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Unlocking the potential of artificial intelligence in improving learning achievement in blended learning: a
Jiajun Wu1, Ahmed Tlili2, Soheil Salha3
1Faculty of Education, City University of Macau, Taipa, Macau SAR, China.
Frontiers in Psychology
|November 17, 2025
Summary
Artificial intelligence (AI) in blended learning shows a medium effect on student achievement. Personalized AI systems yield the largest gains, with context and study design influencing outcomes.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
Background:
- Blended learning effectiveness is established, but the impact of integrating Artificial Intelligence (AI) remains less understood.
- Limited research exists on how AI specifically enhances learning achievement within blended learning environments.
Purpose of the Study:
- To systematically evaluate the impact of AI-enhanced blended learning on student learning achievement through meta-analysis.
- To investigate moderating variables such as AI type, intervention duration, research design, sample size, educational level, and subject area.
Main Methods:
- A meta-analysis was conducted on 21 studies involving 2,873 participants.
- The analysis examined the effect size of AI in blended learning on student achievement.
- Moderating factors including AI technology type, intervention duration, research design, sample size, educational level, and subject area were analyzed.
Main Results:
- AI integration in blended learning demonstrated a medium overall effect size (g = 0.5) on student learning achievement.
- Personalized AI systems exhibited the largest effect size compared to chatbots and intelligent tutoring systems.
- Educational context (grade level, subject) and experimental design (duration, sample size) significantly moderated AI's impact.
Conclusions:
- AI significantly enhances student learning achievement in blended learning settings.
- Personalized AI approaches show particular promise for maximizing learning gains.
- Understanding moderating factors is crucial for optimizing AI integration in education.
Keywords:
artificial intelligenceblended learninghybrid learninglearning achievementlearning performancemeta-analysisquantitative evidencesmart learningMore Related Videos
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