Enhancing Critical Thinking and Self‐Efficacy With GenAI: A Social Cognitive Perspective Using Structural Equation Modelling.
Background: The integration of Generative Artificial Intelligence (GenAI) into higher education is growing rapidly, yet its impact on learning processes remains underexplored. Existing research and theories, such as social cognitive theory (SCT), largely focus on human‐to‐human learning interactions...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 1; pp. 1 - 15 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
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Wiley-Blackwell
Feb2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191181628&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191181628 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Feb2026 vid: 42 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 191181628 191181628 191181628 10.1002/jcal.70176 191181628 ppf: 1 ppct: 14 formats: tig: atl: Enhancing Critical Thinking and Self‐Efficacy With GenAI: A Social Cognitive Perspective Using Structural Equation Modelling. aug: au: Teng, Da Zhou, Xue Al‐Samarraie, Hosam Fang, Lei affil: Faculty of Economics and Management, Beijing University of Chemical Technology, Beijing, China sug: subj: Critical Thinking China Self-Efficacy Artificial Intelligence, Generative Cognition Structural Equation Modeling Utilization Social Learning Theory Learning Methods Students, Undergraduate Human Cross Sectional Studies Surveys China Program Implementation Play and Playthings Male Female Adolescence Social Cognition Young Adult Descriptive Statistics Data Analysis Software Adolescent: 13-18 years Male Female ab: Background: The integration of Generative Artificial Intelligence (GenAI) into higher education is growing rapidly, yet its impact on learning processes remains underexplored. Existing research and theories, such as social cognitive theory (SCT), largely focus on human‐to‐human learning interactions, leaving a gap in understanding how cognitive and motivational mechanisms operate in human–AI contexts. Objectives: This study investigates how GenAI features influence students' critical thinking and self‐efficacy, with a specific focus on the mediating role of cognitive engagement. Methods: Drawing on SCT, we conceptualised GenAI features—playfulness, perceived learning value and output quality—as environmental stimuli influencing student outcomes via cognitive engagement. Survey data were collected from 223 undergraduate and postgraduate students. Structural equation modelling was used to test both direct effects and the mediating role of cognitive engagement. Results and Conclusions: The results indicate that GenAI playfulness and perceived learning value significantly enhance students' cognitive engagement, which then positively affects their critical thinking and self‐efficacy. Cognitive engagement functioned as a key mediator in these relationships. However, output quality did not exhibit a significant effect, suggesting that engagement, rather than content quality alone, is crucial for fostering meaningful cognitive development. This study extends SCT by adapting it to human–AI learning contexts and provides actionable insights for designing GenAI tools that enhance learner engagement and development. Lay Summary: What is currently known about this topic? ○Critical thinking and self‐efficacy are essential learning outcomes.○Cognitive engagement supports academic motivation and deeper learning.○Most studies focus on GenAI's direct effects, not underlying mechanisms.○Current theories like SCT focus on human‐to‐human learning interactions.What does this paper add? ○Shows how GenAI features impact learning via cognitive engagement.○Identifies playfulness and learning value as key drivers of engagement.○Demonstrates cognitive engagement boosts critical thinking and self‐belief.○Extends Social Cognitive Theory to include human–AI interaction.Implications for practice or policy ○Design GenAI tools that actively promote student engagement.○Emphasise learning value and interactivity over output accuracy alone.○Train educators to integrate GenAI in ways that support reflection.○GenAI can act as a co‐learner, peer or teacher, supporting interactive learning experiences. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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