Validating proficiency-mining strategy in adaptive learning environment Online publication date: Sun, 28-Nov-2004
by Peng-Wen Chen, Yuh-Huei Shyu
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 14, No. 4/5, 2004
Abstract: The strategies of detecting learning state and generating relative adaptation link affect the success of adaptive navigation. Proficiency is a classic indicator in testing the learning state of programming. Similar to data mining, proficiency mining is added in the learning process to explore each learner's proficiency from observable behaviour. This paper presents a web-based learning system (NMPTE) embedded with a proficiency-mining strategy that is used for supporting adaptive navigation. The strategy involves using selected parameters to characterise the process of coding rehearsal. The criteria of selecting parameters are based on the psychology researches and the basic properties of learning to program. Web technologies with the standard of XML are adopted to describe adaptive curricula and proficiency parameters. Our experience demonstrates that proficiency mining shows sufficient evidence to represent programming performance and becomes a tool to detect users' features in adaptation system.
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