Regardless of the course topic, every instructor in a computing field endeavors to engage their students in deep problem-solving and critical thinking. One of the specific learning outcomes throughout our computer science curriculum is the development of independent, capable problem solving -And we believe good pedagogy can bring such about. Our experiences indicate to us that students improve their ability to analyze and solve complex computational problems when we pursue pedagogies that support them in developing these skills incrementally. Specifically, we pursue a problem-based learning approach that we apply individually in each course as well as across the entire curriculum of our department, instead of solely considering our pedagogy on a course-by-course basis.

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This dissertation examines the roles of learning styles and teaching methodologies within a data mining educational program designed for non-Computer Science undergraduate college students. The experimental design is framed by a discussion of the history and development of data mining and education, as well as a vision for its future.