Academic Journal
Exploring student motivations for AI usage in education: Nisantasi in Turkey, a case study.
| Τίτλος: | Exploring student motivations for AI usage in education: Nisantasi in Turkey, a case study. |
|---|---|
| Συγγραφείς: | Al-Sayid F; Faculty of Economics, Administrative and Social Sciences, İstanbul Nişantaşı University, Istanbul, 34083, Turkey. Electronic address: fareed_press@hotmail.com., Alpago H; Faculty of Economics, Administrative and Social Sciences, İstanbul Nişantaşı University, Istanbul, 34083, Turkey. Electronic address: hasan.alpago@nisantasi.edu.tr., Kirkil G; Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, 34083, Turkey. Electronic address: gokhan.kirkil@khas.edu.tr. |
| Πηγή: | Acta psychologica [Acta Psychol (Amst)] 2026 Jun; Vol. 266, pp. 106852. Date of Electronic Publication: 2026 Apr 20. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: North Holland Publishing Country of Publication: Netherlands NLM ID: 0370366 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-6297 (Electronic) Linking ISSN: 00016918 NLM ISO Abbreviation: Acta Psychol (Amst) Subsets: MEDLINE |
| Imprint Name(s): | Publication: Amsterdam : North Holland Publishing Original Publication: The Hague. |
| Ιατρικοί όροι (MeSH): | Students*/psychology , Motivation* , Artificial Intelligence*, Humans ; Turkey ; Universities ; Female ; Male ; Young Adult ; Adult |
| Περίληψη: | The purpose of this study wasto examine the main triggers that drive students to adopt artificial intelligence (AI) platforms at university level. Thestudy seeks to build and test a conceptual model of the factors that drive student use of AI-enhanced learning applications. The area of study is broad, addressing intrinsic and extrinsic motivations; Information Seeking, Productivity, Novelty, Enjoyment and Satisfaction dimensions, as well as digital literacy. It uses a mixed methods approach: first, qualitative datawere based on semi-structured interviews with students and experts, and secondly, a quantitative analysis of structured surveys. Data were processed using SPSS and method used was reliability analysis, factor analysis, t-test, ANOVA, correlationand regression analysis. The fit model accounts for 71.2% of variance in students' motivation,with extrinsic factors, and in particular, information seeking, productivity and novelty being the main predictors. Motivationis highly affected by intrinsic elements. Designing an AI platform in line with students' learning circumstances,familiarity with technology and preferences is critical. This study has practical implications for educators,developers, and policy makers who interested to improve learning engagement through AI integration. (Copyright © 2026 The Authors. Published by Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare no competing interests. |
| Contributed Indexing: | Keywords: AI motivations; ChatGPT; Extrinsic motivation; Grounded theory; Intrinsic motivation |
| Entry Date(s): | Date Created: 20260421 Date Completed: 20260715 Latest Revision: 20260715 |
| Update Code: | 20260715 |
| DOI: | 10.1016/j.actpsy.2026.106852 |
| PMID: | 42013755 |
| Βάση Δεδομένων: | MEDLINE |
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