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

Adaptation to Online Education: An Educational Data Mining Application

Pages
95–102
Publication Date
2022-12-07
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

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:Research Article
📍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://ajindex.com/articles/867456

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (4)

  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 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. 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. C. Hark, “Öğrencilerin Akıllı Tahtaya İlişkin Tutumlarının İncelenmesine Yönelik Bir Veri Madenciliği Uygulaması. Fırat Üniversitesi Eğitim Bilimleri Enstitüsü, Yüksek Lisans Tezi,” Fırat Üniversitesi, 2013.
  3. T. UÇKAN, C. HARK, and A. KARCI, “Fp Growth Algoritması Ve Big Data Uygulamaları,” in IDAP 2016 - International Artificial Intelligence and Data Processing Symposium, 2016, pp. 338–341.
  4. G. ÇETİNTAV, B. D. ÇİL, and R. YILMAZ, “EĞİTSEL VERİ MADENCİLİĞİ VE ÖĞRENME ANALİTİKLERİ ARAŞTIRMALARINDA VERİ GİZLİLİĞİ VE ETİK MESELELER: ARAŞTIRMALAR ÜZERİNE BİR İNCELEME,” Eğitim Teknol. Kuram ve Uygul., vol. 12, no. 1, pp. 113–146, Jan. 2022, doi: 10.17943/ETKU.950392. Maciej Serda et al., “Çevrimiçi Öğrenme Ortamındaki Etkileşim Verilerine Göre Öğrencilerin Akademik Performanslarının Veri Madenciliği Yaklaşımı İle Modellenmesi,” Uniw. śląski, vol. 7, no. 1, pp. 343–354, 2014, doi: 10.2/JQUERY.MIN.JS. C. HARK, T. UÇKAN, and A. KARCI, “15 Temmuz Şehitler Köprüsü Kapsamında Hava Yol Durum Bilgileri Kullanılarak Trafik Kazalarının Nedenlerine Yönelik Birliktelik Çıkarımı,” in IDAP 2016 - International Artificial Intelligence and Data Processing Symposium, 2016, pp. 347–351. C. W. Liao and Y. H. Perng, “Data mining for occupational injuries in the Taiwan construction industry,” Saf. Sci., vol. 46, no. 7, pp. 1091–1102, Aug. 2008, doi: 10.1016/J.SSCI.2007.04.007. G. Mühendislik et al., “TRAFİK KAZALARININ BİRLİKTELİK KURALLARI İLE ANALİZİ,” Gazi J. Eng. Sci., vol. 1, no. 2, pp. 265–283, Jun. 2015, Accessed: Oct. 20, 2022. [Online]. Av