Related Experiment Video
Updated: Jan 11, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
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.
Introduction:
While several studies investigated the effect of blended learning on students' learning achievement, scant information exists on whether using artificial intelligence (AI) in blended learning could further contribute to the obtained effect.
Methods:
To effectively address the challenges and opportunities presented by blended learning and AI, the present study conducts a meta-analysis to systematically examine the impact of AI-enhanced blended learning on students' learning achievement, considering the significant role of multiple variables in shaping this achievement, including the type of AI technology, instruction duration, research design, and sample size as well as across different educational levels and subject areas. Specifically, 21 studies (N = 2,873 participants) were meta-analyzed.
Results:
The obtained results revealed that AI has a medium effect (g = 0.5) on students' learning achievement in blended learning. Particularly, personalized systems in blended learning had the highest effect (i.e., large) compared to chatbots and intelligent tutoring systems. Finally, it is seen that the educational context (grade level and educational subject), as well as the experiment type (research design, intervention duration, and sample size), moderate the effect of AI on students' learning achievement in blended learning.
Discussion:
The findings of this study can help researchers and practitioners better understand the effects of AI in blended learning, thereby contributing to a better design of teaching and learning experiences accordingly.
More Related Videos
06:11High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
Published on: September 26, 2025
10:43Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
Published on: June 10, 2021
Related Concept Videos
Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Metacognition
Associative Learning
Classical conditioning, also known...
Purposive Learning
Observational Learning
Avoidance Learning and Learned Helplessness
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...