Extending Introductory Computer Science with Algorithmic Multimedia

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Multimedia and hypermedia have brought many people to computing, and have shown them that computers are easy to use. At the same time, many students report that they no longer find the topics in introductory Computer Science courses interesting or pertinent. By using multimedia-based examples in our introductory courses, we can continue to emphasize algorithms while making them more interesting to a wider variety of students. This is particularly true for students from outside the sciences who are frequently daunted by the scientific and text-processing examples that still dominate many introductory courses and texts. Many important algorithms and problems can be represented in terms of multimedia data. Rather than asking students to find the average element of an array, we could instead ask them how to blur or smudge part of an image. Rather than asking students to develop graph-reachability algorithms, we could instead ask them how to identify orphan nodes in a hypertext system. We can also use multimedia to introduce key concepts. For example, mapping might be introduced by relating image-based functions and video operations (as many video operations are the result of mapping an image-based function on a sequence of images). Drawing upon our experience in multimedia research (Rebelsky) and improving CS pedagogy (Walker, Stone, Rebelsky), we will develop multimedia-based exercises and supporting libraries for four introductory courses. This project requires (1) a small (four-workstation) Macintosh-based multimedia installation, (2) modern projection equipment for our computing classroom and laboratory, and (3) upgrades to our laboratory and classroom workstations to support multimedia computing. With this equipment, we will not only enhance the undergraduate learning experience at Grinnell and make our introductory courses more widely accessible, but also provide a national model of algorithmic multimedia in introductory computer science.