70/100

Moderate evidence

Review of 29 studies finds AI tools tied to higher student grades

Study title: Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis

Evidence type
Systematic review or meta-analysis
Sample
n = 2,657
Sources
1 sourcePeer-reviewed
Published
1 min read

Study title: Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis

A meta-analysis published in Computers and Education: Artificial Intelligence pooled 29 empirical studies covering 2,657 participants at different educational levels. It found a significant positive effect of AI on students' academic performance, with an effect size of 0.924.

Read the study abstract

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 dura…

The gain

A meta-analysis of 29 empirical studies with 2,657 students found a significant positive effect of AI on academic performance, with an effect size of 0.924.

In brief

The authors followed PRISMA guidelines and drew studies from six databases: Scopus, Web of Science, APA PsycINFO, Education Full Text, ERIC and Social Sciences Full Text. They examined whether the effect varied by educational level, role of AI, intervention duration, sample size, learning strategy, subject area and type of AI.

The authors say the result gives a foundation for future research to identify the specific conditions under which AI most effectively improves student learning.

Main points

  1. The meta-analysis included 29 empirical studies that met its inclusion criteria.
  2. The combined sample was 2,657 participants across different educational levels.
  3. The overall effect size of AI on academic performance was 0.924.
  4. Studies were drawn from six databases, including Scopus, Web of Science and ERIC.
  5. Moderators tested were educational level, role of AI, intervention duration, sample size, learning strategy, subject area and type of AI.

The full story

The researchers searched six academic databases and selected 29 studies under PRISMA guidelines. The studies were coded, calculated and analysed to estimate the overall effect of AI on achievement.

They also set out to test moderator variables: educational level, the role AI played, how long the intervention lasted, sample size, learning strategy, subject area and type of AI. The overall finding was a significant positive effect of 0.924.

The authors conclude the work validates AI's efficacy and offers a base for identifying the conditions under which AI works best for student learning.

Sources

1 on file
  1. Peer-reviewed2025-03-20

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Who gets this benefit, and who was left out of the study or story?

Start with a question

Review of 29 studies finds AI tools tied to higher student gradeshttps://truvace.com/item/examining-the-effect-of-artificial-intelligence-in-relation-to-students-academic

  1. Who gets this benefit, and who was left out of the study or story?

    The gain A meta-analysis of 29 empirical studies with 2,657 students found a significant positive effect of AI on academic performance, with an effect size of 0.924.

    Answer in the thread
  2. How 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 2,657, from Computers and Education: Artificial Intelligence.

    Answer in the thread
  3. What does it leave open? What else would you want to know before acting on it?

    Answer in the thread
  4. Have you seen AI used this way where you study, work or live? Did it go the same way?

    Answer in the thread

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