پیش‌بینی و تحلیل عملکرد دانشجویان به کمک تکنیک‌های داده‌کاوی به منظور بهبود عملکرد تحصیلی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 گروه مهندسی صنایع ، دانشکده فنی و مهندسی، دانشگاه تربت حیدریه تربت حیدریه ، ایران

2 مدرس دانشکده فنی و مهندسی ، گروه صنایع ، دانشگاه تربت حیدریه ، تربت حیدریه، ایران

3 گروه مهندسی صنایع، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران

چکیده

پیش‌بینی عملکرد تحصیلی دانشجویان و ارائه راهکارهای مفید برای افزایش اثربخشی آموزشی دانشگاه‌ها از اهمیت ویژه‌ای در موفقیت نظام‌های آموزشی برخوردار است. هدف مقاله حاضر، شناسایی شاخص‌های موثر بر عملکرد تحصیلی، پیش‌بینی وضعیت تحصیلی دانشجویان با استفاده از تکنیک‌های داده‌کاوی و در نهایت، ارائه روندی جدید برای اصلاح انتخاب واحد و راهکارهای آموزشی در جهت افزایش کارایی سیستم آموزش است. به همین منظور، داده‌های جمعیت‌شناختی و سوابق تحصیلی دانشجویان مقطع کارشناسی وارد پایگاه داده شدند. پس از پیش‌پردازش داده‌ها، 13 شاخص‌ در نظر گرفته شده بررسی و به عنوان شاخص‌های موثر شناسایی شدند و با کمک الگوریتم‌های مختلف، مدل‌های مختلفی برای پیش‌بینی وضعیت تحصیلی دانشجویان در نیمسال بعدی ارائه شد. در ادامه، مقایسه‌ای میان نتایج حاصل از 4 الگوریتم‌ مختلف صورت گرفته و بهترین مدل در دسته‌بندی، الگوریتم Logit Boost در هر دو حالت دو و چندکلاسه براساس شاخص‌های درصد صحت و سطح زیر نمودار ROC شناخته‌شده‌است. بنابراین می‌توان مدل پیشنهادی را به عنوان یک ابزار پشتیبان تصمیم‌‌گیری در سیستم‌های آموزشی مورد استفاده قرار داد. در نهایت، با توجه به نتایج بدست امده و نظر خواهی از خبرگان دانشگاهی، فرایند انتخاب واحد، بازطراحی گردید.

چکیده تصویری

پیش‌بینی و تحلیل عملکرد دانشجویان به کمک تکنیک‌های داده‌کاوی به منظور بهبود عملکرد تحصیلی

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Predicting and analyzing the performance of students through data mining techniques to improve academic performance

نویسندگان [English]

  • mohammad ghodoosi 1
  • fatemeh mirsaeedi 2
  • Hamidreza Koosha 3
1 Department of industrial Engineering, university of Torbat Heydarieh, Iran
2 department of industrial engineering , unvercity of torbat heydarieh, torbat heydarieh, iran
3 Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
چکیده [English]

To predict academic performance of students and provide useful strategies for increasing the educational effectiveness of universities is of particular importance in the success of educational systems. The purpose of this paper is to identify the effective indicators on academic performance, predict students' academic status using data mining techniques, and finally present a new trend for modifying unit selection and educational strategies to increase the efficiency of the education system. Because, Demographic data and academic records of undergraduate students are entered in database. After data preprocessing, 13 attributes are selected and identified effective with different algorithms, different models were proposed to predict the student's academic status in the next semester. Then, a comparison between the results of 4 different algorithms has done and the Logit Boost algorithm is known as the best model in categorizing in two class and multi-class according to accuracy rate and ROC. So, the proposed model can be used as a decision support tool in educational systems. Finally, due to the results obtained and the opinions of the academic experts, the process of selecting the unit was redesigned.

کلیدواژه‌ها [English]

  • Educational data mining
  • unit selection
  • academic performance
  • Logit Boost

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