Pre-service teachers’ readiness and engagement for online learning during the covid-19 pandemic: A rasch analysis
Document Type
Article
Publication Date
1-1-2022
Abstract
The widespread of the COVID-19 pandemic has challenged training institutions to rethink the execution of their training programs. New approaches to teaching and learning are now needed due to the forced shift to e-learning modes. However, questions remain about how ready pre-service teachers are and their level of engagement in an online learning model of instruction. The purpose of this study was to investigate the readiness and engagement of pre-service teachers for online learning in Indonesia. This study used a non-experimental quantitative research design. Data were gathered from a sample of 285 pre-service teachers using a questionnaire. Data were analysed using WINSTEPS Rasch model measurement software version 4.30. Descriptive statistical analysis was used to examine pre-service teachers’ readiness and engagement of pre-service teachers for an online learning model of instruction, and a Differential Item Functioning (DIF) analysis was carried out to specifically assess their readiness and engagement for online learning based on their gender and age. Findings indicate pre-service teachers were not ready for online learning during the Covid-19 Pandemic in Indonesia. However, pre-service teachers were found to be actively engaged in online learning. Further analysis indicated there were differences in pre-service teachers’ readiness and engagement in online learning based on their gender and age. This study provides insight into pre-service teachers towards an online learning model of instruction in Indonesia, discusses implications, and offers recommendations for future research. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
Engagement, Online learning, Pre-service teachers, Rasch model, Readiness
Divisions
Education
Funders
None
Publication Title
Lecture Notes in Networks and Systems
Volume
299
Publisher
Springer Science and Business Media Deutschland GmbH
Additional Information
Cited by: 2; Conference name: International Conference on Emerging Technologies and Intelligent Systems, ICETIS 2021; Conference date: 25 June 2021 through 26 June 2021; Conference code: 263669