Evidence map›Paper›PMID 38628736›Full record

ArticleHeliyon2024

Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study.

Nisar Ahmed Dahri, Noraffandy Yahaya, Waleed Mugahed Al-Rahmi, Ahmed Aldraiweesh, Uthman Alturki, Sultan Almutairy, Anna Shutaleva, Rahim Bux Soomro

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
–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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

8 authors.

Nisar Ahmed DahriFaculty of Social Sciences and Humanities, School of Education, University Teknologi Malaysia, UTM Sukadi, Johor, 81310, Malaysia.
Noraffandy YahayaFaculty of Social Sciences and Humanities, School of Education, University Teknologi Malaysia, UTM Sukadi, Johor, 81310, Malaysia.
Waleed Mugahed Al-RahmiFaculty of Social Sciences and Humanities, School of Education, University Teknologi Malaysia, UTM Sukadi, Johor, 81310, Malaysia.
Ahmed AldraiweeshEducational Technology Department, College of Education, King Saud University, P.O. Box 21501, Riyadh, 11485, Saudi Arabia.
Uthman AlturkiEducational Technology Department, College of Education, King Saud University, P.O. Box 21501, Riyadh, 11485, Saudi Arabia.
Sultan AlmutairyEducational Technology Department, College of Education, King Saud University, P.O. Box 21501, Riyadh, 11485, Saudi Arabia.
Anna ShutalevaUral Federal University Named After the First President of Russia B. N. Yeltsin, 620002, Ekaterinburg, Russia.
Rahim Bux SoomroInstitute of Business Administration, Shah Abdul Latif University, Khairpur, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This mixed-method study explores the acceptance of ChatGPT as a tool for Metacognitive Self-Regulated Learning (MSRL) among academics. Despite the growing attention towards ChatGPT as a metacognitive learning tool, there is a need for a comprehensive understanding of the factors influencing its acceptance in academic settings. Engaging 300 preservice teachers through a ChatGPT-based scenario learning activity and utilizing convenience sampling, this study administered a questionnaire based on the proposed Technology Acceptance Model at UTM University's School of Education. Structural equation modelling was applied to analyze participants' perspectives on ChatGPT, considering factors like MSRL's impact on usage intention. Post-reflection sessions, semi-structured interviews, and record analysis were conducted to gather results. Findings indicate a high acceptance of ChatGPT, significantly influenced by personal competency, social influence, perceived AI usefulness, enjoyment, trust, AI intelligence, positive attitude, and metacognitive self-regulated learning. Interviews and record analysis suggest that academics view ChatGPT positively as an educational tool, seeing it as a solution to challenges in teaching and learning processes. The study highlights ChatGPT's potential to enhance MSRL and holds implications for teacher education and AI integration in educational settings.

Indexed as

AI in educationArtificial intelligenceChatGPTMetacognitionSelf-regulated learningTechnology acceptance model

Identifiers

PMID38628736
PMCPMC11016976

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.