AI-Enhanced Blended Learning Models: Testing and Evaluating an Innovative Educational Framework

DOI

10.2991/978-2-38476-487-7_3How to use a DOI?

Keywords

Artificial Intelligence (AI); Blended Learning; Educational Technology Evaluation

Abstract

This study explores the theoretical foundations, practical implementation, and preliminary evaluation of AI-enhanced blended learning models within a specific secondary education context in Southeast China. As schools navigate digital transformation, developing pedagogical strategies that effectively bridge traditional instruction and digital environments while addressing diverse learner needs is crucial. This research introduces and conducts an initial test of an AI-integrated blended learning framework designed to optimize instruction, potentially enhance emotional engagement, and improve academic outcomes in a 10th-grade Chinese Literacy course. It compares the effectiveness over one week of three instructional models—AI-Enhanced Complementary, AI-Enhanced Flipped, and Traditional—across key dimensions: academic performance, student engagement (self-reported), and emotional responsiveness (via aggregated AI analytics). AI tools, including emotion recognition and adaptive platforms, were employed to explore personalization and data-informed adjustments. Initial findings from this short-term, small-scale study suggest potential trends favouring AI-supported models in engagement and academic scores, with statistically significant differences observed in both areas despite the study’s limitations. A deeper analysis explores the relationship between aggregated emotional responses, engagement, and performance, suggesting potential alignments. The study highlights the feasibility of implementing such models but underscores the need for larger, longitudinal research and careful consideration of practical applications of AI data. It also acknowledges critical ethical considerations like data privacy, consent, and equity. This work contributes preliminary insights into AI integration in specific contexts, informing future research and practice for educational innovation.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yuzhe Chi
PY  - 2025
DA  - 2025/11/10
TI  - AI-Enhanced Blended Learning Models: Testing and Evaluating an Innovative Educational Framework
BT  - Proceedings of the 2025 International Conference on Digital Technology and Educational Psychology (DTEP 2025)
PB  - Atlantis Press
SP  - 15
EP  - 28
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-487-7_3
DO  - 10.2991/978-2-38476-487-7_3
ID  - Chi2025
ER  -