ABSTRACT
This paper describes the design and initial assessment of a general education course in computational thinking for non-computer science majors. The key elements of the course include multidisciplinary cohorts to achieve learning across contexts, multiple languages/tools, including block-based and textual programming languages, repeated exposure to the underlying computational ideas in different forms, and student-defined projects using real world ("big") data to heighten motivation through self-directed contextualized learning. The preliminary multi-methods assessment shows that the course engendered high levels of motivation, achieved key objectives for learning in and across contexts, largely affirmed the choice of languages/tools, and supported, though less strongly than anticipated, the motivational effects of real-world data
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Index Terms
- Design and Preliminary Results From a Computational Thinking Course
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