Exploring the Influence of Personality Traits on Students’ Adoption of Artificial Intelligence for Literature Appreciation
Authors
Akademi Pengajian Bahasa, UiTM Cawangan Johor (Malaysia)
Akademi Pengajian Bahasa, UiTM Cawangan Johor (Malaysia)
Akademi Pengajian Bahasa, UiTM Cawangan Johor (Malaysia)
Akademi Pengajian Bahasa, UiTM Cawangan Johor (Malaysia)
Akademi Pengajian Bahasa, UiTM Cawangan Johor (Malaysia)
Akademi Pengajian Bahasa, UiTM Cawangan Johor (Malaysia)
Universitas Muhammadiyah Muara Bungo (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.102100085
Subject Category: Education
Volume/Issue: 10/21 | Page No: 1021-1027
Publication Timeline
Submitted: 2026-07-09
Accepted: 2026-07-14
Published: 2026-07-25
Abstract
Learning literature requires deep and creative analysis to support an in-depth understanding of a literary work. However, most current students are challenged by that idea because their dependency on technology is extremely high, which invites Artificial Intelligence (AI) into the picture. As students’ demographic backgrounds and psychological experiences shape their personality traits, their perceptions and reliance on AI may vary accordingly. Therefore, this study intends to investigate the potential relationship between students’ personality traits; introversion, extroversion, ambiversion, and omniversion and their adoption of artificial intelligence in completing their literature appreciation assignments. A quantitative approach was used to obtain the data; questionnaires. The study used purposive sampling of 36 Diploma in English for Professional Communication (LG120) UiTM Cawangan Johor (UiTMCJ) students who had taken the Literature (ALS103) subject in Semester 1. Data were collected through a structured questionnaire comprising eight sections, including a declaration of personality traits. The quantitative data obtained from the questionnaires were analysed using SPSS; the Chi-square and One-Way ANOVA tests were applied to assess the relationship between personality traits and students’ perception and dependency on AI in completing their literature appreciation assignments. Since previous literature revealed a significant relationship between roughly comparable variables, this study anticipates uncovering parallel findings within the present context. Findings are expected to provide insights into how personality differences influence AI adoption in literary studies, contributing to pedagogical strategies that balance technological support with critical and creative engagement in literature learning.
Keywords
Personality traits, Artificial Intelligence, Literature appreciation
Downloads
References
1. Alqahtani, N., & Wafula, Z. (2025). Artificial intelligence integration: Pedagogical strategies and policies at leading universities. Innovative Higher Education, 50(2), 665-684. [Google Scholar] [Crossref]
2. Baddane, K., & Ennam, A. (2024). Measuring pedagogical transformation: A quantitative analysis of critical thinking integration in literary criticism for heightened student engagement and learning outcomes. International Journal of Linguistics, Literature and Translation, 7(1), 39-50. [Google Scholar] [Crossref]
3. Băiceanu, C. M., Bădoi-Hammami, M., & Popa, C. S. (2025). ARTIFICIAL INTELLIGENCE LITERACY IN TEACHER EDUCATION: TOWARDS A PEDAGOGICAL FRAMEWORK FOR RESPONSIBLE INTEGRATION. [Google Scholar] [Crossref]
4. Bakar, S. Z. S. A., Sarijari, H., Dia Widyawati Amat, Z., Sumery, D. O., & Yusof, F. H. M. (2021). The Relationship between Lg120 Students’ Personality Traits and Their Character Preferences in ‘The Importance of Being Earnest’by Oscar Wilde. Social Sciences, 11(7), 547-560. [Google Scholar] [Crossref]
5. Chang, W. L., & Sun, J. C. Y. (2024). Evaluating AI's impact on self-regulated language learning: A systematic review. System, 126, 103484. [Google Scholar] [Crossref]
6. Du, C., Tang, M., Wang, C., Zou, B., Xia, Y., & Du, Y. (2025). Who is most likely to accept AI chatbots? A sequential explanatory mixed-methods study of personality and ChatGPT acceptance for language learning. Innovation in Language Learning and Teaching, 1-22. [Google Scholar] [Crossref]
7. Gansser, O. A., & Reich, C. S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. [Google Scholar] [Crossref]
8. HARIS, A. (2024). Introverts VS Extroverts. [Google Scholar] [Crossref]
9. Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M. (2024). The roles of personality traits, AI anxiety, and demographic factors in attitudes toward artificial intelligence. International Journal of Human–Computer Interaction, 40(2), 497-514. [Google Scholar] [Crossref]
10. Mustoip, S., Al Ghozali, M. I., Fadhlullah, M. Z. F., & Assenhaji, S. A. Y. (2024). Influence of introverted and extroverted personalities on English learning interaction for elementary school students. Elsya: Journal of English Language Studies, 6(1), 33-45. [Google Scholar] [Crossref]
11. Ozbey, F., & Yasa, Y. (2025). The relationships of personality traits on perceptions and attitudes of dentistry students towards AI. BMC Medical Education, 25(1), 26. [Google Scholar] [Crossref]
12. Son, J. B., Ružić, N. K., & Philpott, A. (2025). Artificial intelligence technologies and applications for language learning and teaching. Journal of China computer-assisted language learning, 5(1), 94-112. [Google Scholar] [Crossref]
13. Stein, J. P., Messingschlager, T., Gnambs, T., Hutmacher, F., & Appel, M. (2024). Attitudes towards AI: measurement and associations with personality. Scientific reports, 14(1), 2909. [Google Scholar] [Crossref]
14. Mubashir, A. S., Altaf, W., & Kainaat, R. (2025). Personality Traits and Attitudes Towards Artificial Intelligence Among University Students. Social Science Review Archives, 3(2), 1010-1019. [Google Scholar] [Crossref]
15. Riedl, R. (2023). Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions: R. Riedl. Electronic Markets, 32(4), 2021-2051. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
- Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
- “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
- Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
- Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study