Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates

IntroductionThis experimental study investigates how engagement modes with AI-related information—structured courses, group discussions, and self-directed research—influence attitude polarization and policy preferences among 132 Chinese undergraduates at a northern Chinese university. Methods: Parti...

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Main Authors: Duan Bo, Aini Azeqa Ma’rof, Zeinab Zaremohzzabieh, Li Rongfeng, Zheng Danhe
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Psychology
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Online Access:https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1596330/full
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author Duan Bo
Duan Bo
Aini Azeqa Ma’rof
Aini Azeqa Ma’rof
Zeinab Zaremohzzabieh
Li Rongfeng
Zheng Danhe
Zheng Danhe
author_facet Duan Bo
Duan Bo
Aini Azeqa Ma’rof
Aini Azeqa Ma’rof
Zeinab Zaremohzzabieh
Li Rongfeng
Zheng Danhe
Zheng Danhe
author_sort Duan Bo
collection DOAJ
description IntroductionThis experimental study investigates how engagement modes with AI-related information—structured courses, group discussions, and self-directed research—influence attitude polarization and policy preferences among 132 Chinese undergraduates at a northern Chinese university. Methods: Participants were randomly assigned to conditions over a six-week intervention, with cognitive load and perceived reliability assessed as key mechanisms.MethodsParticipants were randomly assigned to conditions over a six-week intervention, with cognitive load and perceived reliability assessed as key mechanisms.ResultsHierarchical regression revealed structured courses, marked by high cognitive load and reliability, significantly reduced polarization (β = −0.32, p < 0.01, η2 = 0.11), while self-directed research increased it (β = 0.45, p < 0.01, η2 = 0.15). Self-reported polarization strongly correlated with pre-to-post-test shifts (r = 0.68, p < 0.001), validating the General Attitudes Toward Artificial Intelligence Scale (GAAIS). Policy preferences mirrored these shifts, with structured courses fostering balanced stances (mean change = −0.15, SD = 0.40, p < 0.05).DiscussionThis study suggests structured, reliable, cognitively demanding interventions mitigate polarization, offering theoretical insights into attitude formation and practical guidance for AI education and policy design.
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spelling doaj-art-143bbe693b8d4809ab2bee6bfe2a12082025-08-20T03:16:28ZengFrontiers Media S.A.Frontiers in Psychology1664-10782025-08-011610.3389/fpsyg.2025.15963301596330Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduatesDuan Bo0Duan Bo1Aini Azeqa Ma’rof2Aini Azeqa Ma’rof3Zeinab Zaremohzzabieh4Li Rongfeng5Zheng Danhe6Zheng Danhe7Faculty of Human Ecology, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Management, Shanxi Vocational University of Engineering Science and Technology, Taiyuan, ChinaFaculty of Human Ecology, Universiti Putra Malaysia, Serdang, MalaysiaInstitute for Social Science Studies, Universiti Putra Malaysia, Serdang, MalaysiaWomen and Family Studies Research Center, University of Religions and Denominations, Qom, IranDepartment of Management, Shanxi Vocational University of Engineering Science and Technology, Taiyuan, ChinaFaculty of Human Ecology, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Music and Dance, Jingdezhen University, Jingdezhen, ChinaIntroductionThis experimental study investigates how engagement modes with AI-related information—structured courses, group discussions, and self-directed research—influence attitude polarization and policy preferences among 132 Chinese undergraduates at a northern Chinese university. Methods: Participants were randomly assigned to conditions over a six-week intervention, with cognitive load and perceived reliability assessed as key mechanisms.MethodsParticipants were randomly assigned to conditions over a six-week intervention, with cognitive load and perceived reliability assessed as key mechanisms.ResultsHierarchical regression revealed structured courses, marked by high cognitive load and reliability, significantly reduced polarization (β = −0.32, p < 0.01, η2 = 0.11), while self-directed research increased it (β = 0.45, p < 0.01, η2 = 0.15). Self-reported polarization strongly correlated with pre-to-post-test shifts (r = 0.68, p < 0.001), validating the General Attitudes Toward Artificial Intelligence Scale (GAAIS). Policy preferences mirrored these shifts, with structured courses fostering balanced stances (mean change = −0.15, SD = 0.40, p < 0.05).DiscussionThis study suggests structured, reliable, cognitively demanding interventions mitigate polarization, offering theoretical insights into attitude formation and practical guidance for AI education and policy design.https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1596330/fullartificial intelligenceattitude polarizationcognitive loadperceived reliabilityinformation engagementsocial psychology
spellingShingle Duan Bo
Duan Bo
Aini Azeqa Ma’rof
Aini Azeqa Ma’rof
Zeinab Zaremohzzabieh
Li Rongfeng
Zheng Danhe
Zheng Danhe
Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates
Frontiers in Psychology
artificial intelligence
attitude polarization
cognitive load
perceived reliability
information engagement
social psychology
title Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates
title_full Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates
title_fullStr Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates
title_full_unstemmed Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates
title_short Engagement modes and attitude polarization toward AI: the role of cognitive load and reliability among Chinese undergraduates
title_sort engagement modes and attitude polarization toward ai the role of cognitive load and reliability among chinese undergraduates
topic artificial intelligence
attitude polarization
cognitive load
perceived reliability
information engagement
social psychology
url https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1596330/full
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