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Review of 25 studies finds AI tools linked to better student performance, especially in STEM
Study title: Analysing the Impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and Meta-analysis
- Evidence type
- Systematic review or meta-analysis
- Sample
- n = 25
- Sources
- 1 sourcePeer-reviewed
- Published
- 1 min read
- Truvace record
- TRV-2026-2857cite or check it
Study title: Analysing the Impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and Meta-analysis
A systematic review and meta-analysis searched the Web of Science and Scopus databases for research on how AI components and computational sciences affect student performance. After inclusion and exclusion criteria were applied, 25 articles remained in the sample.
Read the study abstract
Abstract Artificial intelligence (AI) and computational sciences have aroused a growing interest in education. Despite its relatively recent history, AI is increasingly being introduced into the classroom through different modalities, with the aim of improving student achievement. Thus, the purpose of the research is to analyse, quantitatively and qualitatively, the impact of AI components and computational sciences on student performance. For this purpose, a systematic review and meta-analysis have been carried…
The gain
A systematic review and meta-analysis of 25 articles found that AI and computational sciences had a positive impact on student performance, with higher attitude towards learning and motivation, especially in STEM subjects.
In brief
The results support a positive impact on performance, with a rise in students' attitude towards learning and motivation, especially in STEM (science, technology, engineering and mathematics) areas. The findings were consistent at all educational stages.
The authors say using these technologies in teaching brings a large educational and ethical challenge for teachers in how the tools are designed and implemented, which calls for further educational research.
Main points
- The review searched two databases, Web of Science and Scopus.
- After inclusion and exclusion criteria, 25 articles were analysed.
- The analysis combined quantitative and qualitative approaches.
- Student performance improved, along with attitude towards learning and motivation.
- The effects were strongest in STEM areas.
- Findings were consistent across all educational stages.
- Teachers face educational and ethical challenges in designing and implementing the technologies.
The full story
The study set out to analyse, both quantitatively and qualitatively, how AI components and computational sciences affect student performance. It used a systematic review and meta-analysis of literature from the Web of Science and Scopus databases.
Applying inclusion and exclusion criteria left a sample of 25 articles. The authors report that results support a positive impact on student performance, including higher motivation and a better attitude towards learning, especially in STEM subjects.
The authors report consistent findings at all educational stages. They also say that putting these technologies into instruction poses a great educational and ethical challenge for teachers, particularly in design and implementation, and call for further educational research.
Sources
1 on file- Journal of New Approaches in Educational Researchdoi:10.7821/naer.2023.1.1240
Talk it over
Who gets this benefit, and who was left out of the study or story?
Review of 25 studies finds AI tools linked to better student performance, especially in STEMhttps://truvace.com/item/analysing-the-impact-of-artificial-intelligence-and-computational-sciences-on-st
Who gets this benefit, and who was left out of the study or story?
The gain A systematic review and meta-analysis of 25 articles found that AI and computational sciences had a positive impact on student performance, with higher attitude towards learning and motivation, especially in STEM subjects.
Answer in the threadHow do we know? What can this kind of evidence show, and what can’t it?
The evidence This rests on a systematic review or meta-analysis with a sample of 25, from Journal of New Approaches in Educational Research.
Answer in the threadWhat does it leave open? What else would you want to know before acting on it?
The record’s own caveat The authors say that implementing these technologies in instruction poses a great educational and ethical challenge for teachers regarding design and implementation, which requires further analysis.
Answer in the threadHave you seen AI used this way where you study, work or live? Did it go the same way?
Answer in the thread
The questions are the same on every record. The details under them are taken from this record as written.
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