that supports them. Drawing on decades of Artificial Intelligence in Education (AIED) research, we show how to make use of important AIED concepts: (1) learner models; (2) Open Learner Models (OLMs); (3) scrutability and (4) Ontologies. We show how these concepts can be used in the design of OLMs, interfaces that enable a learner to see and interact with an externalised representation of their learning progress. We extend this important work by demonstrating how OLMs can also drive a learner-centred design process of learning data. We draw on the work of Biggs on constructive alignment (Biggs, 1996, 1999, 2011), which has been so influential in education. Like Biggs, we propose a way for teachers to design the learning data in their subjects and we illustrate the approach with case studies. We show how teachers can use this approach today, essentially integrating the design of learning data along with the learning design for their subjects. We outline a research agenda for designing the collection of richer learning data. There are three core contributions of this paper. First, we present the terms OLM, learner model, scrutability and ontologies, as thinking tools for systematic design of learning data. Second, we show how to integrate this into the design and refinement of a subject. Finally, we present a research agenda for making this process both easier and more powerful. ER - TY - JOUR T1 - Creative confidence and thinking skills for lawyers: Making sense of design thinking pedagogy in legal education AU - Hews, Rachel AU - Beligatamulla, Gnanaharsha AU - McNamara, Judith JO - Thinking Skills and Creativity VL - 49 SP - 101352 PY - 2023 DA - 2023/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2023.101352 UR - https://www.sciencedirect.com/science/article/pii/S1871187123001219 KW - Creative confidence KW - Design thinking pedagogy KW - Law KW - Legal education KW - Thinking skills AB - Law schools globally are increasingly recognising the importance of integrating design thinking into their curricula to equip graduates with essential human-centred skills and mindsets for the future of work. Studies in recent years have investigated design thinking pedagogy in higher education, but there is a need for further empirical research to understand educator and learner perspectives in law schools. We conducted in-depth, semi structured interviews with design thinking educators from an Australian law school to investigate their experience and sense-making of design thinking pedagogy as a specific application case. While our research findings are not generalisable, this study allowed us to reach tentative conclusions about how design thinking might be used to approach skills teaching in law. Our participants sensed design thinking pedagogy as developing empathic, creative, and innovative thinking skills as an alternative to the traditional institutionalised way of producing lawyers. They also sensed it as enabling human centred problem solving, developing creative confidence, and enabling alternative mindsets. We propose that law students must cultivate a different way of thinking to prepare for the future of the legal profession. Integrating design thinking pedagogy into law curricula has the potential to prepare graduate lawyers to respond to complex legal problems with fewer constraints, to develop emotional intelligence, to build resilience, to tackle a fear of failure, and to better collaborate in multidisciplinary contexts. For these reasons, we propose all law schools consider including design thinking pedagogy, or relevant components, within their legal education curricula. ER - TY - JOUR T1 - Application of ChatGPT for automated problem reframing across academic domains AU - Einarsson, Hafsteinn AU - Lund, Sigrún Helga AU - Jónsdóttir, Anna Helga JO - Computers and Education: Artificial Intelligence VL - 6 SP - 100194 PY - 2024 DA - 2024/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100194 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000735 KW - Large language models KW - Artificial intelligence KW - Interdisciplinary education KW - Problem reframing KW - Personalized learning AB - This paper explores the potential of large language models, specifically ChatGPT, to reframe problems from probability theory and statistics, making them accessible to students across diverse academic fields including biology, economics, law, and engineering. The aim of this study is to enhance interdisciplinary learning by rendering complex concepts more accessible, relevant, and engaging. We conducted a pilot study using ChatGPT to adapt problems across 17 disciplines, evaluated through expert review. Our results demonstrate the significant potential of ChatGPT in reshaping problems for diverse settings, preserving theoretical meaning in 77.1% of cases, and requiring no or only minor revisions in 74% of cases. An evaluation performed by 23 domain experts revealed that in 73.6% of cases the reframed problem was considered to add educational value compared to a corresponding abstract problem and to represent a real-world scenario in 57.0% of cases. Furthermore, a survey involving 44 Computer Science students revealed a diverse range of preferences between original and reframed problems, underscoring the importance of considering student preferences and learning styles in the design of educational content. The study offers insights into the practicality and efficacy of employing large language models, like ChatGPT, to enhance interdisciplinary education and foster greater student engagement and understanding. ER - TY - JOUR T1 - Optimising team dynamics: The role of AI in enhancing challenge-based learning participation experience and outcomes AU - Georgara, Athina AU - Santolini, Marc AU - Kokshagina, Olga AU - Jacinta Haux, Camila Justine AU - Jacobs, Desmé AU - Biwott, Gloria AU - Correa, Marcela AU - Sierra, Carles AU - Fernandez-Marquez, Jose Luis AU - Rodriguez-Aguilar, Juan A. JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100388 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100388 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000281 KW - Artificial intelligence KW - Challenge-based learning KW - Participation experience KW - Teamwork KW - Relational well-being AB - The approach of engaging students with real-world challenges to enhance collaboration and problem-solving has attracted significant interest from scholars and practitioners across diverse disciplines. Often called Challenge-Based Learning (CBL), this educational approach emphasises developing collaborative and problem-solving skills, with significant learning occurring within team settings. Prior studies highlight the influence of team composition on the efficacy of learning outcomes, pointing out that factors such as gender diversity, personality trait diversity, and a wide range of skills affect team dynamics and performance. Despite these insights, the practical organisation of these teams remains a challenge, often reliant on ad-hoc methods driven primarily by the nature of the setting at hand. Importantly, CBL is typically assessed through the final product, neglecting the impact of CBL on how the participants experience the overall process. That is, CBL is usually considered effective if the outcome is of high quality, ignoring participants' experience and participation quality. This study investigates the potential of an Artificial Intelligence team composition algorithm to improve participation quality and outcomes in collaborative CBL environments. ER - TY - JOUR T1 - Teachers’ engaging messages, students’ motivation to learn and academic performance: The moderating role of emotional intensity in speech AU - Falcon, Samuel AU - Alonso, Jesús B. AU - Leon, Jaime JO - Teaching and Teacher Education VL - 136 SP - 104375 PY - 2023 DA - 2023/12/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2023.104375 UR - https://www.sciencedirect.com/science/article/pii/S0742051X23003633 KW - Teacher professional development KW - Secondary education KW - Pedagogical issues KW - Improving classroom teaching KW - Evaluation methodologies AB - This study examined how emotional intensity of speech affects the relationship between teachers’ engaging messages, and students’ motivation to learn and academic performance. To achieve our goal, we recorded and transcribed teachers’ lessons. Results revealed that messages appealing to external stimuli had lower emotional intensity than those appealing to internal stimuli. Our results also suggest that emotional intensity moderates the relationship between engaging messages and academic performance, with the effect decreasing as emotional intensity increases. This study offers insights into the role of acoustic features in teachers’ influence on students’ motivation and academic performance and suggests avenues for further research. ER - TY - JOUR T1 - Effects of voice assistant creation using different learning approaches on performance of computational thinking AU - Hsu, Ting-Chia AU - Chang, Ching AU - Lin, Yi-Wei JO - Computers & Education VL - 192 SP - 104657 PY - 2023 DA - 2023/01/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2022.104657 UR - https://www.sciencedirect.com/science/article/pii/S0360131522002287 KW - Artificial intelligence KW - Computational thinking KW - Experiential learning KW - Student learning behaviour KW - Voice assistant AB - Designing artificial intelligence (AI) artefact learning has gone beyond command-line-based instruction, to include a low-barrier threshold with block-based programming. Such instructional design must not solely emphasise AI workings. Rather, it must offer students computational thinking (CT) practice to support their AI-related artefact creation while reducing their AI anxiety about future job replacement or sociotechnical blindness. In this study, this research explored an experiential learning approach to improve CT along with AI application capabilities when engaging undergraduate students in creating a voice assistant application (VA app). A total of 56 students participated in the study. The control group (CG) of 26 students used a conventional subject-based learning method, while the experimental group (EG) of 30 students adopted an experiential learning method. This study aimed to examine the differences in the learning achievement of CT and AI concept, as well as the perspectives of AI anxiety, and CT; in the meanwhile, this study analysed the students' learning behaviours using sequential behavioural analysis to discuss the learning process. Results showed that the CT ability of the EG was better than that of the CG, although no significant difference was found between the two groups’ AI concepts and anxiety. The behaviour analysis also revealed that the EG students were willing to ask more questions, and conducted their VA evaluation, whereas the CG students were inclined to focus on the input and output of knowledge, and replicated what the teacher presented. Suggestions and implications are given for future research. ER - TY - JOUR T1 - Harmony in diversity: Digital literacy research in a multidisciplinary landscape AU - Yang, Feng AU - Yao, Ruiyang AU - Ren, Yunyue AU - Guo, Luxuan JO - Computers & Education VL - 230 SP - 105265 PY - 2025 DA - 2025/06/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2025.105265 UR - https://www.sciencedirect.com/science/article/pii/S0360131525000338 KW - Information literacy KW - Interdisciplinary projects KW - Applications in subject areas KW - Bibliometrics AB - The advent of the digital era has significantly heightened interest in digital literacy across multidisciplinary backgrounds and has endowed these fields with interdisciplinary and integrative characteristics. In this study, we employed VOSviewer and Bibliometrix for bibliometric and descriptive analyses of digital literacy, and we analyzed 3005 records from the Social Science Citation Index and Science Citation Index. We constructed keyword co-occurrence time networks across five distinct research areas and supplemented them with keyword co-occurrence frequencies to examine similarities and differences between research themes from diverse disciplinary perspectives. The findings of this study indicate that although various fields recognize the significance of digital literacy, different fields prioritize different aspects. As the main field of research, Education & Educational Research focus primarily on the pedagogical practices of cultivating digital literacy, whereas Communication emphasizes the cultivation of digital literacy to address challenges in information dissemination. Information Science & Library Science typically view libraries as central to digital literacy. Moreover, Computer Science research emphasizes the leveraging of technology, whereas Psychology explores the connection between digital literacy and cognitive processes. Analyzing the differences between different disciplines and drawing new ideas from them is of great significance for Education & Educational Research regarding how to deepen digital literacy education content, construct digital literacy education contexts, integrate digital literacy education resources, narrow the digital divide, and promote educational equity in the future. ER - TY - JOUR T1 - Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy AU - Southworth, Jane AU - Migliaccio, Kati AU - Glover, Joe AU - Glover, Ja’Net AU - Reed, David AU - McCarty, Christopher AU - Brendemuhl, Joel AU - Thomas, Aaron JO - Computers and Education: Artificial Intelligence VL - 4 SP - 100127 PY - 2023 DA - 2023/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100127 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000061 KW - 21st century competencies KW - Curriculum design KW - AI literacy KW - Transformative program development KW - Interdisciplinary education KW - Career readiness AB - Artificial Intelligence (AI) is a ubiquitous concept and tool already found across society and an integral part of everyday life. As such, basic understanding and knowledge of AI should be a critical component of student education to foster successful global citizens. This position paper describes one possible path to address potential gaps in AI education and integrate AI across the curriculum at a traditional research university. The University of Florida (UF) is infusing AI across the curriculum and developing opportunities for student engagement within identified areas of AI literacy regardless of student discipline. The AI Across the Curriculum initiative being developed at UF will make AI education a cornerstone opportunity for all students. The ultimate goal of AI Across the Curriculum is the creation of an AI-ready workforce covering the essential 21st-century competencies identified as workforce and government needs worldwide. Qualified human capital is essential to face the challenges of the 21st-century, and UF is positioning itself to lead in meeting this global societal need. In designing the AI Across the Curriculum model, all students are provided with a suite of AI opportunities and are encouraged to engage. The university is taking advantage of a significant investment in AI campus-wide to innovate curriculum and create activities that nurture interdisciplinary engagement while ensuring student career readiness. As businesses, industry, and governments transform globally within this AI paradigm shift, AI education, innovation, and literacy will become cornerstones of curriculum with UF providing an inclusive example for all undergraduate, graduate, and professional students. While the AI effort at UF is inclusive and broad, the focus of this paper is on undergraduate programs which also represents a Quality Enhancement Plan (or QEP) effort for reaccreditation of UF's undergraduate programs. This program is highly innovative and transformative, creating interdisciplinary AI literacy opportunity for all students. ER - TY - JOUR T1 - School staff members’ professional agency in Finland, Scotland and Sweden – A comparative study AU - Hökkä, Päivi AU - Räikkönen, Eija AU - Vähäsantanen, Katja AU - Sarazin, Marc AU - Lund, Anna AU - Pantić, Natasa JO - Teaching and Teacher Education VL - 159 SP - 104998 PY - 2025 DA - 2025/06/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2025.104998 UR - https://www.sciencedirect.com/science/article/pii/S0742051X25000745 AB - Professional agency has been comprehensively investigated in educational contexts, but there have been few quantitative or comparative studies. This quantitative study explored school staff members’ professional agency in Finland, Scotland, and Sweden, addressing three dimensions of agency: influencing at work, participation at work, and negotiating professional identity. The questionnaire data indicated fairly strong agency among lower secondary school staff members across the dimensions and countries. Professional agency was perceived to be stronger in Sweden than in Finland or Scotland. There were some differences between the countries in terms of the background variables (e.g. working experience) affecting professional agency in schools. ER - TY - JOUR T1 - Uncurtaining windows of motivation, enjoyment, critical thinking, and autonomy in AI-integrated education: Duolingo Vs. ChatGPT AU - Xu, Jia AU - Liu, Qianwen JO - Learning and Motivation VL - 89 SP - 102100 PY - 2025 DA - 2025/02/01/ SN - 0023-9690 DO - https://doi.org/10.1016/j.lmot.2025.102100 UR - https://www.sciencedirect.com/science/article/pii/S0023969025000074 KW - AI-integrated education KW - Autonomy KW - ChatGPT KW - Critical thinking KW - Duolingo KW - Enjoyment KW - Motivation AB - Artificial intelligence (AI) has become increasingly integral to second language learning due to its outstanding advantages, such as personalized learning experiences, real-time feedback, and increased engagement. Despite the growing popularity of AI-powered platforms like Duolingo and ChatGPT, there is limited empirical research comparing their effectiveness in fostering key educational outcomes. This study addressed this gap by investigating the impact of Duolingo and ChatGPT on the motivation, enjoyment, critical thinking (CT), and autonomy of English as a Foreign Language (EFL) learners in China. Employing a true-experimental design, the study involved three groups: two experimental groups (EGs) using Duolingo (n = 81) and ChatGPT (n = 81) and a control group (CG) (n = 82). The outcomes of a one-way MANOVA indicated that both experimental groups significantly outperformed the control group in terms of motivation, enjoyment, CT, and autonomy. Furthermore, the results demonstrated no significant differences between the Duolingo and ChatGPT groups, suggesting both platforms are equally effective in the constructs under investigation in this study. These findings indicated the potential of AI-driven platforms to transform second language education by providing engaging, personalized, and cognitively enriching experiences. ER - TY - JOUR T1 - Evaluating the performance of ChatGPT and GPT-4o in coding classroom discourse data: A study of synchronous online mathematics instruction AU - Xu, Simin AU - Huang, Xiaowei AU - Lo, Chung Kwan AU - Chen, Gaowei AU - Jong, Morris Siu-yung JO - Computers and Education: Artificial Intelligence VL - 7 SP - 100325 PY - 2024 DA - 2024/12/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2024.100325 UR - https://www.sciencedirect.com/science/article/pii/S2666920X24001280 KW - ChatGPT KW - GPT-4o KW - Classroom discourse analysis KW - Professional development KW - Mathematics instruction AB - High-quality instruction is essential to facilitating student learning, prompting many professional development (PD) programmes for teachers to focus on improving classroom dialogue. However, during PD programmes, analysing discourse data is time-consuming, delaying feedback on teachers' performance and potentially impairing the programmes' effectiveness. We therefore explored the use of ChatGPT (a fine-tuned GPT-3.5 series model) and GPT-4o to automate the coding of classroom discourse data. We equipped these AI tools with a codebook designed for mathematics discourse and academically productive talk. Our dataset consisted of over 400 authentic talk turns in Chinese from synchronous online mathematics lessons. The coding outcomes of ChatGPT and GPT-4o were quantitatively compared against a human standard. Qualitative analysis was conducted to understand their coding decisions. The overall agreement between the human standard, ChatGPT output, and GPT-4o output was moderate (Fleiss's Kappa = 0.46) when classifying talk turns into major categories. Pairwise comparisons indicated that GPT-4o (Cohen's Kappa = 0.69) had better performance than ChatGPT (Cohen's Kappa = 0.33). However, at the code level, the performance of both AI tools was unsatisfactory. Based on the identified competences and weaknesses, we propose a two-stage approach to classroom discourse analysis. Specifically, GPT-4o can be employed for the initial category-level analysis, following which teacher educators can conduct a more detailed code-level analysis and refine the coding outcomes. This approach can facilitate timely provision of analytical resources for teachers to reflect on their teaching practices. ER - TY - JOUR T1 - Characteristics, prevalence and tensions of critical thinking in Indonesian high school English language classes resulting from policy-driven teaching AU - Fernandes, Ricky AU - Willison, John AU - Boyle, Christopher JO - Thinking Skills and Creativity VL - 53 SP - 101605 PY - 2024 DA - 2024/09/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101605 UR - https://www.sciencedirect.com/science/article/pii/S1871187124001433 KW - Critical thinking (CT) KW - English as an additional language (EAL) KW - Case study KW - Critical thinking characteristics and prevalence KW - Listening and speaking KW - Critical thinking English listening and speaking (CTELS) AB - Indonesian government policy has emphasised Critical Thinking development in secondary school students to position the nation for better engagement with global concerns, including the Industrial Revolution 4.0. A vehicle of choice to achieve this Critical Thinking development is English as an Additional Language in Secondary Schooling. This article presents a qualitative study that investigated the characteristics and prevalence of Years 10, 11 and 12 Critical Thinking in English listening and speaking tasks in an Indonesian high school. Data were generated through sustained engagement with one class in each year level, providing rich and detailed classroom data. These data were analysed with a conceptual framework of Critical Thinking in English Listening and Speaking to determine the characteristics of student Critical Thinking. Frequency counts of the characteristics yielded the prevalence of Critical Thinking in the period of engagement with each class. The point of intersection between Critical Thinking policy and its implementation demonstrates the congruence and dissonance between the actualised student Critical Thinking and teacher documents. Results showed that the characteristics and prevalence of Critical Thinking were fundamentally different for each year group, in large part due to the differences in teacher facilitation of Critical Thinking, despite, or because of, the overarching policy directives. ER - TY - JOUR T1 - Role transition of higher education teachers due to disruptive technological change: Identity reconstruction for a better teacher-student relationship AU - Mitev, Ariel Zoltán AU - Tóth, Rita AU - Vaszkun, Balázs JO - The International Journal of Management Education VL - 22 IS - 2 SP - 100978 PY - 2024 DA - 2024/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2024.100978 UR - https://www.sciencedirect.com/science/article/pii/S1472811724000491 KW - Role transition KW - Loss of identity KW - Online teaching KW - Student-teacher relationship KW - Crisis KW - Radical change AB - This paper highlights the importance of higher education teachers’ professional identity in the field of management, especially when faced with crisis events or disruptive technology. By employing the Bridges transition framework, we comprehended the profound transformation brought about by the pandemic and suggested proactive measures to effectively address future obstacles that significantly affect teaching methods. Based on a PLS-SEM analysis performed to examine the outcomes of an online survey (N = 145), our study provides insights into the connections between changes in the teachers' identity, digital mastery, successful role transition, and the teacher-student relationship. Our results show that the loss of teaching identity has a direct negative impact on the digital mastery, the success of the transition of the teaching role, and the student-teacher relationship as well. We suggest that a transition process is successful if it is well-managed and supported during its psychological phases, places significant emphasis on the phenomenon of loss of identity and provides guidance towards defining the new identity. ER - TY - JOUR T1 - Developing middle school students’ understanding of machine learning in an African school AU - Sanusi, Ismaila Temitayo AU - Oyelere, Solomon Sunday AU - Vartiainen, Henriikka AU - Suhonen, Jarkko AU - Tukiainen, Markku JO - Computers and Education: Artificial Intelligence VL - 5 SP - 100155 PY - 2023 DA - 2023/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2023.100155 UR - https://www.sciencedirect.com/science/article/pii/S2666920X23000346 KW - Machine learning education KW - Data KW - Ethics KW - Middle school KW - Nigeria AB - Researchers' efforts to build a knowledge base of how middle school students learn about machine learning (ML) is limited, particularly, considering the African context. Hence, we conducted an experimental classroom study (N = 32) within the context of extracurricular activities in a Nigerian middle school to discern how students engaged with ML activities. Furthermore, we explored whether participation in our intervention program elicit changes in students' ML comprehension, and perceptions. Using multiple qualitative data collection techniques including interviews, pre-post open-ended surveys and written assessments, we uncover evidence that indicated evolution of students’ ML understanding, ethical awareness, and societal implication of ML. In addition, our findings showed that a middle school student can learn and understand ML, even when one had no prior knowledge or interest in science related careers. The findings have implication for pedagogical design of AI instruction in middle school context. We discuss the implication of our results for researchers and relevant stakeholders, highlight the limitations and chart future work paths. ER - TY - JOUR T1 - Investigating the impact of situational cognition, emotions, and self-efficacy on creative thinking and collaborative intention in metaverse teaching scene AU - He, Tong-Liang AU - Zhang, Cheng-Cheng AU - Huang, Zhan-Qing AU - Qin, Feng JO - Thinking Skills and Creativity VL - 56 SP - 101723 PY - 2025 DA - 2025/06/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2024.101723 UR - https://www.sciencedirect.com/science/article/pii/S1871187124002645 KW - Metaverse Teaching Scene (MTS) KW - Situated Cognition KW - Emotions KW - Self-efficacy KW - Creative Thinking KW - Collaborative Intention AB - The metaverse has emerged as a significant topic in education, with a growing body of literature examining its feasibility and potential benefits for innovative teaching methods, curriculum development, and educational tools. By integrating technologies such as artificial intelligence (AI), blockchain, virtual reality (VR), and augmented reality (AR), the metaverse presents considerable potential for creating customized teaching environments and promoting situated learning. However, current research on the Metaverse Teaching Scene (MTS) primarily involves qualitative discussions, lacking empirical evidence on how MTS influences students' creative thinking and collaborative intentions. This study, grounded in Situated Learning Theory and the Stimuli-Organism-Response (S-O-R) paradigm, explores the factors that affect students' creative thinking and collaborative intentions within MTS. Data were gathered from 316 Chinese university students through questionnaires and analyzed using structural equation modeling (SEM) and artificial neural networks (ANN). The results indicate that contextual cognition factors (e.g., immersion, learning motivation, interactive experience, perceived incentives) in MTS enhance students' self-efficacy and emotional responses, which in turn foster creative thinking and collaborative intentions. Moreover, the study reveals that self-efficacy positively mediates the association between emotions and creative thinking. These findings highlight the crucial role of MTS in advancing situated learning and suggest that educators incorporate MTS to design customized learning environments and activities that boost student engagement and improve learning outcomes. ER - TY - JOUR T1 - Researcher or teacher-of-teachers: What affects the salient identity of Chinese university-based teacher educators AU - Liang, Jingjing AU - Ell, Fiona AU - Meissel, Kane JO - Teaching and Teacher Education VL - 130 SP - 104184 PY - 2023 DA - 2023/08/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2023.104184 UR - https://www.sciencedirect.com/science/article/pii/S0742051X23001725 KW - University-Based teacher educators KW - Identity salience KW - “Teacher-of-teachers” identity KW - “Researcher” identity KW - Chinese teacher education AB - University-based teacher educators' (UBTEs) identities impact their work, engagement, and professional development. While a deeper understanding of UBTE identity is emerging, how UBTEs value and reconcile different elements of professional identity is under-researched. This study examines 34 Chinese UBTEs' salient aspects of their professional identity. Two salient identities emerged and were distributed differently: a “teacher-of-teachers” identity prevalent in provincial normal universities and a “researcher” identity prevalent in first-class normal universities. Four ways these two identities interact are presented, describing how UBTEs negotiate a tension between “researcher” and “teacher-of-teachers” identities. This tension shapes UBTEs’ work and how teacher education programs function. ER - TY - JOUR T1 - Investigating pedagogical, technological and school factors underpinning effective ‘critical thinking curricula’ in K-6 education AU - Falloon, Garry JO - Thinking Skills and Creativity VL - 51 SP - 101447 PY - 2024 DA - 2024/03/01/ SN - 1871-1871 DO - https://doi.org/10.1016/j.tsc.2023.101447 UR - https://www.sciencedirect.com/science/article/pii/S1871187123002158 KW - Critical thinking KW - K-6 KW - Schools KW - Curriculum KW - Pedagogy KW - Technology AB - Objective This study investigated factors underpinning a successful technology-supported classroom curriculum, specifically designed to promote K-6 students’ critical thinking. Methods Video and audio data illustrating 41 students’ application of critical thinking were collected using a unique display recording app installed on iPads. These were timeline analysed using a literature-generated framework comprising Indicators of critical thinking. Interview data were thematically analysed to build knowledge of teacher pedagogical and school factors supporting the curriculum. Results Data indicated students mostly applied critical thinking for defining and clarifying concepts, presenting reasoned arguments and conclusions, questioning and challenging others’ perspectives, seeking evidence for claims made, and identifying and critiquing assumptions. Results highlight the important contribution of teacher theoretical knowledge, school-wide commitment to a ‘critical thinking’ curriculum, and common understanding of the broader purpose schooling, as foundational to the curriculum's success. Conclusion Teaching for critical thinking was facilitated by close alignment between pedagogical, technological, and school environment factors. It was underpinned by a school-wide learning virtues and values framework emphasising students’ future competencies developed from extensive reading of research and learning theory, and was deliberately planned for. It reflected in theory-informed task design, technology selection, and pedagogy. Practice Critical thinking has been identified in school curricula as an important capability. However, while imperatives and general principles promoting critical thinking in schools are detailed in official documents, few examples exist illustrating how critical thinking can be fostered in K-6 education. Implications Explicit teaching for critical thinking should be considered a priority by teachers at all school levels. Given rapid technological advances such as AI, and implications these hold for students’ critical information literacy, this study provides timely guidance on how explicit teaching for critical thinking might be approached in K-6 education. ER - TY - JOUR T1 - Assessing the pre-conditions for the pedagogical use of digital tools in the Nigerian higher education sector AU - Orji, Ifeyinwa Juliet AU - Ojadi, Frank AU - Okwara, Ukoha Kalu JO - The International Journal of Management Education VL - 20 IS - 2 SP - 100626 PY - 2022 DA - 2022/07/01/ SN - 1472-8117 DO - https://doi.org/10.1016/j.ijme.2022.100626 UR - https://www.sciencedirect.com/science/article/pii/S1472811722000283 KW - Digitalization KW - Higher education KW - TOE theory KW - Social media KW - Learning outcomes KW - Nigeria AB - Currently, there is a burgeoning interest in digitalization as evidenced in extant literature. Nevertheless, the effect, based on teachers’ own perspectives, of the pedagogical use of digital technologies on learning outcomes in the higher education sector has been under-investigated. Thus, this paper aims to investigate the pre-conditions for the effective adoption of social media tools in the Nigerian higher education sector and to assess the impact of the adoption on specific learning outcomes. A multi-criteria decision-making (MCDM) methodology was proposed for study analysis, aided by views of experts with sufficient teaching experience in Nigerian business school programs. The results indicate that adequate budgetary allocations, technical competence, a sufficient level of privacy, and an effective government regulatory framework are the most important of the investigated pre-conditions. Additionally, the pedagogical use of social media in business school programs is more strongly associated with learning outcomes such as professionalism and strategic thinking, emotional intelligence, and social maturity. Hence, the article offers guidance to decision-makers in the higher education sector on how to actualize the successful adoption of social media for pedagogical use and build effective business strategies at various levels of the digitalization process. ER - TY - JOUR T1 - A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023) AU - Almatrafi, Omaima AU - Johri, Aditya AU - Lee, Hyuna JO - Computers and Education Open VL - 6 SP - 100173 PY - 2024 DA - 2024/06/01/ SN - 2666-5573 DO - https://doi.org/10.1016/j.caeo.2024.100173 UR - https://www.sciencedirect.com/science/article/pii/S2666557324000144 KW - Adult learning KW - Information literacy KW - 21st-century abilities KW - Human-computer interface KW - Evaluation methodologies KW - Education AB - The explosion of AI across all facets of society has given rise to the need for AI education across domains and levels. AI literacy has become an important concept in the current technological landscape, emphasizing the need for individuals to acquire the necessary knowledge and skills to engage with AI systems. This systematic review examined 47 articles published between 2019 and 2023, focusing on recent work to capture new insights and initiatives given the burgeoning of the literature on this topic. In the initial stage, we explored the dataset to identify the themes covered by the selected papers and the target population for AI literacy efforts. We identified that the articles broadly contributed to one of the following themes: a) conceptualizing AI literacy, b) prompting AI literacy efforts, and c) developing AI literacy assessment instruments. We also found that a range of populations, from pre-K students to adults in the workforce, were targeted. In the second stage, we conducted a thorough content analysis to synthesize six key constructs of AI literacy: Recognize, Know and Understand, Use and Apply, Evaluate, Create, and Navigate Ethically. We then applied this framework to categorize a range of empirical studies and identify the prevalence of each construct across the studies. We subsequently review assessment instruments developed for AI literacy and discuss them. The findings of this systematic review are relevant for formal education and workforce preparation and advancement, empowering individuals to leverage AI and drive innovation. ER - TY - JOUR T1 - Using Self-Determination Theory to Explain How Mind Mapping and Real-time Commenting Enhance Student Engagement and Learning Outcomes in Video Creation AU - FANG, Xueqing AU - CHIU, Thomas K.F. JO - Computers and Education Open VL - 8 SP - 100254 PY - 2025 DA - 2025/06/01/ SN - 2666-5573 DO - https://doi.org/10.1016/j.caeo.2025.100254 UR - https://www.sciencedirect.com/science/article/pii/S2666557325000138 KW - Multimodal learning KW - Self-determination theory KW - Student engagement KW - Creativity KW - Collaboration AB - Video creation provides students with opportunities to engage in authentic learning experiences while developing knowledge and 21st-century skills across various subjects. The student-created video activity could be an effective pedagogical approach for contemporary higher education teaching in the artificial intelligence (AI) Era. However, its full potential has yet to be realized, and more research is needed to explore learning methodologies that can enhance its effectiveness. Mind mapping (MM) and real-time commenting (RTC) are two strategies that have been shown to enhance student engagement. This study investigated the effects of MM (with vs. without) and RTC (with vs. without) on students’ need satisfaction, engagement, creativity, and collaboration, using Self-Determination Theory (SDT) to explain how the two strategies influence engagement and learning outcomes in video creation activities. We conducted an eight-week intervention study with 138 Chinese university students, using a 2 × 2 between-subjects factorial design, with four experimental groups: video creation (VC), video creation with MM (VC-MM), video creation with RTC (VC-RTC), and video creation with both MM and RTC (VC-MMRTC). Our analysis revealed that: (i) MM significantly satisfied students’ needs for autonomy, competence, and relatedness, while RTC significantly fulfilled their need for relatedness; (ii) MM significantly improved students’ behavioral, cognitive, and agentic engagement, while RTC significantly enhanced their emotional engagement; (iii) MM significantly improved students’ collaboration; and (iv) neither the MM nor RTC significantly improved students’ creativity. The results highlight the effectiveness of integrating MM and RTC strategies in satisfying students’ three psychological needs, enhancing four types of student engagement, and improving collaboration in video-based learning activities. With the help of generative AI tools, instructors and students can easily adopt these strategies for effective learning. ER - TY - JOUR T1 - Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education AU - Garg, Ashish AU - Nisumba Soodhani, K. AU - Rajendran, Ramkumar JO - Computers and Education: Artificial Intelligence VL - 8 SP - 100380 PY - 2025 DA - 2025/06/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2025.100380 UR - https://www.sciencedirect.com/science/article/pii/S2666920X25000207 KW - Applications in subject areas KW - Post-secondary education KW - Teaching/learning strategies AB - The advent of Generative Artificial Intelligence (GenAI) and large language models like LLama, Palm2, GPT, Gemini, and Claude has revolutionized education by generating human-like text and contextually relevant responses. Our research investigates the impact of structured prompt training on students' learning in data analysis and programming. We experimented with 157 first-year engineering students divided into three groups: a control group (internet access, no GenAI), an experimental group 1 (internet and GenAI without prompt training), and an experimental group 2 (internet and GenAI with prompt training). The prompt training session included techniques like few-shot prompting, chain prompting, and the CLEAR framework. We assessed participants' performance in data analysis tasks using Python, with pre-tests and post-tests measuring their skills in programming across three Bloom's taxonomy levels (understanding, application, and analysis). ANOVA on post-test scores showed significant differences among the groups, with G3 (with prompt training) outperforming G2 (without prompt training) and the control group across all three levels, evidenced by higher mean scores (G3: 6.60, G2: 4.94, Control: 4.28), similar pattern observed in task completion also. These results underscore the effectiveness of structured prompt training in enhancing students' data analysis and programming skills. Our study highlights the potential of GenAI and structured prompt training to transform educational practices and suggests future research directions, including integrating prompt engineering within human-AI collaboration. ER - TY - JOUR T1 - Factors influencing engagement in EFL learning of higher education learners in blended learning environments AU - Cai, Qianqian JO - International Journal of Educational Research VL - 131 SP - 102587 PY - 2025 DA - 2025/01/01/ SN - 0883-0355 DO - https://doi.org/10.1016/j.ijer.2025.102587 UR - https://www.sciencedirect.com/science/article/pii/S0883035525000618 KW - Engagement KW - Blended learning KW - Influencing factors KW - Higher education KW - English as a foreign language learning AB - Researchers have long been interested in engagement in blended learning. However, insufficient research has been conducted on factors influencing engagement in blended English as a foreign language learning. This study investigates the factors influencing engagement in blended English as a foreign language learning based on the hedonic-motivation system adoption model. This study aimed to develop a model exploring engagement in blended English as a foreign language learning employing quantitative structural equation modelling methods, supplemented by an open-ended review question. Based on feedback from 938 tertiary students, this study explored the relationship among perceived ease of use, usefulness, teacher support, enjoyment, social presence, L2 grit, and engagement in blended English as a foreign language learning using a structural equational modeling method. Through the thematic analysis of 418 responses to the open-ended question, the author gained insights into the merits, flaws, and recommendations of blended English as a foreign language learning. As a result, perceived ease of use positively affected the usefulness of blended English as a foreign language learning. Perceived ease of use, teacher support, and usefulness positively impacted the social presence of blended English as a foreign language learning. Perceived teacher support, ease of use, and social presence positively influenced the perceived enjoyment of blended English as a foreign language learning. Perceived enjoyment positively predicted second language (L2) grit of blended learning contexts. However, social presence insignificantly affected L2 grit in blended learning contexts. L2 grit, perceived enjoyment, usefulness, and social presence positively impacted engagement in blended English as a foreign language learning. Despite limitations, this study implies teachers, education researchers, and developers in further research and practice for blended language education. ER - TY - JOUR T1 - Teacher learning community for AR-integrated STEM education AU - Lin, Xiao-Fan AU - Chiu, Thomas K.F. AU - Luo, Shucheng AU - Wong, Seng Yue AU - Hwang, Huijuan AU - Hwang, Sirui AU - Li, Wenyi AU - Liang, Zhong-Mei AU - Peng, Shiqing AU - Lin, Wenkai JO - Teaching and Teacher Education VL - 141 SP - 104490 PY - 2024 DA - 2024/04/01/ SN - 0742-051X DO - https://doi.org/10.1016/j.tate.2024.104490 UR - https://www.sciencedirect.com/science/article/pii/S0742051X24000222 KW - STEM teaching KW - Teacher learning community KW - Augmented reality KW - Perceived support AB - This study used a social network analysis and a content analysis to identify 52 teachers’ perceptions to investigate the mechanisms of teachers’ roles and teachers’ perceived support from a learning community to overcome barriers to AR-integrated STEM teaching. The findings revealed that when teachers occupy more powerful and central roles in the AR-integrated STEM teaching community, they may perceive higher-order support for overcoming the corresponding barriers to AR-integrated STEM teaching. Furthermore, this study developed a framework for promoting teachers’ professional development in AR-integrated STEM teaching by clarifying the hidden role and actual support, which was rarely emphasized in past studies. ER - TY - JOUR T1 - The synergistic effects in an AI-supported online scientific argumentation learning environment AU - Lin, Yu-Ren AU - Hung, Cheng-Yu JO - Computers & Education VL - 229 SP - 105251 PY - 2025 DA - 2025/05/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2025.105251 UR - https://www.sciencedirect.com/science/article/pii/S0360131525000193 KW - Artificial intelligence KW - Gamified learning KW - Scientific argumentation KW - Synergistic effect AB - This study combines scientific argumentation, gamified learning, and textual scaffolding to address the needs of cognitive, affective, and skill-based dimensions, designing an AI-interactive learning environment. Through the synergy created by these three dimensions, it aims to promote scientific argumentation learning. An online learning platform called AI web-based online learning in argumentation (AWOLA) was developed to support the study, featuring three distinct versions: gamified learning with textual scaffolding, gamified learning only, and textual scaffolding only. Four scientific argumentation topics, arranged from descriptive to theoretical, were incorporated into the platform. A total of 285 ninth-grade students participated in this quasi-experimental study, evenly distributed across three experimental groups and a control group based on prior knowledge. The experimental groups used three different versions of AWOLA, while the control group received primarily teacher-centered lecture instruction. Results revealed that differences among the three experimental groups were more pronounced for theoretical scientific argumentation topics compared to descriptive ones. Students in the group experiencing the most comprehensive synergy outperformed others in scientific knowledge understanding (including learning progress and retention), learning motivation, and the construction of multiple arguments. These students demonstrated precise use of scientific terminology and interacted with AI as a bridge connecting abstract concepts to everyday experiences. Even with AI-assisted learning, there is still considerable room for improvement in students' argumentation skills. ER - TY - JOUR T1 - AI-based multidisciplinary framework to assess the impact of gamified video-based learning through schema and emotion analysis AU - Vidanaralage, Anjana Junius AU - Dharmaratne, Anuja Thimali AU - Haque, Shamsul JO - Computers and Education: Artificial Intelligence VL - 3 SP - 100109 PY - 2022 DA - 2022/01/01/ SN - 2666-920X DO - https://doi.org/10.1016/j.caeai.2022.100109 UR - https://www.sciencedirect.com/science/article/pii/S2666920X22000649 KW - Artificial intelligence KW - Education technology KW - Emotion recognition KW - Gamification KW - Schema theory KW - Video-based learning AB - Background As a natural and continual process, the initial learning stages encompass mastering and recalling basic facts. The process proves effective with the integration of new information with pre-existing knowledge characterised as schema to facilitate memory encoding. Additionally, emotions also have the ability to modulate human cognition in terms of learning and memory. The recent advent of gamification in e-learning, which has garnered much scholarly and industrial interest, necessitates a thorough examination between video-based learning and its subsequent implications on schema, emotions, and gamification. Objectives The current multidisciplinary research triangulated cognitive psychology, affective science, and education technology with artificial intelligence for evaluating digital learning pedagogy based on memory retrieval accuracy, response time, and emotional valence. Design This three-way (2 x 2 x 2) mixed factorial experiment design with repeated measures entailed 64 healthy young adult volunteers (n = 64) with 32 in the schema congruent group and 32 in the schema incongruent group. Additionally, 27 (42%) of the volunteers were males, while 37 (58%) were females with an age range between 20 and 39 years old (mean age 27.78 years, SD = 4.77 years). Results The findings demonstrate that the schema congruent group attained a statistically significant and higher retrieval accuracy (p < .001). The delayed recall response time was faster than its immediate recall counterpart (p < .001). Overall, the gamified learning mode depicted more positive emotions compared to non-gamified learning, although both groups primarily portrayed more negative emotions (p = .05). Implications The synthesis of current research aimed to recommend an AI-based multidisciplinary framework to assess the impact on adult learners in terms of schema and evaluate their emotions in experiencing gamified or non-gamified video materials as a learning medium. The implications expedited from this research offer valuable insights for diverse stakeholders engaged in the video-based learning ecosystem. ER - TY - JOUR T1 - Effectiveness of gamified intelligent tutoring in physical education through the lens of self-determination theory AU - Hsia, Lu-Ho AU - Lin, Yen-Nan AU - Lin, Chung-Hisenh AU - Hwang, Gwo-Jen JO - Computers & Education VL - 227 SP - 105212 PY - 2025 DA - 2025/04/01/ SN - 0360-1315 DO - https://doi.org/10.1016/j.compedu.2024.105212 UR - https://www.sciencedirect.com/science/article/pii/S0360131524002264 KW - Teaching/learning strategies KW - Improving classroom teaching KW - Pedagogical issues KW - Interactive learning environments AB - Scholars have recommended the application of an intelligent tutoring and instant feedback system (ITIFS) to enhance students' motor skills performance by automatically evaluating their learning performance and providing personalized guidance and feedback. However, solely providing personalized evaluation and feedback may not necessarily attract students' active and sustained engagement in practice. In particular, it is difficult to arouse students' enthusiasm to participate in sports that require repetitive practice to improve their physical abilities and which involve less interaction with the environment and their opponents. To address this issue, grounded in self-determination theory (SDT), the present study integrated a gamification mechanism that aligned with students' psychological needs into an ITIFS. The gamification features included avatars, achievements (personal ratings and rankings), badges, levels, and social networks (group ratings and rankings). It aimed to attract students to engage continuously in practice, and to address the issue of students lacking motivation to engage in repeated practice. To investigate the effectiveness of the proposed method, a quasi-experimental research design was adopted, and the collected data were analyzed with analysis of covariance (ANCOVA), independent samples t tests and qualitative coding. Four classes of university students participated in the experiment. Two classes (N = 80) were the experimental group adopting the SDT-based gamified ITIFS (G-ITIFS), and the other two classes (N = 76) were the control group adopting the conventional ITIFS (C-ITIFS). The findings indicated that the experimental group showed significantly better yoga skills performance and learning engagement compared to the control group. Feedback from students also revealed that the gamification mechanism provided more excitement and had positive impacts, satisfying students’ psychological needs and reinforcing the learning benefits. The findings of the present study revealed that, from the perspective of SDT, incorporating gamification elements into the development of ITIFS could be a promising approach for physical education. Therefore, it is strongly encouraged that educators promote such a gamified intelligent tutoring mode in physical education curriculums as it is crucial to the development of students' physical and mental health, as well as to their enthusiasm to participate in sports. ER -