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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/1212

Title: Personal Recommender Simulation
Authors: Van den Berg, Bert
Nadolski, Rob
Drachsler, Hendrik
Berlanga, Adriana
Hummel, Hans
Koper, Rob
Sloep, Peter
Keywords: simulation
recommender strategies
collaborative filtering
rating
Issue Date: 22-Mar-2008
Abstract: The main goal of our project is to research and develop technologies that support users in Learning Networks. One of the questions in this research is how to tackle the problem of the difficulty for learners to navigate through the network: what is the most effective way to reach the learning target or which course can be studied best after finishing a particular one? The aim of this program is to simulate recommendations (strategies) of learning actions (LA's) for learners in a learning network with different (sub) domains, targets, preferences and competences. It is used to explore and to research the effectiveness of different recommendation strategies in various settings.
Description: The simulation and its background is described in detail in: Simulating [in the search] for lightweight Personalised Recommendation Systems in Learning Networks: A case for Pedagogy-Oriented Rating-based Hybrid Recommendation Strategies Rob J. Nadolski, Bert van den Berg, Adriana J. Berlanga, Hendrik Drachsler, Hans G.K. Hummel, Rob Koper and Peter B. Sloep. Open University of the Netherlands. Available under the three clause BSD licence, Copyright TENCompetence Foundation.
URI: http://hdl.handle.net/1820/1212
Appears in Collections:4. LN: Software and Documentation
Keur der Wetenschap
4. TENC: Software and Documentation

Files in This Item:

File Description SizeFormat
statistic files.zipExperimental data files used for analysis7.74 MBzipView/Open
prs.nlogoPRS simulation in Netlogo 4.0.288.5 kBNETLOGO 4.0.2View/Open
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