Development of Medical School Students’ Attitudes towards Online Learning Scale and Its Relationship with e-Learning Styles


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Yurdal M. O., Şahin E. M., Aytuğ Koşan A. M., Toraman Ç.

Turkish Online Journal of Distance Education, cilt.22, sa.4, ss.310-325, 2021 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 4
  • Basım Tarihi: 2021
  • Doi Numarası: 10.17718/tojde.961855
  • Dergi Adı: Turkish Online Journal of Distance Education
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, EBSCO Education Source, ERIC (Education Resources Information Center), Index Islamicus, Directory of Open Access Journals
  • Sayfa Sayıları: ss.310-325
  • Anahtar Kelimeler: Faculty of Medicine, online learning, e-learning style, attitude
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

This study aims at determining students’ attitudes towards distance education/online learning through a scale developed by the authors and determine the relationship between these attitudes and e-learning styles. The study carried out on students of Canakkale Onsekiz Mart University Faculty of Medicine using the online system of the university., the sample group consists 815 students from different classes, the participation rate was 89.46%. Following the explanatory factor and confirmatory factor analysis resulting structure of the scale was confirmed. Construct validity, criterion validity and internal consistency of the scale were high. Multivariate regression analysis was conducted to assess the predictive strength of the students’ learning styles which were determined using the e-Learning Styles Scale for Electronic Environments for the attitudes towards online learning. Presented Medical School Students’ Attitudes Towards Online Learning Scale was valid and reliable instrument to measure medical school students’ attitudes towards distance/online learning. Although students’ attitudes toward online/distant education were divided, it was negative on the average. The regression modeling showed that the learning styles are significant predictors for attitudes towards online education and the audio-visual learning style was determined as has the highest predictive strength for attitudes towards online education. The developed tool can be used to monitor medical school students’ attitudes towards distance/online learning and will contribute to preparing medical education for a change towards distance learning.