Abstract
Smart learning environments are technology-enhanced educational systems that not only support learners’ learning but also provide a learning environment to learners according to their learning needs. In our previous research, we proposed a rule-based recommender system that supports learners in a learner-centered approach (Imran et al. A rule-based recommender system to suggest learning tasks. Springer, Honolulu, 2014). In this chapter, we introduce a visualization and analytical tool for rule-based recommender system (VAT-RUBARS) to provide support to teachers in learner-centered courses. As a result, teachers no longer need to make assumptions about their learners (or courses) and can improve the learning environment to make it more smart and productive for their learners.
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Acknowledgments
The authors acknowledge the support of Mitacs, NSERC, iCORE, Xerox, Athabasca University and the research related gift funding by Mr. A. Markin.
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Imran, H., Ballance, K., Da Silva, J.M.C., Kinshuk, Graf, S. (2016). VAT-RUBARS: A Visualization and Analytical Tool for a Rule-Based Recommender System to Support Teachers in a Learner-Centered Learning Approach. In: Li, Y., et al. State-of-the-Art and Future Directions of Smart Learning. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-287-868-7_4
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DOI: https://doi.org/10.1007/978-981-287-868-7_4
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