Evidence map›Paper›PMID 41982358›Full record

ArticleFrontiers in psychology2026

Generative AI an academic equalizer? The differential impact of AI-assisted learning on self-efficacy and intrinsic motivation among university students.

Hongmeng Shao, Rifeng Wang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hongmeng ShaoCollege of Advanced Manufacturing Engineering, Guangxi Science and Technology Normal University, Laibin, China.
Rifeng WangSchool of Artificial Intelligence, Guangxi Science and Technology Normal University, Laibin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generative AI tools have become more common in universities, but studies on the psychology of such use for all students remain insufficiently researched at this time point. This study investigated whether AI-assisted Learning (AIL) is associated with college Students' intrinsic motivation and Self-efficacy, and if these relationships vary based on Academic performance. A 2 × 2 quasi-experimental design was employed with 200 STEM undergraduates, who were classified into high- and low-achievement groups and assigned to either a DeepSeek-assisted writing condition or a traditional-support writing condition. Intrinsic Motivation and Self-efficacy of Participants after completing the Scientific Paper. The data were analysed by CFA, ANOVA/ANCOVA, mediation analysis and moderated-mediation analysis. The results indicated that the post-tasks' intrinsic motivation and self-efficacy of students under an AI-accompanied tutoring were much higher than those without it. Further analysis revealed a more pronounced impact of the Group Differences on lower achievers compared to higher ones. Also, intrinsic motivation partly explained why a Writing Support Type was associated with self-efficacy. According to the results, generative AI has equitising characteristics in higher education and provides more robust emotional assistance for weaker learners of initial knowledge.

Indexed as

academic achievement leveleducational equitygenerative AIintrinsic motivationscientific writingself-efficacy

Identifiers

PMID41982358
PMCPMC13071819

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.