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Journals / Bilgisayar Bilimleri / 2022 / Cilt: Vol:7 Sayı: Issue:2

Adaptation to Online Education: An Educational Data Mining Application

Cengiz Hark(İNÖNÜ ÜNİVERSİTESİ)0000-0001-5975-5529
Hatice Okumuş(Malatya Yeşilyurt Bostanbaşı İlkokulu)0000-0002-9784-4300
Taner Uçkan(VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ)0000-0001-5385-6775
Pages
95–102
Publication Date
2022-12-07
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It is thought that the study and the reported results will be a guide in creating education plans suitable for the demographic characteristics of the students enrolled in the online education program.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Despite space, time, and financial limitations, people who want to receive education participate intensively in online education programs that have emerged with the development of technology.
📊
Key Findings & Data:With the Covid-19 outbreak, this interest has increased exponentially.
💡
Conclusion & Impact:It is thought that the study and the reported results will be a guide in creating education plans suitable for the demographic characteristics of the students enrolled in the online education program.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Online education · data mining · association rules.

Abstract

Despite space, time, and financial limitations, people who want to receive education participate intensively in online education programs that have emerged with the development of technology. With the Covid-19 outbreak, this interest has increased exponentially. In today's societies, where online education, which is preferred for different reasons, has become essential, examining the factors affecting success in online learning is a very important research topic. The study examined the level of adaptation to online education in terms of demographic variables. Experimental studies and necessary analyzes were carried out on the open-access ‘Students Adaptability Level in Online Education’ dataset. The results obtained using association rules, among the most widely used data mining techniques, have provided remarkable results regarding factors affecting success in distance education. It is thought that the study and the reported results will be a guide in creating education plans suitable for the demographic characteristics of the students enrolled in the online education program.

Özet

Despite space, time, and financial limitations, people who want to receive education participate intensively in online education programs that have emerged with the development of technology. With the Covid-19 outbreak, this interest has increased exponentially. In today's societies, where online education, which is preferred for different reasons, has become essential, examining the factors affecting success in online learning is a very important research topic. The study examined the level of adaptation to online education in terms of demographic variables. Experimental studies and necessary analyzes were carried out on the open-access ‘Students Adaptability Level in Online Education’ dataset. The results obtained using association rules, among the most widely used data mining techniques, have provided remarkable results regarding factors affecting success in distance education. It is thought that the study and the reported results will be a guide in creating education plans suitable for the demographic characteristics of the students enrolled in the online education program.

🔖

Cite This Article

Hark, C., Okumuş, H., Uçkan, T. (2022). Adaptation to Online Education: An Educational Data Mining Application. Bilgisayar Bilimleri, Cilt: Vol:7 Sayı: Issue:2, 95–102. https://doi.org/10.53070/bbd.1199055

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