تحلیل داده‌های آموزشی دانشجویان با هدف ارزیابی موفقیت تحصیلی با استفاده از رویکرد داده‌کاوی (نمونه موردی: دانشکده مدیریت و مهندسی صنایع دانشگاه شاهرود)

نوع مقاله : علمی - پژوهشی

نویسندگان

1 استادیار دانشکده مهندسی صنایع و مدیریت، دانشگاه صنعتی شاهرود.

2 استادیار، دانشکده مهندسی صنایع، دانشگاه آزاد لاهیجان

چکیده

کسب دانش پیرامون الگوهای رفتاری وضعیت تحصیلی دانشجویان نقش بسزایی در مدیریت موفق مراکز آموزشی و ارائه خدمات مطلوب و متناسب با وضعیت‌های فعلی و آتی تحصیلی دانشجویان دارد. این دانش، در اطلاعات آموزشی نهفته بوده و می‌تواند با استفاده از ابزار داده‌کاوی استخراج شود. در این مقاله یک مدل داده‌کاوی مبتنی بر تکنیک خوشه‌بندی سلسله‌مراتبی توسعه‌یافته برای تحلیل اطلاعات مربوط به وضعیت تحصیلی دانشجویان شامل اطلاعات پیش از ورود به دانشگاه و وضعیت تحصیلی آنان ارائه شده است. علاوه بر آن، یک مدل پیش‌بینی مبتنی بر قرارگیری هر دانشجو با مشخصات خاص در یک خوشه و برآورد عملکرد تحصیلی وی ارائه شده است. مدل داده‌کاوی پیشنهاد شده در دانشکده مدیریت دانشگاه صنعتی شاهرود به‌عنوان نمونه موردی پیاده‌سازی شده است. نتایج تحقیق توسط خبرگان و مدیران آموزشی دانشگاه اعتبارسنجی شده است. پس از تحلیل داده‌ها و ارائه مدل پیش‌بینـی، خوشه‌های دانشجویان مبتنی بر شاخص نشان‌دهنده وضعیت تحصیلی ارائه شده است. نتایج نشان می‌دهند که برخی از ویژگی‌های دانشجویان مربوط به دوران قبل و بعد از ورود آنان به دانشگاه بر تعلق آنان به خوشه‌های وضعیت تحصیلی تأثیر معنادار دارند. با استفاده از ابزار داده‌کاوی، مجموعه‌ای از قوانین برای ارتقای کیفیت تصمیمات مدیران آموزشی و انتقال دانشجویان از خوشه‌های با وضعیت تحصیلی نامناسب به وضعیت بهتر پیشنهاد شده است. هم‌چنین با توجه به شناسایی وضعیت تحصیلی دانشجویان، مدل پیش‌بینی‌کننده وضعیت آتی تحصیلی آنان نظیر رشد معدل و یا مشروطی تحصیلی ارائه شده است. تمامی نتایج با توجه به نظرات دریافت‌شده از خبرگان ارزیابی و اعتبار آنان تأیید شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Analyzing Students’ Educational Information to Evaluate Their Success via Using Data Mining Method (Case Study: Faculty of Management and Industrial Engineering, Shahrood University of Technology)

نویسندگان [English]

  • Ali Akbar Hasani 1
  • Morteza Bazrafshan 2
1 Assistant Professor, Faculty of Industrial Engineering and Management, Shahroud University of Technology.
2 Assistant Professor, Faculty of Industrial Engineering, Lahijan Azad University
چکیده [English]

Knowledge acquisition about the behavior patterns of the educational status of students can have a significant impact on the successful management of educational institutes and provides appropriate services in accordance with current and future status of students. This knowledge is hidden in educational data and could be extracted via using data mining method. In this paper, a data mining model to analyze students’ academic achievement based on the data related to before and after the students’ entrance to university was proposed. To tackle this problem, an advanced hierarchical clustering method was developed. In addition, a forecasting model to determine the belonging of each student to the each considered cluster was provided. The proposed model was evaluated on a case study of the Faculty of Management in Shahrood University of Technology. The obtained results were validated by experts and university administrators. The students were classified in different clusters via considering theirs specific features. The results indicated that some of the considered features related to before and after entering university have significant impacts on determining the students’ educational achievements and also their assigned cluster. Some decision rules are proposed for educational administrators to improve the overall students’ educational achievements and transferring students from clusters with poor academic situations to better ones such as applied rules for transferring students with special status. In addition, an efficient forecasting model for assessment of students' achievement states was proposed. The obtained results were verified by experts.
 

کلیدواژه‌ها [English]

  • educational achievement
  • educational data mining
  • forecasting model
  • advanced hierarchical clustering
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