Building a search engine to drive problem-based learning

ABSTRACT

Search engines pervade the digital world, mediating most access to information instantaneously. We have found that students can build search engine components, and even entire search engines, in the context of problem-based learning in introductory and intermediate computer science courses. The courses cover a broad range of topics in algorithms, data structures, and web design, with a heavy emphasis on programming. Additionally, the internet is coupled with the syllabus at many places, from web design and HTML to graph algorithms and pattern matching. This connection enlivens the discussion of otherwise dry topics like searching, sorting, indexing and hashing. Moreover, the challenge of web-scale computing motivates the continuing students in their later study of formal topics like algorithmic complexity, while non-continuing students acquire transferable analytical skills. We report on the experience in search engine projects for driving problem-based learning in computer science courses, for both high school and university students. Our experience shows that such projects are effective in both introductory and intermediate courses, and readily encompass student groups with diverse programming abilities.

REFERENCES

• 1: D. Boud and G. E. Feletti, editors. The Challenge of Problem-Based Learning. London: Kogan Page, 1997.
• 2: Sergey Brin , Lawrence Page, The anatomy of a large-scale hypertextual Web search engine, Computer Networks and ISDN Systems, v.30 n.1-7, p.107-117, April 1, 1998
• 3: J. R. Curran. Building a Python search engine. School of Information Technologies, University of Sydney.
• 4: Timothy Hickey , Amruth Kumar , Linda Wilkens , Andrew Beiderman , Aparna Mahadev , Heidi Ellis, Internet-centric computing in the Computer Science curriculum, Proceedings of the 33rd SIGCSE technical symposium on Computer science education, February 27-March 03, 2002, Cincinnati, Kentucky
• 5: Anany V. Levitin, Introduction to the Design and Analysis of Algorithms, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 2002
• 6: Christine Shannon, Another breadth-first approach to CS I using python, Proceedings of the 34th SIGCSE technical symposium on Computer science education, February 19-23, 2003, Reno, Navada, USA

INDEX TERMS

Primary Classification:
  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION
      K.3.2 Computer and Information Science Education

General Terms:
Algorithms

Keywords:
Google, data structures, digraphs, python, web