Abstract
Our paper looks into the possibility of creating an Optimizer agent that can help a ITS System modify its teaching strategies in dealing with each individual student, so that the most efficient learning is achieved. Firstly, we will explain how the Tutor Systems on its own would work, explaining the problem of creating an effective decision structure in the Tutor and how other people have overcome this problem. Secondly, we introduce the concept of a “real-time” Optimizer and how it would work. Thirdly, we explain the test we will be using in testing this concept of an Optimizer agent. And fourthly and last, we finish with some conclusions resulting from our research.
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Negoita, M.G., Pritchard, D. (2004). An Optimizer Agent that Empowers an ITS System to “on-the-fly” Modify its Teaching Strategies. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_123
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DOI: https://doi.org/10.1007/978-3-540-30132-5_123
Publisher Name: Springer, Berlin, Heidelberg
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