Learning Approach as Predictor of Students' Epistemological Development in the Framework of Self-Authorship Theory
Author(s) -
Haykal Hafizul Arifin,
Hamdi Muluk
Publication year - 2017
Publication title -
makara human behavior studies in asia
Language(s) - English
Resource type - Journals
eISSN - 2406-9183
pISSN - 2355-794X
DOI - 10.7454/mssh.v21i1.3500
Subject(s) - construct (python library) , psychology , learning to learn , independence (probability theory) , epistemology , style (visual arts) , cognition , mathematics education , computer science , philosophy , statistics , mathematics , archaeology , neuroscience , history , programming language
Past studies have found that an individual's epistemological development is predicted from learning that is meaningful to the learner. The current research aims to address whether deep learning style is able to predict students' epistemological ability (self-authorship, which is defined as the internal capacity to construct and evaluate knowledge claims, to comprehend the nature of contextual knowledge, and to have independence in the acquisition of knowledge). The researchers hypothesized that the deeper the learning approaches adopted by students, the higher their self-authorship. Conversely, the more students utilize a surface approach to learning, the lower their self-authorship. A total of 346 students enrolled in a university in Indonesia participated in the study. The results showed support for both hypotheses, and we discussed the role of cognitive dispositions in the development of epistemological ability.
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