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Psychometric Properties of the Persian ChatGPT Literacy Scale in Higher Education: A Transcultural Adaptation and Validation Study | ||
| Interdisciplinary Journal of Virtual Learning in Medical Sciences | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 11 خرداد 1405 | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.30476/ijvlms.2026.111068.1382 | ||
| نویسندگان | ||
| Abbas Taghizade* 1؛ Afzal Akbari Balootbangan2؛ Roshan Ahmadi3 | ||
| 1Department of Educational Sciences, Farhangian University, Tehran, Iran | ||
| 2Department, of Psychology and Counselling, Farhangian University, Tehran, Iran | ||
| 3Department of Educational Sciences, Faculty of Humanities, Shahid Rajaee Teacher Training University, Tehran, Iran | ||
| چکیده | ||
| Background: As ChatGPT becomes embedded in higher education, sound instruments are needed to measure students’ literacy in using this technology. Nevertheless, no Persian tool had undergone cultural adaptation and psychometric validation. This study sought to translate and culturally adapt the ChatGPT Literacy Scale (CLS) and examine its psychometric performance among Iranian higher education students. Methods: A transcultural adaptation and psychometric validation design was implemented from May through December 2025 with 371 students from five Iranian universities. The original 25-item CLS developed by Lee and Park (2024) was translated and culturally adapted according to the World Health Organization procedure for translating and adapting instruments. Two bilingual translators independently produced and reconciled Persian forward translations, after which a third bilingual translator, blinded to the source questionnaire, back-translated the reconciled version into English before expert review and administration. Evaluation included face and content validity, construct validity using exploratory and confirmatory factor analyses, and internal consistency based on Cronbach’s alpha and McDonald’s omega. Results: Face validity was supported, as every item had an impact score exceeding 1.5. Content validity was also satisfactory, with mean Content Validity Index (CVI) and Content Validity Ratio (CVR) values of 0.82 and 0.88, respectively. Exploratory Factor Analysis (EFA) identified five factors accounting for 57% of total variance, with item loadings ranging from 0.43 to 0.83. Confirmatory Factor Analysis (CFA) supported the first-order five-factor solution and demonstrated satisfactory model fit (χ²/df = 2.73, RMSEA = 0.069, GFI = 0.90, CFI = 0.97, NFI = 0.95, NNFI = 0.96, SRMR = 0.05). Internal consistency was satisfactory; Cronbach’s alpha and McDonald’s omega ranged from 0.72 to 0.89 across subscales, and both were 0.89 for the total scale. Conclusion: The culturally adapted Persian CLS demonstrated psychometric performance and can be considered a valid and reliable measure of ChatGPT literacy among Iranian higher education students. It can support researchers and educators in assessing AI-related competencies and developing evidence-informed initiatives that promote effective, ethical, and responsible use of ChatGPT in academic environments. | ||
تازه های تحقیق | ||
Abbas Taghizade (Google Scholar) | ||
| کلیدواژه‌ها | ||
| Artificial Intelligence؛ ChatGPT Literacy؛ Psychometrics؛ Transcultural Adaptation؛ Students؛ Iran | ||
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آمار تعداد مشاهده مقاله: 10 |
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