Modeling long term learning of generic skills

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Abstract

Many of the most important learning goals can only be achieved over several years. Our CUSP system helps achieve this over the 3-to-5 years of a university degree: it enables each teacher to map their own subject design to institutional learning goals; it creates both subject and degree-level models. It tackles the semantic mapping challenges using a highly flexible lightweight approach. We report its validation for 102 degrees and 1237 subject sessions. CUSP makes a contribution to understanding how to model long term learning of generic skills, using a lightweight semantic mapping based on multiple sets of externally defined learning goals. The work contributes to understanding of how to create comprehensive models of long term learning within degrees that are practical in real environments. © Springer-Verlag Berlin Heidelberg 2010.

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Gluga, R., Kay, J., & Lever, T. (2010). Modeling long term learning of generic skills. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6094 LNCS, pp. 85–94). https://doi.org/10.1007/978-3-642-13388-6_13

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