Abstract
The paper presents an recommender engine, embedded in the feedback module of an e-assessment platform for project management. The objective of this engine is to provide links to the web pages connected with the identified knowledge gaps of the students making the assessments. An ontology-based clustering algorithm is used to generate these recommendations. The authors argue that using a recommender engine the formative value of the e-assessment will increase, the students having the opportunity to take control of their own learning and actively participate in the learning process. The evaluation of the utility of the recommendations is also provided.
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Bodea, CN., Dascalu, MI., Lytras, M.D. (2013). Advanced Personalized Feedback in e-Assessment Systems with Recommender Engine. In: Lytras, M.D., Ruan, D., Tennyson, R.D., Ordonez De Pablos, P., GarcÃa Peñalvo, F.J., Rusu, L. (eds) Information Systems, E-learning, and Knowledge Management Research. WSKS 2011. Communications in Computer and Information Science, vol 278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35879-1_22
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DOI: https://doi.org/10.1007/978-3-642-35879-1_22
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