This makes them easier to learn than some other models, and makes them ideally suited to automatic generation using Machine Learning. A Student Model is used in Intelligent Tutoring Systems to guide the pedagogical process. We discuss the student model incorporated in SQL-Tutor, and suggest how it might be extended to include high level knowledge. We evaluate the proposed refinements and discuss strengths and weaknesses of the revised model. Finally, we explore areas for further research.
Database mining uses machine learning techniques to find regularities in databases.
In the absence of any other information, the potential search space is huge, and noise, missing attributes, and irrelevant data are a problem. The search for the best rule set is NP complete, so ML systems adopt heuristics that reduce the search space. Each method is strong for problems where the underlying rules fit the bias, and are weak otherwise. The resulting system classifies most problems as well as or better than both of the traditional approaches mentioned above. Classification time and memory requirements are also significantly reduced compared to standard nearest neighbour.