Variables Explaining the Online Learning Readiness Level of Students: Turkish Vocational College Example
Yazarlar (3)
Prof. Dr. Gülşah BAŞOL
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Türkiye
Dr. Öğr. Üyesi Tuğba KOCADAĞ ÜNVER
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü | Özgün Makale |
| Makale Alt Türü | Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale |
| Dergi Adı | European Journal of Education Studies |
| Dergi ISSN | 2501-1111 |
| Dergi Tarandığı Indeksler | ERIC |
| Makale Dili | İngilizce |
| Basım Tarihi | 06-2018 |
| Cilt No | 4 |
| Sayı | 10 |
| Sayfalar | 14 / 32 |
| DOI Numarası | 10.5281/zenodo.1302956 |
| Makale Linki | https://oapub.org/edu/index.php/ejes/article/view/1786/4426 |
| Özet |
| The purpose of the study was to investigate the relative importance of previous web-based course familiarity, computer ownership, computer use (years), amount of time spent on a computer (hours/day), social media use (Facebook), e-mail checking frequency, and smartphone use on online readiness of students. These are often provided as selective demographic characteristics in online learning readiness literature, yet their relative importance on online readiness has not been studied. The study was conducted on 633 male military vocational college students, involved in an online teaching environment. Online Learning Readiness Scale and a detailed information sheet were used for data collection purposes. The data were analyzed through a hierarchical linear regression analysis in four steps. According to results, nearly 17% of the variation in students’ online learning readiness levels was explained by the predictor variables. First, as pre-entry characteristics, previous web-based course familiarity, computer ownership, texting and Internet use by a mobile phone explained 8%. In the second order, variables referring further engagement behaviors with technology, computer use in years and the amount of time spent on a computer (hours/day) explained an extra 4.5%. Third, the variables, corresponding to regular/habitual use, Facebook use and e-mail checking frequency, explained another 4.5%. The results indicated that previous web-based course familiarity, the computer use (years) and e-mail checking frequency were the significant variables, predicting students' readiness to online learning. |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 24 |