Long term student learner modeling and curriculum mapping

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Abstract

Over the years of a university degree, students face many challenges, including: selecting elective subjects, gaining a sense of their own progress, understanding the reasons that they are required to do particular learning tasks, and deciding the time to devote to different assignments. These are important for student engagement and success. We aim to create a new way to help students address these challenges, based on a curriculum mapping system. This will aid students making more informed elective decisions based on personalized progress reports and knowledge gap analysis. Our system will capture whole degree programs, mapping the detailed degree requirements (accreditation, learning objectives, attributes) to the individual subjects, the assessments and each student's actual performance on assessment tasks. We will evaluate this in three stages: qualitative studies of students' interaction with the system based on a fictional student's personalized progress report and knowledge gaps; qualitative studies based on actual profiles; and a field trial which tracks interaction and makes use of questionnaires. © 2010 Springer-Verlag.

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Gluga, R. (2010). Long term student learner modeling and curriculum mapping. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6095 LNCS, pp. 227–229). https://doi.org/10.1007/978-3-642-13437-1_27

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