Başaran Bülent, Yalman Murat
Ziya Gökalp Education Faculty, Instructional Technologies, Dicle University, Diyarbakir, Turkey.
Educ Inf Technol (Dordr). 2022;27(6):7471-7490. doi: 10.1007/s10639-022-10910-2. Epub 2022 Feb 10.
In the study, latent class analysis (LCA) was used to determine the unobserved structures and the subpopulations of pre-service teachers' technology-based learning behaviours. According to LCA results, three latent classes were obtained. These classes are labelled as Class-1: "High-Level Technology Perception", Class-2: "Low-Level Technology Perception", Class-3: "Intermediate-Level Technology Perception". When Class-1(Reference Group) and Class-2 were compared, it was observed that the covariates of "gender" and "the Covid-19 pandemic affecting learning motivation" did not have a significant effect on Class-2. It has been determined that pre-service teachers who are older, studying in the 4th grade, using the Internet for more than 8 h a day, have advanced computer skills and have advanced technology-based learning experience are less likely to be in Class-2. In addition, in the study, while self-directed learning with technology was associated with pre-service teachers' attitudes towards online teaching in the Covid-19 period and class membership, the fear of Covid-19 was not associated with latent class membership.
在该研究中,潜在类别分析(LCA)被用于确定职前教师基于技术的学习行为的未观察到的结构和亚群体。根据潜在类别分析结果,得到了三个潜在类别。这些类别被标记为:类别1:“高水平技术认知”,类别2:“低水平技术认知”,类别3:“中等水平技术认知”。当将类别1(参考组)与类别2进行比较时,发现“性别”和“影响学习动机的新冠疫情”这些协变量对类别2没有显著影响。已确定年龄较大、在四年级学习、每天使用互联网超过8小时、具备高级计算机技能且有基于技术的高级学习经验的职前教师不太可能属于类别2。此外,在该研究中,虽然利用技术进行自主学习与职前教师在新冠疫情期间对在线教学的态度及类别归属相关,但对新冠疫情的恐惧与潜在类别归属无关。