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Analyzing the factors that influence enhancing student performance in Oman using data mining
المؤلفون المشاركون
al-Rashidi, Said Muhammad
Zaki, Akram
المصدر
Journal of Science and Technology
العدد
المجلد 27، العدد 1 (30 يونيو/حزيران 2022)، ص ص. 1-14، 14ص.
الناشر
جامعة العلوم و التكنولوجيا كلية الهندسة و الحاسبات
تاريخ النشر
2022-06-30
دولة النشر
اليمن
عدد الصفحات
14
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Education field is a sign of advancement over the countries that can adopt technology to serve it.
It will help to improve and enhance future achievements and be in touch with the development of technology utilizing solutions that extract student data, including their school records and other vital information about their performance, which can facilitate this process.
These data are then analyzed to identify factors that affect the academic performance of the students at the school by expanding data mining techniques to enhance student academic performance.
These factors are examined to develop a predictive model.
Machine learning (ML) is one artificial intelligence (AI) field that can use such a model that supports educational institutions and decision-makers.
A predictive method is applied using the data mining (DM) technique to take proactive action in identifying and anticipating the student's path.
The data was analyzed, and the findings showed that the decision tree algorithm recorded the fastest training time for every 1000 rows.
Also, the fast-scoring time for 1000 rows was in the decision tree algorithm, which was around 195 milliseconds, and the longest scoring time occurred in the random forest algorithm, which was two seconds.
The top percent of classification errors reached 51% for the logistic regression algorithm and around +-1.5% of standard deviation.
It took 520 mile-second for scoring time with 690 Gains for 67 m/s training time in every 1000 rows of the datasets.
The findings of this study can help parents and teachers better understand the factors that influence students' academic performance and support them in assisting students with improving their academic performance.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
al-Rashidi, Said Muhammad& Zaki, Akram. 2022. Analyzing the factors that influence enhancing student performance in Oman using data mining. Journal of Science and Technology،Vol. 27, no. 1, pp.1-14.
https://search.emarefa.net/detail/BIM-1501493
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
al-Rashidi, Said Muhammad& Zaki, Akram. Analyzing the factors that influence enhancing student performance in Oman using data mining. Journal of Science and Technology Vol. 27, no. 1 (2022), pp.1-14.
https://search.emarefa.net/detail/BIM-1501493
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
al-Rashidi, Said Muhammad& Zaki, Akram. Analyzing the factors that influence enhancing student performance in Oman using data mining. Journal of Science and Technology. 2022. Vol. 27, no. 1, pp.1-14.
https://search.emarefa.net/detail/BIM-1501493
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 14
رقم السجل
BIM-1501493
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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