شناسایی ابعاد، مولفه‌ها و شاخص های کارکردهای هوش مصنوعی در آموزش عالی با رویکرد فراترکیب

نوع مقاله : ویژه‌نامه پاییز ۱۴۰۴

نویسندگان

1 دانشیار گروه علوم تربیتی، دانشگاه پیام نور، تهران، ایران.

2 دانشجوی دکتری برنامه ریزی آموزش از راه دور، دانشگاه پیام نور، تهران، ایران

چکیده

پژوهش حاضر با هدف شناسایی ابعاد، مولفه‌ها و شاخص های کارکردهای هوش مصنوعی در آموزش عالی انجام شد. پژوهش به لحاظ هدف، کاربردی و از نوع داده‌ها، کیفی بوده و با استفاده از روش فراترکیب انجام شد. جامعه مورد مطالعه شامل تمامی اسناد، مبانی نظری و پیشینه مرتبط با کارکردهای هوش مصنوعی در آموزش عالی در پایگاه‌های داده ایرانی (1403-1395) و خارجی (2025-2010) بود. نمونه‌گیری به‌صورت هدفمند انجام شد و حجم نمونه بر اساس حذف سیستماتیک طبق نمودار جریان مدل پریزما تعیین گردید. ابزار جمع‌آوری داده‌ها شامل فیش‌برداری و مرور سیستماتیک ادبیات بود و برای محاسبه روایی از چک‌لیست 27 موردی براساس مدل پریزما و برای محاسبه پایایی از ضریب کاپای کوهن استفاده شد. تحلیل داده‌ها با نرم‌افزار MaxQDA2018 و به‌روش تحلیل مضمون انجام شد. یافته‌ها نشان داد که کارکردهای هوش مصنوعی در آموزش عالی شامل ابعاد شخصی سازی یادگیری، تجزیه و تحلیل داده های آموزشی، پشتیبانی از تدریس و یادگیری و ارزیابی و پیش‌بینی موفقیت است که بعد شخصی سازی یادگیری دارای مولفه های شناسایی نیازهای یادگیری، منابع آموزشی متنوع و یادگیری خودگردان؛ بعد تجزیه و تحلیل داده­های آموزشی دارای مولفه‌های جمع‌آوری داده‌های یادگیری، تجزیه و تحلیل پیشرفته و گزارش‌دهی و مصورسازی؛ پشتیبانی از تدریس و یادگیری دارای مولفه های ابزارهای تدریس هوشمند، پشتیبانی از اساتید و یادگیری مشارکتی و بعد ارزیابی و پیش‌بینی موفقیت شامل مولفه های ارزیابی خودکار، پیش‌بینی موفقیت دانشجویان، ارزیابی کیفیت آموزش و بهبود مستمر است. ابعاد به طور تنگاتنگ به هم مرتبط هستند و همچنین به بهبود کیفیت آموزش و یادگیری در آموزش عالی کمک می‌کنند. این تحولات می‌توانند منجر به ارتقاء کیفیت آموزش و افزایش موفقیت دانشجویان شوند.

کلیدواژه‌ها

عنوان مقاله [English]

Identifying the Dimensions, Components and Indicators of Artificial Intelligence Functions in Higher Education with a Meta-Synthesis Approach

نویسندگان [English]

  • Nazila Khatib Zanjani 1
  • Mahsa Karimi 2
1 Associate Professor of Department of Education, Payam Noor University, Tehran, Iran.
2 PhD Student, Department of Distance Education Planning, Payam Noor University,Tehran, Iran.
چکیده [English]

The present study was conducted with the purpose of researching aims to identify the dimensions, components, and indicators of the functions of artificial intelligence in higher education. This study is applied in terms of purpose and qualitative in terms of data type, and was conducted using a meta-synthesis method. The study population includes all documents, theoretical foundations, and literature related to the functions of artificial intelligence in higher education from Iranian databases (1395-1403) and foreign databases (2010-2025).  Sampling was conducted purposively and the sample size was determined based on systematic elimination according to the PRISMA flow chart. The data collection tools included data extraction and systematic literature review, and to assess validity, a 27-item checklist based on the PRISMA model was used, while Cohen’s Kappa coefficient was employed to assess reliability. Data analysis was conducted using MaxQDA2018 software and thematic analysis method. The findings indicate that the functions of artificial intelligence in higher education encompass dimensions such as personalized learning, educational data analytics, teaching and learning support, and assessment and success prediction. The personalized learning dimension includes components such as identifying learning needs, diverse educational resources, and self-directed learning; the educational data analytics dimension comprises components such as collecting learning data, advanced analysis, and reporting and visualization; the teaching and learning support dimension includes components such as intelligent teaching tools, support for instructors, and collaborative learning; and the assessment and success prediction dimension consists of components such as automated assessment, predicting student success, evaluating educational quality, and continuous improvement. These dimensions are closely interconnected and contribute to enhancing the quality of education and learning in higher education. These transformations can lead to improved educational quality and increased student success.

کلیدواژه‌ها [English]

  • Higher Education
  • Artificial Intelligence
  • Personalized Learning

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فناوری و دانش پژوهی در تعلیم و تربیت
دوره 5، ویژه نامه پاییز - شماره پیاپی 18
"هوش مصنوعی و تحول در آموزش و یادگیری"
آذر 1404
صفحه 9-25

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سابقه مقاله

  • تاریخ دریافت: 26 تیر 1404
  • تاریخ بازنگری: 07 شهریور 1404
  • تاریخ پذیرش: 08 آبان 1404
  • تاریخ اولین انتشار: 08 آبان 1404
  • تاریخ انتشار: 01 آذر 1404

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