مقایسه مدل های سنجش کیفیت خدمات در ارزیابی دانشجویان از کیفیت فرایند تدریس و یادگیری با استفاده از شبکۀ عصبی مصنوعی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استاد دانشکدة اقتصاد و توسعة کشاورزی، دانشگاه تهران

2 دانشجوی کارشناسی ارشد آموزش کشاورزی، دانشگاه تهران

3 استاد دانشکدة مهندسی فناوری کشاورزی، دانشگاه تهران

چکیده

هدف از این مطالعه تعیین و ارزیابی کمی موقعیت کیفی فرایند تدریس و یادگیری در مراکز آموزش عالی کشاورزی است. به این منظور، از توانمندی شبکه‌های عصبی مصنوعی در مدل‌سازی روابط غیر خطی، برای بررسی و ارزیابی مدل‌های مختلف سنجش کیفیت خدمات استفاده شد. جامعة آماری، دانشجویان تحصیلات تکمیلی رشته‌های کشاورزی دانشگاه فردوسی مشهد (1070نفر) است که با استفاده از جدول مورگان 280 پرسشنامه جمع‌آوری شد و درنهایت 202 پرسشنامه تجزیه و تحلیل شد. به‌منظور بررسی و ارزیابی کیفیت فرایند تدریس و یادگیری از چهار مدل سروپروف غیر وزنی، سروکوآل غیر وزنی، سروپرف وزنی و سروکوآل وزنی به کمک شبکه‌های عصبی مصنوعی استفاده شد. نتایج به‌کارگیری رویکرد شبکه‌‌های عصبی مصنوعی نشان داد مدل سروکوآل وزنی با دقت بیشتری قادر به ارزیابی کیفیت تدریس و پیش‌بینی رضایت است. این مدل با معماری 7-29-14-1 یعنی 7 نرون در لایة ورودی، 29 و 14 نرون در لایه‌های مخفی اول و دوم و یک نرون در لایة خروجی، به‌عنوان بهترین راه حل برای تخمین ارزیابی کیفیت انتخاب شد. این معماری دارای ضریب همبستگی 96/0 بود و مقایر MAE، MSE و MAPE آن به‌ترتیب 18/0، 06/0 و 41/4 درصد داشتند.

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