For forty years programming has been the foundation of introductory computer science. Despite exponential increases in computational power during this period, examples used in introductory courses have remained largely unchanged. The incredible growth in statistics courses at all levels, in contrast with the decline of students taking computer science courses, points to the potential for introducing computer science at many levels without emphasizing the process of programming: leverage the expertise and role-models provided by high school mathematics teachers by studying topics that arise from social networks and modeling to introduce computer science as an alternative to the traditional programming approach. This new approach may capture the interest of a broad population of students, crossing gender boundaries. We are developing modules that we hope will capture student interest and provide a compelling yet intellectually rich area of study. We plan to incorporate these modules into existing courses in math, statistics, and computer science at a wide variety of schools at all levels.
Often in teaching an introductory computer science course for non-majors, a primary focus on building programming skills is neither practical nor effective. Many instructors choose a breadth-first approach focusing on building problem solving skills and surveying computer science. This paper argues that conducting hands-on labs where students work together to physically implement algorithms is an effective supplement for programming labs on the computer. We present lab examples and summarize our experiences.
Our field continues to be blessed (and plagued) with continual curriculum change, from languages to techniques (objects first) to perspectives ("sage on the stage" vs. "guide on the side"). Particular emphasis has been spent crafting and re-crafting our introductory curricula [1]. This makes sense, since that not only defines the foundation upon which our upper-division courses are based, but is exactly where we attract (or lose) our best students who had not considered majoring in computer science. With enrollments declining, retaining our fence-sitting prospective majors takes on that much more importance.
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