Developing authentic problem solving skills in introductory computing classes

ABSTRACT

The ability to solve problems is the key to developing software, and it is an ability that can be difficult to learn. Introductory Computer Science students are often taught syntax and semantics, along with simple problems designed to develop logical, structured thinking, but authentic problem-solving skills are rarely developed at these early stages.

In this paper we describe an approach to introductory computer science education that addresses student engagement through integrating cooperative learning techniques and authentic problem solving processes throughout each aspect of the curriculum.

Over a period of 4 years, the introductory computer science course at the University of Adelaide has been modified to support a cooperative learning style. A three-stage methodology has been implemented in place of traditional lectures to achieve this. The process focuses on observing the application of programming techniques, observing problem solving techniques and then applying cooperative problem solving exercises in the classroom. The results from this change in teaching methodology have been an increase in attendance rates at lectures and practical sessions as well as improved learning outcomes as measured by exam results. Student experience surveys show students have greater motivation for learning and believe they have a better understanding of concepts since the changes have occurred.

REFERENCES

• 1: V. H. Allan , M. V. Kolesar, Teaching computer science: a problem solving approach that works, ACM SIGCUE Outlook, v.25 n.1-2, p.2-10, Jan./April 1997 [doi>10.1145/274375.274376]
• 2: D. J. Barnes, S. Fincher, and S. Thompson. Introductory problem solving in computer science. In Proceedings of the 5th Annual Conference on the Teaching of Computing, pages 36--39, August 1997.
• 3: R. Burns. Study and stress among first year students in an australian university. Higher Education Research and Development, 16:61--77, 1991.
• 4: H. Cameron. Assessment and feedback in higher education: Key links in the learning chain. In Proceedings of the 2nd Education Research Group of Adelaide Conference (ERGA 2007), September 2007.
• 5: K. A. Ericsson, R. T. Krampe, and C. Tesch-Romer. The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3):363--406, 1993.
• 6: Thomas R. Flowers , Karl A. Gossett, Teaching problem solving, computing, and information technology with robots, Journal of Computing Sciences in Colleges, v.17 n.6, p.45-55, May 2002
• 7: David Ginat, Misleading intuition in algorithmic problem solving, Proceedings of the thirty-second SIGCSE technical symposium on Computer Science Education, p.21-25, February 2001, Charlotte, North Carolina, United States
• 8: David Ginat, Learning from wrong and creative algorithm design, Proceedings of the 39th SIGCSE technical symposium on Computer science education, March 12-15, 2008, Portland, OR, USA
• 9: W. Glasser. The Quality School: Managing Students without Coercion, 1st edition. New York: Harper Collins, ISBN: 006055200X, 1990.
• 10: Donald E. Knuth, Structured Programming with go to Statements, ACM Computing Surveys (CSUR), v.6 n.4, p.261-301, Dec. 1974 [doi>10.1145/356635.356640]
• 11: C. McInnis, R. James, and R. Hartley. Trends in the first year experience in australian universities. Technical report, DETYA, Canberra, 2000.
• 12: Z. Michalewicz and M. Michalewicz. Puzzle-Based Learning: An Introduction to Critical Thinking, Mathematics, and Problem Solving. Hybrid Publishers, June 2008.
• 13: G. Polya. How To Solve It. Princeton University Press, 1945.
• 14: David D. Riley, Teaching problem solving in an introductory computer science class, ACM SIGCSE Bulletin, v.13 n.1, p.244-251, February 1981
• 15: B. Smith and J. MacGregor. What is Collaborative Learning? National Centre on Postsecondary Teaching, Learning and Assessment, Pennsylvania State University, 1992.
• 16: S. Sonnentag. Expertise in professional software design: A process study. Journal of Applied Psychology, 83(5):703--715, 1998.
• 17: M. Urban-Lurain and D. J. Weinshank. Attendance and outcomes in a large, collaborative learning, performance assessment course. In Annual Meeting of the American Educational Research Association (AERA), 2000.
• 18: N. R. White. Tertiary education in the noughties: the student perspective. Higher Education Research & Development, 25(3):231--246, 2006.

INDEX TERMS

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

General Terms:
Design, Human Factors

Keywords:
cooperative learning, engagement, introductory computer science education, problem solving