توسعه و رواسازی پرسشنامه پذیرش هوش مصنوعی در آموزش عالی مبتنی بر مدل یکپارچه پذیرش و استفاده از فناوری: یک طرح روش‌های پژوهش آمیخته توسعه ابزار

نوع مقاله : پژوهشی

نویسندگان

1 کارشناسی ارشد روان شناسی تربیتی، دانشکده روان شناسی و علوم تربیتی دانشگاه تهران، تهران، ایران.

2 گروه روان شناسی تربیتی، دانشکده روان شناسی و علوم تربیتی، دانشگاه تهران، تهران، ایران

3 دانشیار سنجش آموزش، بخش تخصصی پژوهش و سنجش؛ دانشکده روان شناسی و علوم‌تربیتی؛ دانشگاه تهران، تهران، ایران

چکیده

با گسترش روزافزون فناوری هوش مصنوعی در آموزش عالی، شناسایی و ارزیابی عوامل مؤثر بر پذیرش و به‌کارگیری این فناوری به یکی از دغدغه‌های اصلی پژوهشگران، طراحان آموزشی، سیاست‌گذاران و مدیران آموزشی تبدیل شده است. اگرچه ابزارهایی برای سنجش پذیرش فناوری در دسترس هستند، تاکنون ابزار بومی و جامعی که به‌طور خاص مؤلفه‌های مؤثر بر پذیرش هوش مصنوعی در آموزش عالی را ارزیابی کند، طراحی نشده است. هدف پژوهش حاضر، توسعه و رواسازی پرسشنامه‌ای برای اندازه‌گیری عوامل مؤثر بر پذیرش و استفاده از فناوری هوش مصنوعی در آموزش عالی بر پایه مدل UTAUT است. این مطالعه با رویکرد پژوهش آمیخته مدل توسعه ابزار در دو بخش کیفی و کمّی (اسنادی و همبستگی) انجام شد. در بخش کیفی، نشانگان سازه ریسک ‌ادراک شده شناسایی شده و ضمن متناسب‌سازی سایر گویه‌ها به شکلی دقیق و بومی‌سازی‌شده، نسخه توسعه‌یافته‌ آماده شد. در بخش کمّی، نمونه‌ای ۲۳۰ نفر انتخاب شدند. ابزار پژوهش شامل ۲۹ گویه در قالب هفت سازه اصلی شامل عملکرد مورد انتظار، تلاش مورد انتظار، تأثیر اجتماعی، شرایط تسهیل‌گر، ریسک ادراک‌شده، قصد رفتاری و رفتار استفاده بود. روایی صوری و محتوایی ابزار با استفاده از نظر خبرگان و شاخص‌های CVR و CVI تأیید شد. همچنین ثبات و همسانی درونی ابزار از طریق آزمون بازآزمایی، ضریب آلفای کرونباخ و ضریب اُمگا برای هر سازه بررسی و تأیید گردید. یافته‌ها نشان می‌دهند که این ابزار از ویژگی‌های روان‌سنجی مناسبی برخوردار است و می‌تواند به‌طور مؤثری برای سنجش و تحلیل عوامل مؤثر بر پذیرش و استفاده از هوش مصنوعی در آموزش عالی به کار رود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Development and Validation of an Artificial Intelligence Acceptance Questionnaire in Higher Education Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) Model: A Mixed Methods Instrument Development Design

نویسندگان [English]

  • Amirhosein Zanganeh 1
  • Elahe Hejazi 2
  • Keyvan Salehi 3
1 MS in Educational Psychology, Faculty of Psychology and Education, University of Tehran, Tehran, Iran.
2 Department of Educational Psychology, Faculty of Psychology and Education, University of Tehran, Tehran, Iran
3 Associate Professor of Educational Assessment, Division of Research and Assessment, Faculty of Psychology and Education, University of Tehran, Tehran, Iran
چکیده [English]

With the rapid expansion of artificial intelligence technology in higher education, identifying and evaluating the factors that influence the adoption and utilization of this technology has become a significant concern for researchers, instructional designers, policymakers, and educational administrators. Although tools for measuring technology acceptance are available, no comprehensive, localized instrument has yet been developed specifically to assess the components affecting AI acceptance in higher education. The present study aimed to develop and validate a questionnaire to measure the factors influencing the acceptance and use of AI technology in higher education, based on UTAUT. This study employed a mixed-methods approach for instrument development, conducted in both qualitative and quantitative phases. In the qualitative phase, through the analysis of 10 relevant documents, the indicators of the perceived risk construct were identified. While adapting other items in a precise and localized manner, the developed version was prepared. In the quantitative phase, a sample consisting of 230 faculty members and students from universities in Tehran was selected using convenience sampling. The research instrument consisted of 29 items across seven main constructs. The instrument’s face and content validity were confirmed through expert review and the CVR and CVI indices. Additionally, the reliability and internal consistency of the instrument were verified through test–retest reliability, Cronbach’s alpha, and Omega coefficients for each construct. The findings indicate that this instrument possesses strong psychometric properties and can be effectively used to assess and analyze the factors influencing the acceptance and use of artificial intelligence in higher education.

کلیدواژه‌ها [English]

  • Artificial Intelligence
  • The extended Unified Theory of Acceptance and Use of Technology (UTAUT)
  • Higher Education
  • Validation
  • Mixed Methods Instrument Development Design

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