Mapping Kolb Learning Styles to Adaptive Curriculum Strategies in Geography Teacher Education: Evidence from Indonesia

Faisal Arif Setiawan; Akhmad Munaya Rahman; Sri Agustina; Noor Liana Waty

doi:10.35445/alishlah.v18i1.8424

Mapping Kolb Learning Styles to Adaptive Curriculum Strategies in Geography Teacher Education: Evidence from Indonesia

Faisal Arif Setiawan, Akhmad Munaya Rahman, Sri Agustina, Noor Liana Waty

Abstract

Understanding students’ learning styles is essential for designing responsive higher education curricula. This study aims to map university students’ learning styles and propose an adaptive curriculum framework for geography education in Indonesia.A descriptive quantitative design was employed. Data were collected from a stratified sample of 100 undergraduate students (cohorts 2019–2022; 45% male, 55% female) at Universitas Lambung Mangkurat using Kolb’s Learning Style Inventory (LSI). Outliers (Z > |3|) were removed prior to analysis. Descriptive statistics were used to identify the distribution of learning styles and mean scores across learning dimensions.The distribution of learning styles was dominated by Converging (52%), followed by Accommodating (24%), Assimilating (17%), and Diverging (7%). Mean dimension scores were AE = 23.09, AC = 21.81, CE = 19.15, and RO = 18.81, indicating a preference for active experimentation and abstract conceptualization. These findings suggest a tendency toward problem-solving and practical application among students.Based on the identified profiles and relevant literature, a conceptual adaptive curriculum model is proposed, integrating experiential learning, technology-enhanced instruction, and local geographical contexts. Such alignment may improve engagement and learning outcomes by accommodating diverse preferences.Mapping learning styles provides a basis for curriculum adaptation in geography education. However, the findings are limited by the single-institution sample, reliance on self-reported data, and ongoing theoretical debates surrounding learning-style models. Further experimental research is needed to validate the proposed framework.

Keywords

Kolb Learning Style Inventory (LSI); experiential learning; adaptive curriculum; higher education; geography teacher education

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References

Adera, N. (2025). Innovative learning spaces and blended learning: Quest for 21st century competency teaching and learning approaches. Creating Dynamic Space in Higher Education: Modern Shifts in Policy, Competencies, and Governance, 139–174.

Azeez, F., & Aboobaker, N. (2024). Exploring new frontiers of experiential learning landscape: A hybrid review. The Learning Organization, 31(6), 985–1007.

Bahadur, R., & Zhang, L. (2021). Socratic teaching and learning styles: Exposing the pervasiveness of implicit bias and white privilege in legal pedagogy. Hastings Race & Poverty LJ, 18, 114.

Baskara, F. X. R. (2023). Chatbots and flipped learning: Enhancing student engagement and learning outcomes through personalised support and collaboration. IJORER: International Journal of Recent Educational Research, 4(2), 223–238.

Carroll, M., Lindsey, S., Chaparro, M., & Winslow, B. (2021). An applied model of learner engagement and strategies for increasing learner engagement in the modern educational environment. Interactive Learning Environments, 29(5), 757–771.

CAST, C. (2018). Universal design for learning guidelines version 2.2. Http://Udlguidelines. Cast. Org.

Dutta, S., Ranjan, S., Mishra, S., Sharma, V., Hewage, P., & Iwendi, C. (2024). Enhancing educational adaptability: A review and analysis of AI-driven adaptive learning platforms. 2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM), 1–5.

El-Sabagh, H. A. (2021). Adaptive e-learning environment based on learning styles and its impact on development students’ engagement. International Journal of Educational Technology in Higher Education, 18(1), 53.

Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13(12), 1216.

Hunaepi, H., & Suharta, I. (2024). Transforming education in Indonesia: The impact and challenges of the Merdeka belajar curriculum. Path of Science, 10(6), 5026–5039.

Jakubik, M. (2023). Cultivating the Future in Higher Education: Fostering Students’ Life-World Becoming with Wisdom Pedagogy. Trends in Higher Education, 2(1), 45–61.

Kamau, H. W. (2020). Influence of Brainstorming Technique on Standard Seven Learners’ Achievement in English Composition Writing in Public Primary Schools in Kisumu County, Kenya. University of Nairobi.

Kirschner, P. A. (2017). Stop propagating the learning styles myth. Computers & Education, 106, 166–171.

Kolb, A., & Kolb, D. (2017). Experiential Learning Theory as a Guide for Experiential Educators in Higher Education. Experiential Learning & Teaching in Higher Education, 1(1), 7–44.

Lestari, N., & Suyanto, S. (2024). A systematic literature review about local wisdom and sustainability: Contribution and recommendation to science education. Eurasia Journal of Mathematics, Science and Technology Education, 20(2), em2394.

Morris, T. H. (2020). Experiential learning–a systematic review and revision of Kolb’s model. Interactive Learning Environments, 28(8), 1064–1077.

Pamuk, M. (2023). Teaching Geographical Thinking With GIS-Based Projects: Learning From Experienced Teachers’ Perspectives. The Florida State University.

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. Psychological Science in the Public Interest, 9(3), 105–119. https://doi.org/10.1111/j.1539-6053.2009.01038.x

Prasetyo, B., & Adi, W. (2024). Experiential Learning in Geography: Enhancing Student Engagement through Field-Based Education. Springer.

Raleiras, M., Nabizadeh, A. H., & Costa, F. A. (2022). Automatic learning styles prediction: A survey of the State-of-the-Art (2006–2021). Journal of Computers in Education, 9(4), 587–679.

Sanjabi, T., & Montazer, G. A. (2020). Personalization of E-learning environment using the Kolb’s learning style model. 2020 6th International Conference on Web Research (ICWR), 89–92.

Schober, P., Mascha, E. J., & Vetter, T. R. (2021). Statistics From A (Agreement) to Z (z Score): A Guide to Interpreting Common Measures of Association, Agreement, Diagnostic Accuracy, Effect Size, Heterogeneity, and Reliability in Medical Research. Anesthesia & Analgesia, 133(6), 1633–1641. https://doi.org/10.1213/ANE.0000000000005773

Shoaib, M., Sayed, N., Singh, J., Shafi, J., Khan, S., & Ali, F. (2024). AI student success predictor: Enhancing personalized learning in campus management systems. Computers in Human Behavior, 158, 108301. https://doi.org/10.1016/j.chb.2024.108301

Su, F., & Zou, D. (2022). Technology-enhanced collaborative language learning: Theoretical foundations, technologies, and implications. Computer Assisted Language Learning, 35(8), 1754–1788.

Tantri, N. N., & Santosa, M. H. (2024). The Integration and Development of EFL Classroom Materials Based on Local Culture: A Systematic Literature Review. Jurnal Pendidikan Bahasa Inggris Undiksha, 12(1), 61–70.

Tong, D. H., Uyen, B. P., & Ngan, L. K. (2022). The effectiveness of blended learning on students’ academic achievement, self-study skills and learning attitudes: A quasi-experiment study in teaching the conventions for coordinates in the plane. Heliyon, 8(12).

Widana, I. W., Sumandya, I. W., Citrawan, I. W., Widana, I. N. S., Ibarra, F. P., Quicho, R. F., Santos, M. R. H. M. D., Velasquez-Fajanela, J. V, & Mukminin, A. (2023). The effect of teacher’s responsibility and understanding of the local wisdom concept on teacher’s autonomy in developing evaluation of learning based on local wisdom in special needs school. Journal of Higher Education Theory and Practice, 23(10).

Yetti, E. (2024). Pedagogical innovation and curricular adaptation in enhancing digital literacy: A local wisdom approach for sustainable development in Indonesia context. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100233.

Zhang, L., Carter Jr, R. A., Basham, J. D., & Yang, S. (2022). Integrating instructional designs of personalized learning through the lens of universal design for learning. Journal of Computer Assisted Learning, 38(6), 1639–1656.

DOI: https://doi.org/10.35445/alishlah.v18i1.8424