Social networks generate interest in computer science

  • Authors:

  • Casey Alt;Owen Astrachan;Jeffrey Forbes;Richard Lucic;Susan Rodger

  • Affiliations:

  • Duke University, Durham, NC;Duke University, Durham, NC;Duke University, Durham, NC;Duke University, Durham, NC;Duke University, Durham, NC

  • Venue:
  • Proceedings of the 37th SIGCSE technical symposium on Computer science education
  • Year:
  • 2006

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Abstract

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.