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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
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
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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