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TRUVACE RECORD VERSION
record: TRV-2026-2804
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:26:13.456162Z
status: published
lens: g_space
sector: education
headline: The effect of chatbots on learning: a meta-analysis of empirical research
dek: This meta-analysis aimed to comprehensively review empirical studies on the effect of chatbots on learning and quantitatively synthesize their findings to produce an overall effect size. Searching several databases yielded 28 eligible reports with 31 individual effect sizes. The results revealed a significant and medium effect (g = .48) of chatbots on learning. Further analyses indicated four significant moderators: the type of instruction in the comparison group, experimental duration, chatbot type, and chatbot…
gain_title: A meta-analysis of 28 empirical reports (31 effect sizes) found chatbots had a medium positive effect on learning (g = .48), with the largest effects in single-session use and for chatbots handling frequently asked questions.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 28 empirical reports (31 effect sizes) found chatbots had a medium positive effect on learning (g = .48), with the largest effects in single-session use and for chatbots handling frequently asked questions.
gain_evidence: The results revealed a significant and medium effect (g = .48) of chatbots on learning. | 28 eligible reports with 31 individual effect sizes
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis in the Journal of Research on Technology in Education pooled 28 eligible reports, giving 31 individual effect sizes, to estimate how chatbots affect learning. It found a significant, medium overall effect of g = .48.

The effect was not uniform. Four factors changed it: the type of instruction in the comparison group, how long the experiment lasted, the type of chatbot and the tasks the chatbot performed.

The largest effects appeared when the comparison group had no specific support, when the experiment lasted just one session, and when chatbots were task-focused and answered frequently asked questions. The authors conclude chatbots can be more effective in certain cases.
limitation: The effect varied significantly by comparison condition, duration, chatbot type and task, and the highest effects came from one-session experiments, so the overall figure does not apply equally across settings.
tag: Evidence-backed gain
key_points: The analysis covered 28 eligible reports that together supplied 31 effect sizes. | The overall effect of chatbots on learning was significant and medium (g = .48). | Four moderators were significant: comparison-group instruction, experiment duration, chatbot type and chatbot task. | Effects were highest when the comparison group got no specific support. | Single-session experiments produced the highest effect sizes. | Task-focused chatbots that handled frequently asked questions did best.
rundown: The researchers searched several databases for empirical studies on chatbots and learning and pooled their results quantitatively. They identified 28 eligible reports with 31 individual effect sizes, producing an overall effect of g = .48.

Moderator analyses showed which conditions shaped the result. Four were significant: what instruction the comparison group received, how long the experiment ran, the kind of chatbot and the tasks it performed.

The strongest results came when comparison students had no specific support, when the experiment lasted only one session, and when chatbots were task-focused and handled frequently asked questions. The authors say these findings suggest chatbots work better in some cases than others within their contribution area to learning.
sources:
- peer_reviewed | Journal of Research on Technology in Education | https://doi.org/10.1080/15391523.2023.2255698 | 2023-09-12
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