Evaluate the Correlation Between Online Learning Motivation and Learning Effectiveness for Students Enrolled at the Taiwan Institute of Technology (68541)

Session Information:

Friday, 26 May 2023 15:15
Session: Poster
Room: Room 701
Presentation Type:Poster Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

During the COVID-19 pandemic, following the policy of “Learning Never Stops”, schools of all levels in Taiwan adopted a flexible and interdisciplinary approach to maintain educational continuity, and online teaching became one of the main methods of achieving this goal. Our research used the ARCS model to evaluate any correlation between online learning motivation and the learning performance of students enrolled at the Taiwan Institute of Technology during the pandemic. Our objectives are: (1) to evaluate the level of online learning motivation of students enrolled at the Taiwan Institute of Technology during the pandemic; (2) to evaluate the online learning effectiveness of the students enrolled at the Taiwan Institute of Technology during the pandemic; (3) evaluate the correlation between online learning motivation and learning effectiveness for the students enrolled at the Taiwan Institute of Technology during the pandemic. The subjects are all students enrolled at an Institute of Technology in Taiwan. A research instrument was developed using the ARCS model of Motivation, coupled with a literature review. The study was conducted via questionnaire investigation. After the collection and analysis of the data, our conclusions were: (1) the students’ level of online learning motivation was average; (2) online learning was effective in the case of these students; (3) there is a correlation between the online learning motivation and the performance of the students who took part in this study.

Authors:
Shin Liao, National Taiwan Normal University, Taiwan
Chao-Fu Yang, Shu-Te University, Taiwan
Wei-Cheng Lo, National Taiwan Normal University, Taiwan


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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00