The Correlation between Student Perception and Learning Motivation: Blended Learning Strategy

Abednego Abednego; Sefnath Nuniary; Emma Rumahlewang; John Rafafy Batlolona

doi:10.35445/alishlah.v15i2.3850

The Correlation between Student Perception and Learning Motivation: Blended Learning Strategy

Abednego Abednego, Sefnath Nuniary, Emma Rumahlewang, John Rafafy Batlolona

Abstract

Different perceptions will affect the success of learning outcomes, namely student perceptions. Thus, it affects student learning motivation. The study aimed to determine the relationship between student perceptions and learning motivation toward blended learning strategy (BLS). The research used is a correlational test between student perceptions and learning outcomes with BLS. The participants in this study were 70 people from two different classes. The BLS research instruments and student learning motivation include 1) Desire to succeed, 2) Encouragement and needs in learning, 3) Expectations and future goals, and 4) Appreciation of learning. 5) Interesting desires in learning, 6) A Conducive learning environment. The results showed no relationship between student perceptions and learning motivation toward BL learning strategies. Thus, other factors influence student perceptions and learning motivation, such as socioeconomic, family environment, and cultural environment. The implications of this research can provide insights for education policy makers in Indonesia and in the regions about how to design policies mixed learning that is aligned with the preferences of teachers and students in improving the quality of learning and student learning outcomes.

Keywords

Student Perceptions; Learning Motivation; Blended Learning Strategy

Full Text:

PDF

References

Adu, S. G., & Ohemeng, P. (2015). Students’ perception of blended learning environment: a case study of the University of Education, Winneba, Kumasi-Campus, Ghana. International Journal of Education and Development Using Information and Communication Technology, 11(1), 80–100.

Appova, A., & Arbaugh, F. (2018). Teachers’ motivation to learn: implications for supporting professional growth. Professional Development in Education, 44(1), 5–21. https://doi.org/10.1080/19415257.2017.1280524

Barfi, K. A., Arkorful, V., Appiah, F., Agyapong, E. M., & Acheampong, E. (2023). The impact of blended learning on students using the IBOX platform: Initial perspectives of teachers. Heliyon, 9(3), 1–9. https://doi.org/10.1016/j.heliyon.2023.e14297

Batlolona, J. R., & Jamaludin, J. (2022). Physics problem solving skills with IBL-STEMWeb: Students on Small Islands in Maluku. Jurnal Penelitian Pendidikan IPA, 8(2), 592–598. https://doi.org/10.29303/jppipa.v8i2.1344

Bektas-Cetinkaya, Y., & Oruc, N. (2011). Effects of socioeconomic status and physical learning environment on motivation of university students. European Journal of Social Sciences, 21(1), 71–79.

Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability (Switzerland), 12(24), 1–22. https://doi.org/10.3390/su122410367

Farrelly. (2023). Online vs. Blended vs. Face-to-Face Venn Diagram.

Fenech, R. (2021). Blended learning: honouring students’ psychological contract. Cogent Education, 8(1), 1–13. https://doi.org/10.1080/2331186X.2021.1914286

Grønlien, H. K., Christoffersen, T. E., Ringstad, Ø., Andreassen, M., & Lugo, R. G. (2021). A blended learning teaching strategy strengthens the nursing students’ performance and self-reported learning outcome achievement in an anatomy, physiology and biochemistry course – A quasi-experimental study. Nurse Education in Practice, 52, 1–6. https://doi.org/10.1016/j.nepr.2021.103046

Halasa, S., Abusalim, N., Rayyan, M., Constantino, R. E., Nassar, O., Amre, H., Sharab, M., & Qadri, I. (2020). Comparing student achievement in traditional learning with a combination of blended and flipped learning. Nursing Open, 7(4), 1129–1138. https://doi.org/10.1002/nop2.492

Halimah, L., Arifin, R. R. M., Yuliariatiningsih, M. S., Abdillah, F., & Sutini, A. (2020). Storytelling through “Wayang Golek” puppet show: Practical ways in incorporating character education in early childhood. Cogent Education, 7(1), 1–12. https://doi.org/10.1080/2331186X.2020.1794495

Hazelkorn, E., & Locke, W. (2021). Blended learning is dead, long live blended learning! Policy Reviews in Higher Education, 5(1), 1–4. https://doi.org/10.1080/23322969.2021.1873348

Henri, M., Johnson, M. D., & Nepal, B. (2017). A review of competency-based learning: tools, assessments, and recommendations. Journal of Engineering Education, 106(4), 607–638. https://doi.org/10.1002/jee.20180

Herman, C., Gracia, R., Macniven, L., Clark, B., & Doyle, G. (2019). Using a blended learning approach to support women returning to STEM. Open Learning, 34(1), 40–60. https://doi.org/10.1080/02680513.2018.1554475

Hill, T., Chidambaram, L., & Summers, J. D. (2017). Playing ‘catch up’ with blended learning: performance impacts of augmenting classroom instruction with online learning. Behaviour and Information Technology, 36(1), 54–62. https://doi.org/10.1080/0144929X.2016.1189964

Ibrahim, M. M., & Nat, M. (2019). Blended learning motivation model for instructors in higher education institutions.

Kalean, A., & Batlolona, J. R. (2023). Gardner intelligence in physics students in Maluku, Indonesia. Jurnal Penelitian Pendidikan IPA, 9(1), 305–314. https://doi.org/10.29303/jppipa.v9i1.2383

Kintu, M. J., Zhu, C., & Kagambe, E. (2017). Blended learning effectiveness: the relationship between student characteristics, design features and outcomes. International Journal of Educational Technology in Higher Education, 14(1), 1–20. https://doi.org/10.1186/s41239-017-0043-4

Leasa, M., Batlolona, J. R., Enriquez, J. J., & Kurnaz, M. A. (2018). Determination of elementary students’ learning styles reviewed from gender aspects. Journal of Education and Learning (EduLearn), 12(3), 478–486. https://doi.org/10.11591/edulearn.v12i3.8978

Leasa, M., Batlolona, J. R., & Talakua, M. (2019). Analysis of internal representations about the concept of science in elementary school. AIP Conference Proceedings, 2202, 1–9. https://doi.org/10.1063/1.5141678

Licorish, S. A., Owen, H. E., Daniel, B., & George, J. L. (2018). Student perception Kahoot. Research and Practice in Technology Enhanced Learning, 13(9), 1–24.

Lizzio, A., Wilson, K., & Simons, R. (2002). University students’ perceptions of the learning environment and academic outcomes: Implications for theory and practice. Studies in Higher Education, 27(1), 27–52. https://doi.org/10.1080/03075070120099359

Makhdoom, N., Khoshhal, K. I., Algaidi, S., Heissam, K., & Zolaly, M. A. (2013). “Blended learning” as an effective teaching and learning strategy in clinical medicine: A comparative cross-sectional university-based study. Journal of Taibah University Medical Sciences, 8(1), 12–17. https://doi.org/10.1016/j.jtumed.2013.01.002

Muskitta, M., Batlolona, J. R., Kesaulya, N., & Manuputty, D. (2023). Analysis of high school students ’ difficulties in writing scientific papers. Jurnal Penelitian Pendidikan IPA, 9(1), 66–73. https://doi.org/10.29303/jppipa.v9i1.2407

Naaj, M. A., Nachouki, M., & Ankit, A. (2012). Evaluating student satisfaction with blended learning in a gender-segregated environment. Journal of Information Technology Education:Research, 11(1), 185–200. https://doi.org/10.28945/1692

Nancu, D., Sima, V., & Gheorghe, I. G. (2020). Influences of the industry 4 . 0 revolution on the human capital development and consumer behavior : a systematic review. Sustainability (Switzerland), 12(10), 1–28.

Nasr El-Din, W. A., Atwa, H., Potu, B. K., Deifalla, A., & Fadel, R. A. (2022). Checklist-based active learning in anatomy demonstration sessions during the COVID-19 pandemic: Perception of medical students. Morphologie, 1–9. https://doi.org/10.1016/j.morpho.2022.10.001

Osaili, T. M., Ismail, L. C., ElMehdi, H. M., Al-Nabulsi, A. A., Taybeh, A. O., Saleh, S. T., Kassem, H., Alkhalidy, H., Ali, H. I., Al Dhaheri, A. S., & Stojanovska, L. (2023). Comparison of students’ perceptions of online and hybrid learning modalities during the covid-19 pandemic: The case of the University of Sharjah. PloS One, 18(3), e0283513. https://doi.org/10.1371/journal.pone.0283513

Richardson. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 77(2), 68–88. https://doi.org/10.1016/j.pec.2009.03.021

Romualdi, K. B., & Sudrajat, A. (2023). Development of genially interactive multimedia on materials for the national movement organization for middle school students. Al-Ishlah: Jurnal Pendidikan, 15(2), 1166–1180. https://doi.org/10.35445/alishlah.v15i2.3139

Roztocki, N., Soja, P., & Weistroffer, H. R. (2019). The role of information and communication technologies in socioeconomic development: towards a multi-dimensional framework*. Information Technology for Development, 25(2), 171–183. https://doi.org/10.1080/02681102.2019.1596654

Salleh, S. M. (2021). Students ’ Perception on interactive learning in enhancing blended learning experiences. Global Business and Management Research: An International Journal, 13(4), 268–277.

Singh, J., Steele, K., & Singh, L. (2021). Combining the Best of Online and Face-to-Face Learning: Hybrid and Blended Learning Approach for COVID-19, Post Vaccine, & Post-Pandemic World. In Journal of Educational Technology Systems (Vol. 50, Issue 2). https://doi.org/10.1177/00472395211047865

Vandewaetere, M., Vandercruysse, S., & Clarebout, G. (2012). Learners’ perceptions and illusions of adaptivity in computer-based learning environments. Educational Technology Research and Development, 60(2), 307–324. https://doi.org/10.1007/s11423-011-9225-2

Walsh, B. M., & Magley, V. J. (2020). Workplace civility training: understanding drivers of motivation to learn. International Journal of Human Resource Management, 31(17), 2165–2187. https://doi.org/10.1080/09585192.2018.1441164

Wang, W., Guo, L., He, L., & Wu, Y. J. (2019). Effects of social-interactive engagement on the dropout ratio in online learning: insights from MOOC. Behaviour and Information Technology, 38(6), 621–636. https://doi.org/10.1080/0144929X.2018.1549595

Wong, K. T., Hwang, G. J., Goh, P. S. C., & Mohd Arrif, S. K. (2020). Effects of blended learning pedagogical practices on students’ motivation and autonomy for the teaching of short stories in upper secondary English. Interactive Learning Environments, 28(4), 512–525. https://doi.org/10.1080/10494820.2018.1542318

Xiao, B., & Song, G. (2022). The Impact of family socioeconomic status on learning conformity among chinese university students: self-efficacy as mediating factor. Sustainability (Switzerland), 14(16), 1–16. https://doi.org/10.3390/su14169845

Xu, Z., Zhao, Y., Liew, J., Zhou, X., & Kogut, A. (2023). Synthesizing research evidence on self-regulated learning and academic achievement in online and blended learning environments: A scoping review. Educational Research Review, 39, 1–17. https://doi.org/10.1016/j.edurev.2023.100510

Zavyalova, K. (2020). Unlocking students’ motivation in the blended higher education classroom: Lecturers’ perspectives. E-Learning and Digital Media, 17(5), 425–441. https://doi.org/10.1177/2042753020931774

Zhang, Z., Li, Z., Liu, H., Cao, T., & Liu, S. (2020). Data-driven online learning engagement detection via facial expression and mouse behavior recognition technology. Journal of Educational Computing Research, 58(1), 63–86. https://doi.org/10.1177/0735633119825575

DOI: https://doi.org/10.35445/alishlah.v15i2.3850