healthrealtikaphi.gq/the-alien-inside-in-1977-we-sent.php However, most computer-based learning environments use heuristics or rely on the discretion of students when they determine whether instructional scaffolding needs be provided. The predictive model of problem solving performance of students can be used as a quantitative guideline that can help make a better decision on when to provide instructional supports and guidance in the computer-based learning environment, which can potentially maximize the learning outcome of students.
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Visit emeraldpublishing. Abstract Purpose The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment.
Findings The regularized logistic regression model showed a better predictive power than the standard Bayesian Knowledge Tracing model, the most frequently used quantitative model of student learning in the Educational Data Mining research. Please note you might not have access to this content. You may be able to access this content by login via Shibboleth, Open Athens or with your Emerald account.
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Most would agree that the acquisition of problem-solving ability is a primary goal of education. The emergence of the new information technologiesin the last ten. We have also focused on the acquisition of problem-solving skills and framework for the design of computer-based learning environments.
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