Interplay of Cognitive Flexibility and Adaptive Emotion Regulation as Predictors of Academic Success in AI-Enhanced Learning Environments

Authors

    Malihe Ghafourimanesh Department of Psychology, CT.C., Islamic Azad University, Tehran, Iran.
    Katauon Haddadi * Department of Psychology, CT.C., Islamic Azad University, Tehran, Iran. drhaddadi@iau.ac.ir
    Fatemeh Mirchenari Department of Educational Psychology, CT.C., Islamic Azad University, Tehran, Iran
    Fateme Haj Manouchehri Department of Educational Psychology, CT.C., Islamic Azad University, Tehran, Iran
https://doi.org/10.61838/

Keywords:

Artificial intelligence in education, cognitive flexibility, adaptive emotion regulation, academic success, higher education, learning engagement

Abstract

Objective: The objective of this study was to examine the interactive predictive roles of cognitive flexibility and adaptive emotion regulation on academic success among university students learning in artificial intelligence–enhanced educational environments.

Methods and Materials: This quantitative cross-sectional correlational study was conducted among 317 undergraduate students from major public universities in Tehran who were enrolled in courses supported by AI-based learning platforms. Participants completed validated questionnaires measuring cognitive flexibility, adaptive emotion regulation, engagement with AI-enhanced learning systems, and academic success. Data were analyzed using descriptive statistics, Pearson correlations, hierarchical multiple regression, and structural equation modeling with SPSS 26 and AMOS 24. Model fit was evaluated using standard goodness-of-fit indices including CFI, TLI, RMSEA, and SRMR.

Findings: Hierarchical regression revealed that after controlling for demographic variables and AI-learning engagement, cognitive flexibility (β = .31, p < .001) and adaptive emotion regulation (β = .36, p < .001) significantly predicted academic success, together explaining 56% of the total variance. Structural equation modeling demonstrated strong direct effects of cognitive flexibility (β = .34, p < .001) and adaptive emotion regulation (β = .39, p < .001) on academic success, as well as significant indirect effects mediated through AI-learning engagement (β = .41, p < .001). The overall model exhibited satisfactory fit to the data (CFI = .95, TLI = .94, RMSEA = .061, SRMR = .047).

Conclusion: The findings indicate that cognitive flexibility and adaptive emotion regulation are critical psychological determinants of academic success in AI-enhanced learning environments and operate both directly and through strengthening students’ engagement with intelligent educational systems.

Downloads

Download data is not yet available.

References

Abdullahi, N. J. K. (2025). Managing Artificial Intelligence-Driven Platforms for Student Development. International Journal of Engineering Technology and Natural Sciences, 7(1), 75-86. https://doi.org/10.46923/ijets.v7i1.467

Abishev, N., Ramazanov, R. R., Abaideldanova, M., Chesnokova, K., & Baizhumayeva, A. (2025). Artificial Intelligence Model in the Cognitive and Learning Activities of University Subjects. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1623170

Amoah-Oppong, D., Coufie, P. J., Antwi, R., & Laing, E. V. (2025). Application of Artificial Intelligence Techniques on Lesson Delivery in Senior High Schools in Ghana: Enhancing Student Engagement, Personalised Learning, Performance Assessment and Holistic Development. https://doi.org/10.21203/rs.3.rs-6393110/v1

Aslam, F., Marwat, S. A., Arif, M., & Hussain, A. (2025). Artificial Intelligence in Higher Education: Shaping the Future of University Teaching Through Adaptive Learning, Intelligent Tutoring, and Academic Analytics. Ijss, 3(2), 46-64. https://doi.org/10.59075/ijss.v3i2.1007

Bhatia, A., Bhatia, P., & Sood, D. (2024). Leveraging AI to Transform Online Higher Education: Focusing on Personalized Learning, Assessment, and Student Engagement. International Journal of Management and Humanities, 11(1), 1-6. https://doi.org/10.35940/ijmh.a1753.11010924

Chun, Y. E., Hwang, S. W., & Burm, E. (2024). Exploring the Impact of AI-based Adaptive Learning on Academic Achievement: Focusing on the Mediating Learning Flow and Self-Directed Learning Ability. Asia-pacific Journal of Convergent Research Interchange, 10(7), 541-555. https://doi.org/10.47116/apjcri.2024.07.39

Dubuc, M., Aubertin‐Leheudre, M., & Karelis, A. D. (2020). Relationship Between Interference Control and Working Memory With Academic Performance in High School Students: The Adolescent Student Academic Performance Longitudinal Study (ASAP). Journal of adolescence, 80(1), 204-213. https://doi.org/10.1016/j.adolescence.2020.03.001

Ezzaim, A., Dahbi, A., Haidine, A., & Aqqal, A. (2024). The Impact of Implementing a Moodle Plug-in as an AI-based Adaptive Learning Solution on Learning Effectiveness: Case of Morocco. International Journal of Interactive Mobile Technologies (Ijim), 18(01), 133-149. https://doi.org/10.3991/ijim.v18i01.46309

Far, F. T., Ghanadzadegan, H., & Heydari, S. (2024). A Comparison of the Effectiveness of Emotional Cognitive Regulation Strategies and Self-Regulated Learning Strategies on Academic Self-Concept and Cognitive Flexibility in Elementary School Students With Specific Learning Disabilities in Reading. Injoeacs, 5(5), 124-132. https://doi.org/10.61838/kman.ijecs.5.5.14

Faridoon, N., Talpur, Q., Latif, F., Naz, G., & Shahzad, T. (2025). The Role of AI Tutors in Improving Academic Performance and Student Engagement. Aijss, 4(3), 5897-5910. https://doi.org/10.63056/acad.004.03.0837

Hamdani, D. A. (2025). Understanding Perceptions, Adoption Rates and Challenges of New Technologies in Education. Global Conference on Business and Social Sciences Proceeding, 17(1), 99-99. https://doi.org/10.35609/gcbssproceeding.2025.1(99)

Hussain, S., Ayub, F., Ahmed, N., & Din, Z. U. (2025). Cognitive Load Management Through Adaptive AI Learning System Implications for Student Focus and Retention. The Critical Review of Social Sciences Studies, 3(3), 701-719. https://doi.org/10.59075/kpfrdv65

Hussein, E., Hussein, M. A., & Al-Hendawi, M. (2025). Investigation Into the Applications of Artificial Intelligence (AI) in Special Education: A Literature Review. Social Sciences, 14(5), 288. https://doi.org/10.3390/socsci14050288

Jiang-tao, F. U., & Hali, A. U. (2025). The Role of the Reflective Thinking Scale for International Students in China Through Factor Analysis. Behavioral Sciences, 15(5), 651. https://doi.org/10.3390/bs15050651

Kaur, R., Sarkar, R., Lalitha, M. K., Chandra, S., & Anand, T. (2025). The Effect of AI-Enhanced Gamification on Learning Outcomes in Higher Education. 75-104. https://doi.org/10.4018/979-8-3373-5077-6.ch004

Khan, M. S., & Irfan, R. (2025). The Role of Artificial Intelligence in Academic Achievement in the Current Scenario. International Journal for Multidisciplinary Research, 7(4). https://doi.org/10.36948/ijfmr.2025.v07i04.49965

Kiran, A. S. (2025). Applications and Impacts of Ai Tools in Education. https://doi.org/10.47716/978-93-92090-38-7

Kishorchandra, P. V., & Rajnikant, P. (2025). The Impact of AI on the Learning Habits of HEI Students. International Journal of Current Science Research and Review, 08(07). https://doi.org/10.47191/ijcsrr/v8-i7-44

Maaz, N., Mounsef, J., & Maalouf, N. (2025). CARE: Towards Customized Assistive Robot-Based Education. Frontiers in Robotics and Ai, 12. https://doi.org/10.3389/frobt.2025.1474741

Mahafdah, R. F., Bouallegue, S., & Bouallègue, R. (2024). Enhancing E-Learning Through AI: Advanced Techniques for Optimizing Student Performance. https://doi.org/10.21203/rs.3.rs-4724603/v1

Melnichuk, M. V., & Belogash, M. A. (2021). Emotional Interaction as a Facilitator of IT-enhanced Distance Education. Liberal Arts in Russia, 162. https://doi.org/10.15643/libartrus-2021.3.3

Ouariach, S., Ouariach, F. Z., & Khaldi, M. (2025). Artificial Intelligence as a Harbinger of Engagement and Collaboration. 147-180. https://doi.org/10.4018/979-8-3373-2262-9.ch006

Pérez, E. E., & Losada, J. L. (2024). Using Artificial Intelligence in Education: Decision Tree Learning Results in Secondary School Students Based on Cold and Hot Executive Functions. Humanities and Social Sciences Communications, 11(1). https://doi.org/10.1057/s41599-024-04040-y

Rajavarman, V. N., Raja, V. S., R, M. S., & Senthilvelan, G. (2025). Ai in Education Today. https://doi.org/10.47716/978-93-92090-42-4

Sa-ad, M. M., Abukari, A. M., Korda, D. R., & Owusu-Boateng, O. (2025). Personalized Learning Experiences With Artificial Intelligence. https://doi.org/10.70593/978-93-49307-53-7_2

Sales, X. (2025). The Teaching Challenges of AI in Higher Education. 57-74. https://doi.org/10.63782/pf24004

Vikram, E., Kalaivani, K., Praanesh, M. R., & Surya, M. (2025). GEN AI Based Personalized AI Tutor. Interantional Journal of Scientific Research in Engineering and Management, 09(10), 1-9. https://doi.org/10.55041/ijsrem53002

Wyk, C. S. (2023). AI in Education. https://doi.org/10.38140/ufs.c.6762126

Zambrano, S. E. V., Herrera, P., Paltán, B. P. H., Atiencia, J. C. F., & Atiencia, J. C. F. (2025). Implementación De Inteligencia Artificial Para La Personalización Del Aprendizaje en Educación Superior. Salud Ciencia Y Tecnología - Serie De Conferencias, 4, 1436. https://doi.org/10.56294/sctconf20251436

Zhang, J. (2025). Emotional Intelligence, Foreign Language Enjoyment, and AI-Assisted Pedagogy: Integrating Positive Psychology for Resilient and Sustainable Language Learning. https://doi.org/10.21203/rs.3.rs-8256795/v1

Zhao, T. (2023). AI in Educational Technology. https://doi.org/10.20944/preprints202311.0106.v1

Zheng, M. (2025). Artificial Intelligence in Lifelong Learning: Enhancing Chinese Language Instruction for Non-Native Adult Learners. GBP Proc. Ser., 2, 141-146. https://doi.org/10.71222/vxzcka39

Downloads

Additional Files

Published

2026-03-10

Submitted

2025-09-01

Revised

2025-12-22

Accepted

2025-12-29

Issue

Section

Articles

How to Cite

Ghafourimanesh, M. ., Haddadi, K., Mirchenari, F. ., & Haj Manouchehri , F. . (2026). Interplay of Cognitive Flexibility and Adaptive Emotion Regulation as Predictors of Academic Success in AI-Enhanced Learning Environments. Journal of Adolescent and Youth Psychological Studies (JAYPS), 1-9. https://doi.org/10.61838/