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(2000) Altermatt, Peter; Schumacher, J; Cuevas, A; Glunz, S; King, Ronald; Heiser, Gernot; Schenk, AndreasConference Paper
(2008) Ben-Naim, Dror; Marcus, Nadine; Bain, MichaelConference PaperIn this paper we describe research that applies educational data-visualization and data mining techniques in an Adaptive Exploratory eLearning Environment called the Adaptive eLearning Platform. Using a novel visualization tool called the Solution Trace Graph, we were able to visualize student interactions and thus gain insights that led to the refinement of the intelligently adapted remediation in the system. An important observation we make concerns the employment of a software design methodology which we refer to as Virtual Apparatus Framework (VAF). By using VAF to develop eLearning content, the process of developing intelligently adapted remediation in an exploratory learning scenario, and subsequently the analysis of students? behaviour, is greatly enhanced and simplified.
(2009) Wong, Anna; Marcus, Nadine; Ayres, Paul; Sweller, JohnJournal ArticleBased on the assumption of a working memory processor devoted to human movement, cognitive load theory is used to explore some conditions under which animated instructions are hypothesised to be more effective for learning than equivalent static graphics. Using paper-folding tasks dealing with human movement, results from three experiments confirmed our hypothesis, indicating a superiority of animation over static graphics. These results are discussed in terms of a working memory processor that may be facilitated by our mirror-neuron system and may explain why animated instructional animations are superior to static graphics for cognitively based tasks that involve human movement.