Student Engagement in Artificial Intelligence-Based Learning: An Analysis of Behavioral, Emotional, and Cognitive Engagement

Dyah Kusumastuti; Nuraeningsih; Rahma Kurnia Novitasari

Student Engagement in Artificial Intelligence-Based Learning: An Analysis of Behavioral, Emotional, and Cognitive Engagement

Authors

Dyah Kusumastuti Universitas Muhammadiyah Purwokerto
Nuraeningsih Universitas Muria Kudus
Rahma Kurnia Novitasari Universitas Negeri Yogyakarta

Keywords:

Student Engagement, AI-Based Learning, Higher Education, Artificial Intelligence

Abstract

This study aims to describe the level of student engagement in Artificial Intelligence (AI)-based learning by examining three dimensions of engagement: behavioral, emotional, and cognitive. The respondents were students of the English Education Study Program at Universitas Muhammadiyah Purwokerto. Data were collected through a Likert-scale questionnaire (1–5) and analyzed descriptively. The results showed that student engagement was at a high level across all three dimensions. The average scores were 12.80 (out of 15) for behavioral engagement, 12.67 (out of 15) for emotional engagement, and 21.09 (out of 25) for cognitive engagement. These findings indicate students’ readiness to respond to the integration of AI in learning. Further research is recommended to analyze these aspects using a correlational quantitative approach or causal models such as Structural Equation Modeling (SEM) to explore the relationships between engagement and a broader range of factors.

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References

Azwar, S. (2017). Reliabilitas dan Validitas. Pustaka Pelajar.

Czerkawski, B. C., & Lyman, E. W. (2016). An instructional design framework for fostering student engagement in online learning environments. TechTrends, 60(6), 532–539. https://doi.org/10.1007/s11528-016-0110-z

Dixson, M. D. (2015). Measuring student engagement in the online course: The Online Student Engagement Scale (OSE). Online Learning, 19(4), 1–15. https://doi.org/10.24059/olj.v19i4.561

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059

Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64–71. https://doi.org/10.1007/s11528-014-0822

Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90, 36–53. https://doi.org/10.1016/j.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.

Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38(5), 758–773. https://doi.org/10.1080/03075079.2011.598505

Kim, Y., Park, Y., Cozart, J., & Lee, H. (2015). From motivation to engagement: The role of effort regulation in online learning. Educational Technology & Society, 18(4), 261–272.

Lee, J. (2014). The relationship between student engagement and academic performance: Is it a myth or reality? The Journal of Educational Research, 107(3), 177–185. https://doi.org/10.1080/00220671.2013.807491

Skinner, E. A., & Belmont, M. J. (1993). Motivation in the classroom: Reciprocal effects of teacher behavior and student engagement. Journal of Educational Psychology, 85(4), 571–581. https://doi.org/10.1037/0022-0663.85.4.571

Sugiyono. (2017). Metode Penelitian Pendidikan: Pendekatan Kuantitatif, Kualitatif, dan R&D. Alfabeta.

UNESCO. (2021). AI and Education: Guidance for Policy-Makers. United Nations Educational, Scientific and Cultural Organization.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

Zepke, N., & Leach, L. (2010). Improving student engagement: Ten proposals for action. Active Learning in Higher Education, 11(3), 167–177. https://doi.org/10.1177/1469787410379680

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2

Student Engagement in Artificial Intelligence-Based Learning: An Analysis of Behavioral, Emotional, and Cognitive Engagement