Deconstructing University Learners' Adoption Intention Towards AIGC Technology: A Mixed‐Methods Study Using ChatGPT as an Example.

Background: ChatGPT, as a cutting‐edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated co...

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Publicado en:Journal of Computer Assisted Learning Vol. 41; no. 1; pp. 1 - 17
Autores principales: Wang, Chengliang, Chen, Xiaojiao, Hu, Zhebing, Jin, Sheng, Gu, Xiaoqing
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell Feb2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2025
      vid: 41
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        atl: Deconstructing University Learners' Adoption Intention Towards AIGC Technology: A Mixed‐Methods Study Using ChatGPT as an Example.
      aug:
        au:
          Wang, Chengliang
          Chen, Xiaojiao
          Hu, Zhebing
          Jin, Sheng
          Gu, Xiaoqing
        affil: Department of Education Information Technology, Faculty of Education, East China Normal University, Shanghai, China
      sug:
        subj:
          Artificial Intelligence, Generative
          Learning Methods
          Students, College
          Motivation
          Intention
          Student Attitudes
          Educational Technology
          Human
          Multimethod Studies
          Grounded Theory
          Questionnaires
          Interviews
          Random Sample
          Task Performance and Analysis
          Coding Methods
          Information Literacy
          Models, Theoretical
          Decision Making
          Exploratory Research
      ab: Background: ChatGPT, as a cutting‐edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated content (AIGC) technology, highlighting the need for deeper insights into the factors influencing adoption. Objectives: This study aims to investigate higher education learners' adoption intentions towards AIGC technology, with a focus on understanding the underlying reasons and future prospects for its application in education. Methods: The research is divided into two phases. First, an exploratory analysis involving practical activities and interviews develops an action decision framework for AIGC adoption. Second, a confirmatory analysis using fuzzy‐set qualitative comparative analysis on 233 valid questionnaires identifies six configurations associated with high adoption intentions, emphasising the roles of AI literacy and perceived behavioural control. Results and Conclusions: The study reveals key factors influencing AIGC adoption, including the importance of AI literacy and perceived behavioural control. It provides actionable insights for educators and learners to prepare for and effectively integrate AIGC technology, ensuring equitable and adaptive educational practices.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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