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TRUVACE RECORD VERSION
record: TRV-2026-2205
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-23T06:45:47.965025Z
status: published
lens: g_space
sector: education
headline: When college students perceive GAI feedback as credible: the role of perceived GAI feedback credibility in promoting deep learning through cognitive engagement
dek: Generative artificial intelligence (GAI) has rapidly developed in higher education and has raised new questions from an educational psychology perspective. Why does GAI feedback promote meaningful learning for some college students but fail to produce similar learning benefits for others? To answer this question, this study develops a theoretical framework based on Information Processing Theory, Elaboration Likelihood Model, and Constructivist Learning Theory. This study examines how perceived GAI feedback credi…
gain_title: Among 506 surveyed undergraduates, those who judged generative AI feedback as more credible reported higher cognitive engagement and deeper learning, with engagement partly explaining the link.
problem_title: (none)
trace_subject: (none)
gain_reading: Among 506 surveyed undergraduates, those who judged generative AI feedback as more credible reported higher cognitive engagement and deeper learning, with engagement partly explaining the link.
gain_evidence: perceived GAI feedback credibility has positive relationships with both cognitive engagement and deep learning | cognitive engagement plays a significant mediating role
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers surveyed 506 undergraduate students chosen through stratified sampling and analyzed the responses with structural equation modeling. They tested whether students' judgments of how credible generative AI feedback is relate to cognitive engagement and to deep learning.

The study suggests that the benefit of AI feedback depends on how students evaluate and process it, not on the technology alone. It helps explain why some students gain from the tools and others do not, but the design is a questionnaire, so the findings show associations rather than proven causation.
limitation: The evidence comes from a questionnaire analyzed with structural equation modeling, and the authors say credible feedback 'may' support deep learning, so the findings suggest rather than prove a causal pathway.
tag: Evidence-backed gain
key_points: The sample was 506 undergraduate students selected through stratified simple sampling. | Perceived credibility of AI feedback was positively related to both cognitive engagement and deep learning. | Cognitive engagement mediated the link between perceived credibility and deep learning. | The framework draws on Information Processing Theory, the Elaboration Likelihood Model, and Constructivist Learning Theory.
rundown: The study begins from a puzzle in higher education: generative AI feedback promotes meaningful learning for some college students but does not produce similar benefits for others. It seeks to explain that difference through educational psychology.

Data came from questionnaires and were tested with structural equation modeling. The authors report that credible feedback may support deep learning by encouraging cognitive processing and reflective thinking.

The authors conclude that the effect of AI feedback does not simply come from the technology. Students' credibility judgments and their following cognitive engagement shape deep learning processes.
sources:
- peer_reviewed | Frontiers in Psychology | https://doi.org/10.3389/fpsyg.2026.1986129 | 2026-10-22
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