Expanding Computational Thinking Across Disciplines In Higher Education
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The expansion of information technology has been accompanied with growing uneasiness. As computers and code become more foundational to virtually every sector of the economy, the wide divide between the lay person and the tech guru becomes more worrisome. Accordingly, leaders have begun to call for an overhaul of the education system – we need to prepare for the economy of the future. For many high-profile advocates of this change, the solution is to push for universal programming knowledge. Increasingly, however, researchers have seen greater potential in preparing people for a world dominated by information technology by starting with fundamental concepts, rather than the hard technical skills. In 2006, Jeannette Wing popularized the term for this approach: Computational Thinking. According to Wing, “Computational Thinking is the thought processes involved in formulating a problem and expressing its solution in a way that a computer – human or machine – can effectively carry out,” (Wing 2012, p. 7). Wing and others have since worked to concretize this concept with further definitions, examples, and categories. Efforts to integrate computational thinking into education more generally have produced new courses, university programs, and literature over the results. These efforts have not, however, been without problems, and it becomes clear from a survey of the state of the field that current conceptual understandings, categorizations, and studies of education based on computational thinking leaves much to be desired. This thesis investigates these problems and seeks to expose and partially mitigate these issues by developing a firmer understanding of computational thinking and critically analyze many of the efforts so far.