Analysis of the Influence of Neuroadaptive Learning Systems and Artificial Emotional Intelligence in Education on Deep Learning Mastery Through Cognitive Engagement Intensity and Emotional Regulation in Learning

Authors

  • Mad Umar
  • Zaenudin
  • Abdul Muin
  • Evi Gustini
  • Nita Andriani

Abstract

The rapid advancement of artificial intelligence has transformed higher education by enabling the integration of Neuroadaptive Learning Systems (NLS) and Artificial Emotional Intelligence in Education (AEIE) to create more personalized and intelligent learning environments. However, the mechanisms through which these technologies contribute to deep learning mastery remain insufficiently understood. This study investigates the direct and indirect effects of NLS and AEIE on Deep Learning Mastery (DLM), with Cognitive Engagement Intensity (CEI) and Emotional Regulation in Learning (ERL) serving as mediating variables. A quantitative explanatory design was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected through an online questionnaire from undergraduate students who had experienced AI-supported digital learning platforms for at least one academic semester. The structural model was estimated using SmartPLS 4 with a bootstrapping procedure of 5,000 resamples. The findings reveal that both NLS and AEIE significantly enhance Cognitive Engagement Intensity and Emotional Regulation in Learning. However, Cognitive Engagement Intensity does not significantly influence Deep Learning Mastery, nor does it mediate the relationships between AI-based educational technologies and learning outcomes. In contrast, Emotional Regulation in Learning emerges as the strongest predictor of Deep Learning Mastery and fully mediates the effects of both Neuroadaptive Learning Systems (β = 0.313, p < 0.001) and Artificial Emotional Intelligence in Education (β = 0.188, p = 0.004). These findings challenge traditional cognition-centered learning models by demonstrating that advanced educational technologies improve learning mastery primarily through strengthening students' emotional regulation rather than merely increasing cognitive engagement. The study contributes to the growing literature on AI-enhanced education by proposing an affective-centered framework for designing intelligent learning environments that promote sustainable conceptual mastery.

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Published

2025-12-05

How to Cite

Umar, M., Zaenudin, Muin, A., Gustini, E., & Andriani, N. (2025). Analysis of the Influence of Neuroadaptive Learning Systems and Artificial Emotional Intelligence in Education on Deep Learning Mastery Through Cognitive Engagement Intensity and Emotional Regulation in Learning. Philippine Journal of Basic Studies, 1(2). Retrieved from https://pjbs.pti.edu.ph/index.php/pjbs/article/view/89

Issue

Vol. 1 No. 2 (2025): PJBS Special Issue of 2025

Section

Articles

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Copyright (c) 2025 Mad Umar, Zaenudin, Abdul Muin, Evi Gustini, Nita Andriani

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