TY - GEN
T1 - Enhancement of learning experience using skill-challenge balancing approach
AU - Katuk, Norliza
AU - Wang, Ruili
AU - Ryu, Hokyoung
PY - 2011
Y1 - 2011
N2 - This paper addresses the issue of content sequencing in computer-based learning (CBL). In doing so, it proposes a Skill-Challenge Balancing (SCB) approach as a way to enhance the CBL experience. The approach is based on the Flow Theory, allowing self-adjustment of the given levels of challenges in a given learning tasks so that the learner will consistently be adaptively able to engage in the CBL activity. An empirical study with 70 students suggested that the SCB-based learners were significantly better in their learning experience specifically in their focus of attention and intrinsic interests compared to the learners in the system without SCB. The results also revealed that SCB was fully utilised by the learners to regulate the levels of difficulty of the CBL tasks.
AB - This paper addresses the issue of content sequencing in computer-based learning (CBL). In doing so, it proposes a Skill-Challenge Balancing (SCB) approach as a way to enhance the CBL experience. The approach is based on the Flow Theory, allowing self-adjustment of the given levels of challenges in a given learning tasks so that the learner will consistently be adaptively able to engage in the CBL activity. An empirical study with 70 students suggested that the SCB-based learners were significantly better in their learning experience specifically in their focus of attention and intrinsic interests compared to the learners in the system without SCB. The results also revealed that SCB was fully utilised by the learners to regulate the levels of difficulty of the CBL tasks.
KW - computer-based learning
KW - Flow theory
KW - learning experience
KW - skill-challenge balancing
UR - http://www.scopus.com/inward/record.url?scp=83755173657&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-25832-9_72
DO - 10.1007/978-3-642-25832-9_72
M3 - Conference contribution
AN - SCOPUS:83755173657
SN - 9783642258312
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 707
EP - 716
BT - AI 2011
T2 - 24th Australasian Joint Conference on Artificial Intelligence, AI 2011
Y2 - 5 December 2011 through 8 December 2011
ER -