Using ChatGPT-generated prequestions to improve memory and text comprehension.

Prequestioning is a learning method that involves guessing the answers to questions about to-be-learned information (i.e., prequestions), followed by the opportunity to discover the correct answers. Its application during self-regulated learning requires access to practice questions, which can often be quite limited. Across four experiments, we investigated a potential solution: using artificial intelligence (AI)-specifically, the large language model-based chatbot, ChatGPT-to generate prequestions. Experiment 1 found that AI-generated prequestioning enhanced the learning of an educational text relative to simply reading. Experiment 2 found that AI-generated questions and human-generated questions were equally effective at promoting learning. Experiments 3-4 revealed that prequestioning with questions generated using different AI prompts aided learning relative to studying an AI-generated outline. Across experiments, prequestioning benefited subsequent test performance on questions that were identical and nonidentical to those previously encountered. Together, these results highlight the potential of generative AI to facilitate prequestioning, yielding substantial learning benefits.

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Publication Details

Journal
Journal of Applied Research in Memory and Cognition
Published
2025-10-23
DOI
https://doi.org/10.1037/mac0000254
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Using ChatGPT-generated prequestions to improve memory and text comprehension.

Judith Schweppe, Steven C. Pan, Andy Z. J. Teo, Niklas Wenzel et al.
Journal of Applied Research in Memory and Cognition
Topic Modeling
article

Using ChatGPT-generated prequestions to improve memory and text comprehension.

Judith Schweppe, Steven C. Pan, Andy Z. J. Teo, Niklas Wenzel, Alyssa Indrajaya
article en

Abstract

Prequestioning is a learning method that involves guessing the answers to questions about to-be-learned information (i.e., prequestions), followed by the opportunity to discover the correct answers. Its application during self-regulated learning requires access to practice questions, which can often be quite limited. Across four experiments, we investigated a potential solution: using artificial intelligence (AI)-specifically, the large language model-based chatbot, ChatGPT-to generate prequestions. Experiment 1 found that AI-generated prequestioning enhanced the learning of an educational text relative to simply reading. Experiment 2 found that AI-generated questions and human-generated questions were equally effective at promoting learning. Experiments 3-4 revealed that prequestioning with questions generated using different AI prompts aided learning relative to studying an AI-generated outline. Across experiments, prequestioning benefited subsequent test performance on questions that were identical and nonidentical to those previously encountered. Together, these results highlight the potential of generative AI to facilitate prequestioning, yielding substantial learning benefits.

Journal of Applied Research in Memory and Cognition
Openalex Percentile: Top 84%
Topic Modeling
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Using ChatGPT-generated prequestions to improve memory and text comprehension. — Judith Schweppe, Steven C. Pan, et al. · Journal of Applied Research in Memory and Cognition (2025) | TGRS Research Map | TGRS