کاربست هوش مصنوعی مولد در مدیریت یادگیری و بهسازی فرایند تربیت معلم: فرصتها، چالشها و راهکارها
محورهای موضوعی : علوم تربیتی
علی اصغر مهرپور
1
,
محسن حاجی زاده اناری
2
1 - گروه آموزش تربیت بدنی، دانشگاه فرهنگیان، صندوق پستی 889-14665 تهران، ایران
2 - گروه روانشناسی و مشاوره، دانشگاه فرهنگیان، تهران، ایران
کلید واژه: تربیت معلم, هوش مصنوعی مولد, مدیریت یادگیری, چالشهای آموزشی, راهکارهای آموزشی نوین,
چکیده مقاله :
مقدمه و هدف: با توجه به اهمیت بهبود فرآیندهای آموزشی و نقش مدیریت یادگیری در تربیت معلم، هدف این مقاله بررسی فرصتها و چالشهای استفاده از هوش مصنوعی مولد در تربیت معلم و ارائه راهکارهای عملی برای بهرهگیری بهینه از این فناوری نوین است.
روششناسی پژوهش: این پژوهش کیفی با رویکرد توصیفی–تحلیلی و مبتنی بر مرور نظاممند اسناد و مصاحبههای نیمهساختاریافته است. دادهها از طریق مرور نظاممند منابع علمی منتشرشده در بازه زمانی ۲۰۱۸ تا ۲۰۲4 و مصاحبههای نیمهساختاریافته گردآوری شد. مشارکتکنندگان در مصاحبه شامل ۱8 نفر از خبرگان منتخب (7 عضو هیأت علمی در حوزه تربیت معلم و فناوری آموزشی، 5 متخصص هوش مصنوعی و 6 معلم باتجربه) بودند که بهصورت هدفمند انتخاب شدند. دادهها به روش تحلیل مضمون و با بهرهگیری از مراحل شش گانه براون و کلارک (2006) تحلیل شدند.
یافتهها: هوش مصنوعی مولد با فراهمآوری فرصتهایی مانند یادگیری شخصیسازیشده، تولید محتوای آموزشی جذاب، شبیهسازی محیطهای یادگیری و بازخورد تحلیلی دقیق، نقش مهمی در ارتقاء آموزش معلمان ایفا میکند. با وجود این مزایا، چالشهای مهمی نیز شناسایی شدند که شامل دغدغههای اخلاقی، خطر وابستگی بیش از حد به ابزارها، کاهش بالقوه تعامل انسانی، کمبود زیرساختهای لازم و مقاومت در برابر تغییر میشوند.
نتیجهگیری: بهرهگیری مؤثر از پتانسیل هوش مصنوعی در آموزش معلمان، مستلزم اتخاذ راهبردی جامع است. این راهبرد باید شامل رعایت دقیق اصول اخلاقی، تقویت هدفمند زیرساختها و منابع فنی، آموزش و توانمندسازی معلمان، ادغام متوازن این فناوری با روشهای سنتی و ادامه پژوهشهای بیشتر برای ارزیابی مداوم تأثیرات آن باشد.
Introduction: Given the importance of improving Educational processes and the role of learning management in teacher education, the aim of this article is to examine the opportunities and challenges of using generative artificial intelligence (AI) in teacher education and to propose practical strategies for its optimal utilization.
Methodology: This study is qualitative, descriptive-analytical in nature, and is based on a systematic review of documents and semi-structured interviews. Data were collected through a systematic review of scientific sources published between 2018 and 2024, as well as through semi-structured interviews. The interview participants consisted of 18 selected experts—seven faculty members in the field of teacher education and educational technology, five AI specialists, and six experienced teachers—who were chosen purposively. Data were analyzed using thematic analysis following the six-phase framework proposed by Braun andClarke (2006).
Findings: The Findings indicate that Generative Artificial Intelligence (GenAI) significantly elevates teacher education by offering crucial opportunities, including personalized learning, creating engaging educational content, simulating learning environments, and providing precise analytical feedback. Despite these advantages, key challenges were identified, comprising ethical concerns, the risk of excessive dependency on tools, a potential reduction in human interaction, a lack of necessary infrastructure, and resistance to change.
Conclusion: The effective utilization of GenAI’s potential in teacher education necessitates adopting a comprehensive strategy. This approach must involve strict adherence to ethical principles, targeted reinforcement of technical infrastructure and resources, training and empowerment of teachers, balanced integration of the technology with traditional methods, and a commitment to continued research for ongoing evaluation of its impacts.
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