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Trust in ChatGPT and Perceived Academic Writing Improvement: A TAM-Based Quantitative Study in a ESL Context

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  • Author(s): Bilqees Anwer (ORCID Bilqees Anwer (ORCID 0009-0004-3693-9818)
  • Language:
    English
  • Source:
    International Journal of Technology in Education and Science. 2026 10(1):162-177.
  • Publication Date:
    2026
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      International Society for Technology, Education, and Science. e-mail: ijtesoffice@gmail.com; Web site: http://www.ijtes.net
    • Peer Reviewed:
      Y
    • Source:
      16
    • Education Level:
      Higher Education
      Postsecondary Education
    • Subject Terms:
    • Subject Terms:
    • ISSN:
      2651-5369
    • Abstract:
      This study examines the impact of undergraduate students' trust in ChatGPT on their perceived improvement in academic writing and their intention to utilize the tool in future writing tasks. Grounded in the Technology Acceptance Model (TAM) and the Trust in Technology Framework, the study employs a quantitative approach to examine student perceptions within a Functional English course at a public-sector university in Pakistan. A total of 225 students from the Telecommunication Engineering, Computer Science, and Chemistry departments participated in a structured survey. Descriptive statistics, Pearson's correlation, and multiple regression analysis revealed that trust in ChatGPT significantly correlates with perceived improvements in clarity, vocabulary, and organization. Moreover, overall trust and Acceptance were strong predictors of students' future intent to use ChatGPT. The findings suggest that students' confidence in AI feedback enhances their writing development, underscoring the importance of institutional support and the ethical integration of AI. This study contributes to the growing body of research on generative AI in education by providing localized insights from a non-Western English as a Second Language (ESL) context and recommending pedagogically sound strategies for responsible AI adoption.
    • Abstract:
      As Provided
    • Publication Date:
      2026
    • Accession Number:
      EJ1494433