Predicting student enrolments and attrition patterns in higher educational institutions using machine learning

المؤلفون المشاركون

Shilbayeh, Samar
Abu Namah, Abd Allah

المصدر

The International Arab Journal of Information Technology

العدد

المجلد 18، العدد 4 (31 يوليو/تموز 2021)، ص ص. 562-567، 6ص.

الناشر

جامعة الزرقاء عمادة البحث العلمي

تاريخ النشر

2021-07-31

دولة النشر

الأردن

عدد الصفحات

6

التخصصات الرئيسية

العلوم التربوية

الملخص EN

In higher educational institutions, student enrollment management and increasing student retention are fundamental performance metrics to academic and financial sustainability.

In many educational institutions, high student attrition rates are due to a variety of circumstances, including demographic and personal factors such as age, gender, academic background, financial abilities, and academic degree of choice.

In this study, we will make use of machine learning approaches to develop prediction models that can predict student enrollment behavior and the students who have a high risk of dropping out.

This can help higher education institutions develop proper intervention plans to reduce attrition rates and increase the probability of student academic success.

In this study, real data is taken from Abu Dhabi School of Management (ADSM) in the UAE.

This data is used in developing the student enrollment model and identifying the student’s characteristics who are willing to enroll in a specific program, in addition to that, this research managed to find out the characteristics of the students who are under the risk of dropout.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Shilbayeh, Samar& Abu Namah, Abd Allah. 2021. Predicting student enrolments and attrition patterns in higher educational institutions using machine learning. The International Arab Journal of Information Technology،Vol. 18, no. 4, pp.562-567.
https://search.emarefa.net/detail/BIM-1434339

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Shilbayeh, Samar& Abu Namah, Abd Allah. Predicting student enrolments and attrition patterns in higher educational institutions using machine learning. The International Arab Journal of Information Technology Vol. 18, no. 4 (Jul. 2021), pp.562-567.
https://search.emarefa.net/detail/BIM-1434339

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Shilbayeh, Samar& Abu Namah, Abd Allah. Predicting student enrolments and attrition patterns in higher educational institutions using machine learning. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 4, pp.562-567.
https://search.emarefa.net/detail/BIM-1434339

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 566

رقم السجل

BIM-1434339