به کارگیری هوش مصنوعی مولد در تحلیل تحقیقات آمیخته
محورهای موضوعی : مدیریت آموزشی
1 - دانشگاه آزاد واحد تهران جنوب
کلید واژه: هوش مصنوعی مولد, تحقیق آمیخته, تحقیق کیفی, تحقیق کمی,
چکیده مقاله :
دستاوردهای اخیر در زمینه هوش مصنوعی مولد قادر است روش‌های تحقیقات علمی را دگرگون سازد. برای بهره‌برداری از ابزارهای نوین در تمامی حوزه‌های آموزشی، سازگاری با تغییرات سریع فناوری امری ضروری محسوب می‌شود. این مطالعه با هدف بررسی استفاده از هوش مصنوعی مولد[1] در تحلیل داده‌های تحقیق آمیخته (کیفی-کمی) نوشته شده است. در این تحقیق به بررسی این موضوع پرداخته می‌شود که داده‌های حاصل از هوش مصنوعی مولد چگونه می‌توانند معتبر و قابل اعتماد باشند. همچنین توصیه‌هایی نیز برای بهبود استفاده از این رویکرد برای استفاده در تحقیقات آمیخته ارائه می‌شود. هوش مصنوعی مولد به عنوان ابزاری فکری، می‌تواند بهترین همکاری را با دیدگاه‌های انسانی داشته باشد؛ این مسئله به‌ویژه در زمان کدگذاری داده‌های کیفی اهمیت می‌یابد. برای مثال، اگر از مدل هوش مصنوعی مولد [2]ChatGPT درخواست کدگذاری استقرایی شود، این پلتفرم می‌تواند کدهای عمومی را تولید کند که بر اساس تجزیه و تحلیل‌های انسانی، بهبود یافته و ارتباط معناداری بین کدگذاری انسانی و ماشین (هوش مصنوعی مولد) ایجاد شده است. همچنین، به کارگیری هوش مصنوعی مولد در تحلیل کمی داده‌های آمار توصیفی نیز می‌تواند دقیق باشد، اما محقق باید به‌طور منطقی بهترین انتخاب را برای انجام تحلیل استنباطی مناسب داشته باشد. به‌علاوه، برای تحلیل کمی و کیفی در تحقیقات آمیخته باید استفاده از هوش مصنوعی مولد به‌طور جداگانه مدنظر قرار گیرد. این مقاله شامل توصیه‌ها و راهنمایی‌هایی درباره نحوه استفاده اخلاقی، مسئولانه و علمی از هوش مصنوعی مولد در زمینه تحقیقات علوم اجتماعی و علوم انسانی است.
[1] Generative Artificial Intelligence (Gen AI)
[2] Chat Generative Pre-Trained Transformer
The next steps in the field of generative artificial intelligence (GAI) can transform scientific research methods. To utilize new tools in all educational fields, adaptation to rapid technological changes is required. This study was written with the aim of examining the use of artificial intelligence in mixed research data analysis (qualitative-quantitative). This study examines how the findings from artificial intelligence can be valid and reliable. It also provides recommendations for improving the use of this method for use in mixed research. Artificial intelligence, as an intellectual tool, can best collaborate with human perspectives. This issue becomes especially important during qualitative coding. For example, if the ChatGPT artificial intelligence model is asked to perform inductive coding, the platform can generate generic codes that are based on human analysis, improved, and meaningful connections between human and machine (GAI) coding. Also, the use of AI in quantitative analysis of descriptive statistics data can be accurate, but the researcher must make the best logical choice to perform the appropriate inferential analysis. In addition, GAI should be fully considered for quantitative and qualitative analysis in mixed research. This article provides recommendations and guidelines on how to use ethical, including cases of science and knowledge from artificial intelligence in the context of social science and humanities research.
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