Metrics to facilitate automated categorization of student learning patterns while using educational engineering software

• Autores: Linda Stern, Colin Burvill, John Weir, Bruce Field
• Localización: The International journal of engineering education, ISSN-e 0949-149X, Vol. 32, no. 5 (Parte A), 2016, 1902 págs.
• Idioma: inglés
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• Resumen

  • In this paper we describe the use of metrics for analysing student interactions with educational software. We applied thismetric-based approach to a class of 200 second-year undergraduate students using an educationally-oriented softwaresimulator to solve specific problems in mechanical engineering design. Our results show that a metric can facilitatecategorization of student learning patterns. We suggest how similar metrics could allow automated feedback on learning toboth students and educators. Since it is based on numerical analysis and modelling, our approach is particularly well-suitedto software used to support teaching and learning in engineering and other mathematically-based disciplines.