پیشنهاددهنده تطبیقی منابع آموزشی بر اساس سبک یادگیری، بازخورد کاربر و الگوریتم اتوماتای یادگیر
الموضوعات :محمد طهماسبي 1 , فرانک فتوحی 2 , مهدی اسماعیلي 3
1 - دانشگاه قم
2 - دانشگاه قم
3 - دانشگاه آزاد اسلامي واحد کاشان
الکلمات المفتاحية: سیستم پیشنهاددهندهسبک یادگیرییادگیری بر اساس منابع آموزشییادگیری پیشرفته آموزشیرتبه‌بندی صفحاتشخصی‌سازی,
ملخص المقالة :
سیستم‌های پیشنهاددهنده شخصی‌سازی شده، در کنار موتورهای جستجو، راهکاری برای غلبه بر مشکل گرانباری اطلاعات هستند به گونه‌ای که در آنها سعی می‌شود با استفاده از تکنیکهای هوشمند و تعاملات کاربران در وب، محیطی شخصی‌سازی شده جهت تولید پیشنهادات مناسب فراهم آید. یکی از زمینههای کاربردی برای این سیستم‌ها، محدوده یادگیری تطبیقی است. یک زیرسیستم پیشنهاددهنده، ماژول مهمی از سیستم‌های تطبیقی آموزشی است که وظیفه ارائه اشیای آموزشی مناسب به کاربر خود را دارد. کاربران گوسفند خاکستری، یکی از چالش‌های مطرح‌شده در این دسته از سیستم‌ها هستند. این کاربران تشابه کمی با دیگر فراگیران دارند لذا پیشنهادات ارائه‌شده برای دیگران و یا بر اساس عادات قبلی آنها، لزوماً مناسب این نوع از کاربران نیست. برای حل این چالش، راهکار مطرح‌شده در این مقاله، استخراج فراداده صفحات آموزشی وب و تطابق آنها با خصوصیت سبک یادگیری کاربر در قالب یک فرمول رتبه‌بندی، جهت ارائه مناسب‌ترین پیشنهاد منبع آموزشی برای یک فراگیر است. تعیین سبک یادگیری کاربر، بر اساس مدل فلدر- سیلورمن انجام می‌گیرد. سپس بر طبق میزان آن، صفحات مناسب برای آموزش و یادگیری بر حسب پارامترهای صریح و پنهان تعریف‌شده در آن صفحات، استخراج و پیشنهاد می‌گردند. پاسخ سیستم به پرس و جوی کاربر در قالب خروجی ایده مطرح‌شده، به وی نمایش داده می‌شود. همچنین کاربر می‌تواند جواب پیشنهادات برای سؤال خود را با خروجی الگوریتم لوسین که در اکثر موتورهای جستجو مورد استفاده است، برای مقایسه میزان مناسب‌بودن آنها مشاهده نماید. کاربر میزان مفیدبودن پیشنهادات مطرح‌شده را به سیستم بازخورد می‌دهد. این بازخورد برای الگوریتم اتوماتای یادگیر تعریف‌شده برای تولید نتایج و پیشنهادات بعدی، مورد استفاده قرار می‌گیرد. نمونه‌ای از سیستم پیاده‌سازی شده، در محیط آموزشی دانشگاهی، مورد ارزیابی دانشجویان قرار گرفته که نتایج بازخورد کاربران نشان از بهبود عملکرد سیستم نسبت به الگوریتم‌های متعارف جستجوی عمومی دارد. این سیستم را می‌توان به صورت یادگیری رسمی و غیر رسمی بر پایه منبع در محیط وب، مورد استفاده قرار داد.
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