فصلنامه روندها و دستاوردها در فناوری یادگیری

فصلنامه روندها و دستاوردها در فناوری یادگیری

اعتباریابی مقیاس پذیرش هوش مصنوعی مولد در میان دانشجویان: آزمون یک مدل مبتنی بر نظریه یکپارچه پذیرش و کاربست فناوری (UTAUT)

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استادیار، گروه مدیریت آموزشی، دانشگاه فرهنگیان، تهران، ایران.
2 استادیار، گروه آموزش روانشناسی و مشاوره، دانشگاه فرهنگیان، تهران، ایران.
3 دانشجوی دکترا ، گروه علوم سیاسی، دانشگاه آزاد اسلامی، واحد کرمانشاه، کرمانشاه، ایران.
چکیده
هدف مطالعه، اعتباریابی مقیاس پذیرش هوش مصنوعی مولد مبتنی بر مدل نظریه یکپارچه پذیرش و استفاده از فناوری در میان دانشجویان ایرانی بود. جامعه آماری مشتمل بر تمامی دانشجویان مقطع کارشناسی دانشگاه‌های کشور بود که با استفاده از روش نمونه‌گیری در دسترس تعداد 351 نفر انتخاب شدند. ابزار گردآوری داده‌ها، نسخه فارسی مقیاس پذیرش هوش مصنوعی مولد شامل 20 ماده و چهار زیرمقیاس انتظار عملکرد، انتظار تلاش، شرایط تسهیل‌کننده و تأثیر اجتماعی بود. قبل از اجرا، از انطباق فرهنگی مقیاس با کمک روش ترجمه معکوس و روایی ظاهری با نظر خبرگان اطمینان حاصل شد. تجزیه و تحلیل داده‌ها با تحلیل عاملی مرتبه اول و دوم، ضریب آلفای کرونباخ، و آزمون t تک نمونه‌ای انجام شد. نتایج تحلیل عاملی مرتبه اول نشان داد که آیتم‌ها در دامنه 52/0 تا 87/0 قرار داشته و قابل تقلیل به چهار مؤلفه انتظار عملکرد، انتظار تلاش، شرایط تسهیل‌کننده و تأثیر اجتماعی هستند (95/0:CFI ؛056/0: RMSEA ؛12/2:X2/df). نتایج تحلیل مرتبه دوم نشان داد که چهار مؤلفه، می‌توانند تشکیل‌دهنده سازه کلی‌تر پذیرش هوش مصنوعی مولد باشند (94/0:CFI ؛060/0: RMSEA ؛26/2:X2/df). بار عاملی مؤلفه‌ها بر روی سازه کلی در دامنه 51/0 تا 82/0 قرار داشت. پایایی کل مقیاس 90/0 بود و پایایی زیرمقیاس‌ها در دامنه 61/0 تا 89/0 قرار داشت. بررسی وضعیت سازه نیز نشان داد که میزان پذیرش هوش مصنوعی مولد در میان دانشجویان مورد مطالعه بالاتر از متوسط بوده است (01/0P<). بر اساس یافته‌ها می‌توان در مطالعات آتی از این مقیاس برای سنجش میزان پذیرش هوش مصنوعی مولد استفاده کرد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Validation of the Generative Artificial Intelligence Acceptance Scale Among University Students: Testing a Model Based on the Unified Theory of Acceptance and Use of Technology (UTAUT)

نویسندگان English

Khalil Zandi 1
Seyed Adnan Hosseini 2
Elahe Niknam 3
1 Assistant Professor, Department of Educational Administration, Farhangian University, Tehran, Iran.
2 Assistant Professor, Department of Psychology Education and Counselling, Farhangian University, Tehran, Iran.
3 Ph.D Candidate of Political Science, Ker.C., Islamic Azad University, Kermanshah, Iran.
چکیده English

The purpose of this study was to validate the Generative Artificial Intelligence Acceptance Scale, grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), among Iranian university students. The statistical population consisted of all undergraduate students nationwide, from whom 351 participants were selected through convenience sampling. Data were collected using the Persian version of the Generative AI Acceptance Scale, comprising 20 items across four subscales: performance expectancy, effort expectancy, facilitating conditions, and social influence. Prior to administration, cultural adaptation was ensured through back-translation procedures and expert review for face validity. Data analyses included first- and second-order confirmatory factor analyses, Cronbach’s alpha coefficients, and one-sample t-tests. First-order CFA results indicated that item loadings ranged from 0.52 to 0.87, confirming the four-factor structure (χ²/df = 2.12; RMSEA = 0.056; CFI = 0.95). Second-order CFA further demonstrated that the four components collectively formed a higher-order construct representing generative AI acceptance (χ²/df = 2.26; RMSEA = 0.060; CFI = 0.94). Factor loadings of the components on the higher-order construct ranged from 0.51 to 0.82. The overall reliability of the scale was 0.90, and the subscales showed reliability values ranging from 0.61 to 0.89. Examination of the construct level also revealed that the generative AI acceptance score among the participating students was significantly above average (p < 0.01). Based on these findings, the scale can be effectively used in future research to assess generative AI acceptance among university students.

کلیدواژه‌ها English

Artificial intelligence
Effort expectancy
Facilitating conditions
Performance expectancy
Social influence
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  • تاریخ دریافت 10 تیر 1404
  • تاریخ بازنگری 24 مرداد 1404
  • تاریخ پذیرش 08 شهریور 1404
  • تاریخ انتشار 01 مهر 1404