Core empirical concepts and skills for computer science

ABSTRACT

Educators are increasingly acknowledging that practical problems in computer science demand basic competencies in experimentation and data analysis. However, little effort has been made towards explicitly identifying those empirical concepts and skills needed by computer scientists, nor in developing methods of integrating those concepts and skills into CS curricula. In this paper, we identify a core list of empirical competencies and motivate them based on established courses outside of computer science, their potential use in standard CS courses, and their application to real-world problems. Sample assignments that facilitate the integration of these competencies into the CS curriculum are also discussed.

REFERENCES

• 1: Grant Braught , David Reed, The knob & switch computer: A computer architecture simulator for introductory computer science, Journal on Educational Resources in Computing (JERIC), v.1 n.4, p.31-45, December 2001 [doi>10.1145/514144.514730]
• 2: Grant Braught , David Reed, Disequilibration for teaching the scientific method in computer science, ACM SIGCSE Bulletin, v.34 n.1, March 2002
• 3: Victor R. Basili, The role of experimentation in software engineering: past, current, and future, Proceedings of the 18th international conference on Software engineering, p.442-449, March 25-29, 1996, Berlin, Germany
• 4: Ewa Z. Bem, Experiment-based project in undergraduate computer architecture, ACM SIGCSE Bulletin, v.34 n.1, March 2002
• 5: Blatchford, N. (2003). "Analysis: x86 vs. PPC." OS News. Retrieved August 4, 2003 from http://www.osnews.com/story.php?news_id=3997.
• 6: Matthew C. Clarke, Teaching the empirical approach to designing human-computer interaction via an experiential group project, ACM SIGCSE Bulletin, v.30 n.1, p.198-201, Mar. 1998
• 7: Allen B. Downey, Teaching experimental design in an operating systems class, ACM SIGCSE Bulletin, v.31 n.1, p.316-320, March 1999
• 8: Freedman, D., Pisani, R., and Purves, R. (1998). Statistics, Third Edition. New York: W.W. Norton & Company.
• 9: T. Dean Hendrix , James H. Cross, II , Saeed Maghsoodloo , Matthew L. McKinney, Do visualizations improve program comprehensibility? experiments with control structure diagrams for Java, ACM SIGCSE Bulletin, v.32 n.1, p.382-386, Mar. 2000
• 10: Joint IEEE Computer Society/ACM Task Force for CC2001 (2001). "Computing Curricula 2001." Online at http://www.acm.org/sigcse/cc2001/.
• 11: Miller, C.S. (2003). "Relating Theory to Actual Results in Computer Science and Human-Computer Interaction. Computer Science Education 13(3): 227--240.
• 12: Trevor Mudge, Report on the panel: “how can computer architecture researchers avoid becoming the society for irreproducible results?”, ACM SIGARCH Computer Architecture News, v.24 n.1, p.1-5, March 1996 [doi>10.1145/232790.232791]
• 13: Allen Newell , Herbert A. Simon, Computer science as empirical inquiry: symbols and search, Communications of the ACM, v.19 n.3, p.113-126, March 1976 [doi>10.1145/360018.360022]
• 14: David Reed , Craig Miller , Grant Braught, Empirical investigation throughout the CS curriculum, ACM SIGCSE Bulletin, v.32 n.1, p.202-206, Mar. 2000
• 15: Steven Robbins , Kay A. Robbins, Empirical exploration in undergraduate operating systems, ACM SIGCSE Bulletin, v.31 n.1, p.311-315, March 1999
• 16: Walter F. Tichy, Should Computer Scientists Experiment More?, Computer, v.31 n.5, p.32-40, May 1998 [doi>10.1109/2.675631 ]
• 17: Marvin V. Zelkowitz , Dolores R. Wallace, Experimental Models for Validating Technology, Computer, v.31 n.5, p.23-31, May 1998 [doi>10.1109/2.675630 ]

INDEX TERMS

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

Additional Classification:
  A. General Literature
  A.0 GENERAL

  G. Mathematics of Computing
  G.3 PROBABILITY AND STATISTICS

  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION
      K.3.2 Computer and Information Science Education
          Subjects: Curriculum

General Terms:
Experimentation

Keywords:
empirical concepts, empirical skills