Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy

The present study aims to show if a skill-challenge balancing (SCB) instruction strategy can assist learners to motivation-ally engage in computer-based learning. Csikszentmihalyi's flow theory (self-control, curiosity, focus of attention, and intrinsic interest) was applied to an account of th...

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Main Authors: Kim, Jieun, Ryu, Hokyoung, Katuk, Norliza, Wang, Ruili, Choi, Gyunghyun
Format: Article
Language:English
Published: SAGE Publications 2014
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/17173/1/4.pdf
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author Kim, Jieun
Ryu, Hokyoung
Katuk, Norliza
Wang, Ruili
Choi, Gyunghyun
author_facet Kim, Jieun
Ryu, Hokyoung
Katuk, Norliza
Wang, Ruili
Choi, Gyunghyun
author_sort Kim, Jieun
collection UUM
description The present study aims to show if a skill-challenge balancing (SCB) instruction strategy can assist learners to motivation-ally engage in computer-based learning. Csikszentmihalyi's flow theory (self-control, curiosity, focus of attention, and intrinsic interest) was applied to an account of the optimal learning experience in SCB-based learning activities. Two empirical studies were carried out, where a group of learners were taught “Computer Networks” as part of a statutory curriculum at a tertiary institution. The empirical results suggested that a degree of self-control to compensate for the fully automatic SCB instruction strategy (i.e., competence and autonomy) would be of a greater value for learning motivation enhancement in adaptive computer-based learning systems.
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spelling uum-171732016-05-19T02:13:35Z https://repo.uum.edu.my/id/eprint/17173/ Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy Kim, Jieun Ryu, Hokyoung Katuk, Norliza Wang, Ruili Choi, Gyunghyun QA75 Electronic computers. Computer science The present study aims to show if a skill-challenge balancing (SCB) instruction strategy can assist learners to motivation-ally engage in computer-based learning. Csikszentmihalyi's flow theory (self-control, curiosity, focus of attention, and intrinsic interest) was applied to an account of the optimal learning experience in SCB-based learning activities. Two empirical studies were carried out, where a group of learners were taught “Computer Networks” as part of a statutory curriculum at a tertiary institution. The empirical results suggested that a degree of self-control to compensate for the fully automatic SCB instruction strategy (i.e., competence and autonomy) would be of a greater value for learning motivation enhancement in adaptive computer-based learning systems. SAGE Publications 2014 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/17173/1/4.pdf Kim, Jieun and Ryu, Hokyoung and Katuk, Norliza and Wang, Ruili and Choi, Gyunghyun (2014) Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy. Journal of Educational Computing Research, 50 (1). pp. 1-28. ISSN 0735-6331 http://doi.org/10.2190/EC.50.1.a doi:10.2190/EC.50.1.a doi:10.2190/EC.50.1.a
spellingShingle QA75 Electronic computers. Computer science
Kim, Jieun
Ryu, Hokyoung
Katuk, Norliza
Wang, Ruili
Choi, Gyunghyun
Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy
title Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy
title_full Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy
title_fullStr Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy
title_full_unstemmed Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy
title_short Enhancing competence and autonomy in computer-based instruction using a skill-challenge balancing strategy
title_sort enhancing competence and autonomy in computer based instruction using a skill challenge balancing strategy
topic QA75 Electronic computers. Computer science
url https://repo.uum.edu.my/id/eprint/17173/1/4.pdf
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