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- Title
Understanding Students' Intention to Engage in Deep Learning: Application of the Theory of Planned Behaviour.
- Authors
Teh Raihana Nazirah Roslan; Chee Keong Ch'ng; Chuah, Francis
- Abstract
This paper examines students' intention to engage in deep learning with the aim to understand them better. Majority of students practice surface learning approach, defined as having the intention to only meeting the minimum requirements by memorizing important information. Based on the Theory of Planned Behavior, we relate the components of this theory with our main quest of students' intention to engage in deep learning, where the attainable predictors are students' attitude, subjective norm, and perceived behavioral control. Our online survey, which was conducted and analyzed both statistically and descriptively, revealed that our students are deep learners. Our model was also found significant, with all three predictors were positive and significantly contributing to students' intention to engage in deep learning. Nonetheless, detailed analysis suggests that none of the predictors appeared to have a stronger effect over the others. The findings from this study confirm the applicability of the Theory of Planned Behavior in explaining students' intention to engage in deep learning. The findings also provide educators with the required knowledge to better design their curriculum with deep learning approaches.
- Subjects
PLANNED behavior theory; DEEP learning; STUDENT attitudes; INTENTION; THEORY of reasoned action
- Publication
Ilkogretim Online, 2021, Vol 20, Issue 4, p490
- ISSN
1305-3515
- Publication type
Article
- DOI
10.17051/ilkonline.2021.04.54