Adaptation to Online Education: An Educational Data Mining Application

Author:

HARK Cengiz1,OKUMUŞ Hatice2,UÇKAN Taner3ORCID

Affiliation:

1. İNÖNÜ ÜNİVERSİTESİ

2. Malatya Yeşilyurt Bostanbaşı İlkokulu

3. VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ

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.

Publisher

Anatolian Science - Bilgisayar Bilimleri Dergisi

Reference18 articles.

1. N. H. SÖYLEMEZ, “BİLGİSAYAR DESTEKLİ VE BİLGİSAYAR TEMELLİ ÖĞRETİM YÖNTEMLERİNİN AKADEMİK BAŞARI VE KALICILIĞA ETKİSİ,” Elektron. Eğitim Bilim. Derg., vol. 2, no. 3, Mar. 2013, Accessed: Oct. 17, 2022. [Online]. Available: https://dergipark.org.tr/tr/pub/ejedus/issue/15937/167581

2. M. Aksarayli, D. İibf, and İ. / Türkiye, “Uzaktan Eğitimi Tercih Etme Nedenleri ve Başarı Arasındaki İlişkinin Kümeleme Analizi İle İncelenmesi,” West. Anatolia J. Educ. Sci., vol. 8, no. 2, pp. 37–48, Dec. 2017, Accessed: Oct. 14, 2022. [Online]. Available: https://dergipark.org.tr/en/pub/baebd/issue/33149/350179

3. S. G. TELLİ and D. ALTUN, “Coronavirüs ve Çevrimiçi (Online) Eğitimin Önlenemeyen Yükselişi,” Üniversite Araştırmaları Derg., vol. 3, no. 1, pp. 25–34, Apr. 2020, doi: 10.32329/uad.711110.

4. R. S. Baker, “Educational data mining: An advance for intelligent systems in education,” IEEE Intell. Syst., vol. 29, no. 3, pp. 78–82, 2014, doi: 10.1109/MIS.2014.42.

5. C. Hark, “Öğrencilerin Akıllı Tahtaya İlişkin Tutumlarının İncelenmesine Yönelik Bir Veri Madenciliği Uygulaması. Fırat Üniversitesi Eğitim Bilimleri Enstitüsü, Yüksek Lisans Tezi,” Fırat Üniversitesi, 2013.

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