Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis
Recent developments in artificial intelligence (AI) have revolutionized the field of education as its presence and benefits enable new methods for teaching and learning. Therefore, many empirical studies have been conducted to evaluate the effectiveness of using AI on students' academic achieve...
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| Language: | English |
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Elsevier
2025-06-01
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| Series: | Computers and Education: Artificial Intelligence |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666920X25000402 |
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| author | Liu Dong Xiuxiu Tang Xiyu Wang |
| author_facet | Liu Dong Xiuxiu Tang Xiyu Wang |
| author_sort | Liu Dong |
| collection | DOAJ |
| description | Recent developments in artificial intelligence (AI) have revolutionized the field of education as its presence and benefits enable new methods for teaching and learning. Therefore, many empirical studies have been conducted to evaluate the effectiveness of using AI on students' academic achievement. The purpose of this meta-analysis study was to examine the overall effect of AI on students' academic achievement in relation to a set of moderator variables including educational level, role of AI, intervention duration, sample size, learning strategy, subject area, and type of AI. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 29 empirical studies were selected from six databases (Scopus, Web of Science, APA PsycINFO, Education Full Text; Education Source, ERIC, and Social Sciences Full Text). These studies, comprising a sample of 2,657 participants across different educational levels, met the inclusion criteria before being coded, calculated, and analyzed. Overall, we found a significant positive effect of AI on students’ academic performance, with an effect size of 0.924. This study validates the efficacy of AI and provides a critical foundation for future research to identify and leverage specific conditions under which AI can most effectively enhance student learning. |
| format | Article |
| id | doaj-art-e657096026d14e0eb86fca8159ee220f |
| institution | Kabale University |
| issn | 2666-920X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers and Education: Artificial Intelligence |
| spelling | doaj-art-e657096026d14e0eb86fca8159ee220f2025-08-20T03:47:10ZengElsevierComputers and Education: Artificial Intelligence2666-920X2025-06-01810040010.1016/j.caeai.2025.100400Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysisLiu Dong0Xiuxiu Tang1Xiyu Wang2College of Education, Purdue University, West Lafayette, IN, 47906, USA; Corresponding author. Beering Hall, 100 N. University Street, West Lafayette, IN, 47906, USA.College of Arts & Letters, University of Notre Dame, South Bend, IN, 46556, USACollege of Education, Purdue University, West Lafayette, IN, 47906, USARecent developments in artificial intelligence (AI) have revolutionized the field of education as its presence and benefits enable new methods for teaching and learning. Therefore, many empirical studies have been conducted to evaluate the effectiveness of using AI on students' academic achievement. The purpose of this meta-analysis study was to examine the overall effect of AI on students' academic achievement in relation to a set of moderator variables including educational level, role of AI, intervention duration, sample size, learning strategy, subject area, and type of AI. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 29 empirical studies were selected from six databases (Scopus, Web of Science, APA PsycINFO, Education Full Text; Education Source, ERIC, and Social Sciences Full Text). These studies, comprising a sample of 2,657 participants across different educational levels, met the inclusion criteria before being coded, calculated, and analyzed. Overall, we found a significant positive effect of AI on students’ academic performance, with an effect size of 0.924. This study validates the efficacy of AI and provides a critical foundation for future research to identify and leverage specific conditions under which AI can most effectively enhance student learning.http://www.sciencedirect.com/science/article/pii/S2666920X25000402Meta-analysisArtificial intelligenceAcademic achievement |
| spellingShingle | Liu Dong Xiuxiu Tang Xiyu Wang Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis Computers and Education: Artificial Intelligence Meta-analysis Artificial intelligence Academic achievement |
| title | Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis |
| title_full | Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis |
| title_fullStr | Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis |
| title_full_unstemmed | Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis |
| title_short | Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis |
| title_sort | examining the effect of artificial intelligence in relation to students academic achievement a meta analysis |
| topic | Meta-analysis Artificial intelligence Academic achievement |
| url | http://www.sciencedirect.com/science/article/pii/S2666920X25000402 |
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