Enhancing the Metacognitive Skill of Novice Programmers Through Collaborative Learning

Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 76)

Abstract

Computer Supported Collaborative Learning (CSCL) aims to improve education by combining collaborative learning with modern information and communication technology. The opportunity exists to develop successful CSCL applications due to the increase in popularity of social networking and online gaming among students. In this chapter, we present an approach for promoting metacognition in computer programming using collaboration and computer games. We show that CSCL can improve the students’ metacognitive skills and the use of games motivates and engages students in the learning process. Together, they enhance the qualities of a successful problem solver and low problem solving skill has been identified as the main challenge faced by novice computer programmers.

Keywords

CSCL Programming Metacognition Problem solving COPS Multiplayer game Collaborative learning 

Abbreviations

CL

Collaborative learning

COPS

Collaborative online problem solving

CSEC

Caribbean secondary education certificate

CSCL

Computer supported collaborative learning

CXC

Caribbean examinations council

DIV

Division

ICT

Information and communications technology

IT

Information technology

MOD

Modulo

References

  1. 1.
    Bachu, E., Bernard, M.: A computer supported collaborative learning (CSCL) model for educational multiplayer games. In: 11th International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government. Las Vegas (2012)Google Scholar
  2. 2.
    Bachu, E., Bernard, M.: Enhancing computer programming fluency through game playing. Int. J. Comput. 1(3) (2011)Google Scholar
  3. 3.
    CXC. Information technology general proficiency examination May/June 2011. Report on Candidates’ Work in the Secondary Education Certificate Examination. St. Michael, Barbados (2011)Google Scholar
  4. 4.
    CXC. Information technology general proficiency examination May/June 2010. Report on Candidates’ Work in the Secondary Education Certificate Examination. St. Michael, Barbados (2010)Google Scholar
  5. 5.
    CXC. Information technology general proficiency examination May/June 2012. Report on Candidates’ Work in the Secondary Education Certificate Examination. St. Michael, Barbados (2012)Google Scholar
  6. 6.
    CXC. Annual reports for year 2005–2009. St. Michael, BarbadosGoogle Scholar
  7. 7.
    CXC. Information technology general proficiency examination January 2011. Report on Candidates’ Work in the Secondary Education Certificate Examination. St. Michael, Barbados (2011)Google Scholar
  8. 8.
    CXC. Information technology general proficiency examination January 2010. Report on Candidates’ Work in the Secondary Education Certificate Examination. St. Michael, Barbados (2010)Google Scholar
  9. 9.
    CXC. Information technology general proficiency examination January 2012. Report on Candidates’ Work in the Secondary Education Certificate Examination. St. Michael, Barbados (2012)Google Scholar
  10. 10.
    Beaubouef, T., Mason, J.: Why the high attrition rate for computer science students: some thoughts and observations. ACM SIGCSE Bull. 37(2), 103–106 (2005)CrossRefGoogle Scholar
  11. 11.
    Sheard, J., Simon, S., Hamilton, M., Jan L.: Analysis of research into the teaching and learning of programming. In: 5th International Computing Education Research Workshop, pp. 93–104. ACM, New York (2009)Google Scholar
  12. 12.
    Gomes, A., Mendes, A.J.: Learning to program-difficulties and solutions. In: International Conference on Engineering Education, vol. 2007. Coimbra, Portugal (2007)Google Scholar
  13. 13.
    Deek, F.P., McHugh, J.A., Turoff, M.: Problem solving and cognitive foundations for program development: an integrated model. In: Sixth International Conference on Computer Based Learning in Science (CBLIS), pp. 266–271. Nicosia, Cyprus (2003)Google Scholar
  14. 14.
    Watson, R., de Raadt, M., Toleman, M.: Teaching and assessing programming strategies explicitly. In: 11th Australasian Computing Education Conference (ACE 2009), Wellington, New Zealand (2009)Google Scholar
  15. 15.
    Sardone, N.B.: Developing information technology fluency in college students: an investigation of learner environments and learner characteristics. Inf. Technol. Educ. 10(1), 101–122 (2011)Google Scholar
  16. 16.
    Hundhausen, C.D., Farley, S.F., Brown, J.L.: Can direct manipulation lower the barriers to computer programming and promote transfer of training?: an experimental study. ACM Trans. Comput. Hum. Interact. 16(3), 1–40 (2009)CrossRefGoogle Scholar
  17. 17.
    Mayer, R.E.: Cognitive, metacognitive, and motivational aspects of problem solving. Instr. Sci. 26(1), 49–63 (1998)CrossRefGoogle Scholar
  18. 18.
    Metcalfe, J., Shimamura, A.: Metacognition: Knowing About Knowing. Bradford Books, Cambridge (1994)Google Scholar
  19. 19.
    Jonassen, D.: Learning to solve problems: A Handbook for Designing Problem-Solving Learning Environments. Taylor & Francis, United Kingdom (2011)Google Scholar
  20. 20.
    Bachu, E.: A Framework for Computer Supported Collaborative Learning (CSCL) Using Online Multiplayer Games. M.Phil., dissertation, The University of the West Indies, St. Augustine, Trinidad and Tobago (2013)Google Scholar
  21. 21.
    Viviene, C., Macaulay, C.: Transfer of Learning in Professional and Vocational Education. Psychology Press, United Kingdom (2000)Google Scholar
  22. 22.
    Ben-Ari, M.: Constructivism in computer science education. In: 29th SIGCSE Technical Symposium on Computer Science Education, pp. 257–261. ACM, New York (1998)Google Scholar
  23. 23.
    Gonzalez, G.: Constructivism in an introduction to programming course. J. Comput. Sci. Coll. 19(4), 299–305 (2004)Google Scholar
  24. 24.
    Boyer, N.R., Langevin, S., Gaspar, A.: Self direction and constructivism in programming education. In: 9th ACM SIGITE Conference on Information Technology Education, pp. 89–94. ACM, New York (2008)Google Scholar
  25. 25.
    Lui, A.K., Kwan, R., Poon, M., Cheung, Y.H.Y.: Saving weak programming students: applying constructivism in a first programming course. ACM SIGCSE Bull. 36(2), 72–76 (2004)CrossRefGoogle Scholar
  26. 26.
    Gokhale, A.: Collaborative learning enhances critical thinking. J. Technol. Educ. 7(1), 56–65 (1995)Google Scholar
  27. 27.
    Panitz, T.: Collaborative versus cooperative learning: a comparison of the two concepts which will help us understand the underlying nature of interactive learning (1999)Google Scholar
  28. 28.
    Alavi, M.: Computer-mediated collaborative learning: an empirical evaluation. MIS Q. 18(2), 159–174 (1994)CrossRefGoogle Scholar
  29. 29.
    Jara, C.A., Candelas, F.A., Torres, F., Dormido, S., Esquembre, F., Reinoso, O.: Real-time collaboration of virtual laboratories through the Internet. Comput. Educ. 52(1), 126–140 (2009)CrossRefGoogle Scholar
  30. 30.
    Roger, T., Johnson, D.W.: An overview of cooperative learning. In: Thousand, J., Villa, A., Nervin, A. (eds.) Creativity and Collaborative Learning. Brookes Press, Baltimore (1994)Google Scholar
  31. 31.
    Kelleher, C., Pausch, R.: Lowering the barriers to programming: a taxonomy of programming environments and languages for novice programmers. ACM Comput. Surv. 37(2), 83–137 (2005)CrossRefGoogle Scholar
  32. 32.
    Urness, T.: Assessment using peer evaluations, random pair assignment, and collaborative programing in CS1. J. Comput. Small Coll. 25(1), 87–93 (2009)Google Scholar
  33. 33.
    Bagley, C.A., Chou, C.C.: Collaboration and the importance for novices in learning Java computer programming. In: 12th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, pp. 211–215. ACM, New York (2007)Google Scholar
  34. 34.
    Williams, L.: Lessons learned from seven years of pair programming at North Carolina State University. SIGCSE Bull. 39(4), 79–83 (2007)CrossRefGoogle Scholar
  35. 35.
    Davidson, N.: Cooperative and collaborative learning: an integrative perspective. In: Thousand, J., Villa, R., Nevin, A. (eds.) Creativity and Collaborative Learning: A Practical Guide to Empowering Students and Teachers, pp. 13–30. Paul H. Brookes Publishing Co., Baltimore, MD (1994)Google Scholar
  36. 36.
    Preston, D.: Pair programming as a model of collaborative learning: a review of the research. J. Comput. Sci. Coll. 20(4), 39–45 (2005)Google Scholar
  37. 37.
    DeClue, T.H.: Pair programming and pair trading: effects on learning and motivation in a CS2 course. J. Comput. Sci. Coll. 18(5), 49–56 (2003)Google Scholar
  38. 38.
    Ehtinen, E., Hakkarainen, K., Lipponen, L., Rahikainen, M., Muukkonen, H.: Computer supported collaborative learning: a review. The JHGI Giesbers Reports on Education (1999)Google Scholar
  39. 39.
    Stahl, G., Koschmann, T., Suthers, D.: CSCL: an historical perspective. In: Sawyer, K.R. (ed.) Cambridge Handbook of the Learning Sciences, vol. 5, pp. 409–426. Cambridge University Press, UK (2006)Google Scholar
  40. 40.
    Newman, D.R., Webb, B., Cochrane, C.: A content analysis method to measure critical thinking in face-to-face and computer supported group learning. Interpersonal Comput. Technol. 3(2), 56–77 (1995)Google Scholar
  41. 41.
    Pifarre, M., Cobos, R.: Promoting metacognitive skills through peer scaffolding in a CSCL environment. Int. J. Comput. Support. Collaborative Learn. 5(2), 237–253 (2010)CrossRefGoogle Scholar
  42. 42.
    Lee, E.Y.C., Chan, C.K.K., Van-Aalst, J.: Students assessing their own collaborative knowledge building. Int. J. Comput. Support. Collaborative Learn. 1(1), 57–87 (2006)CrossRefGoogle Scholar
  43. 43.
    Diziol, D., Rummel, N., Spada, H., McLaren, B.M.: Promoting learning in mathematics: script support for collaborative problem solving with the cognitive tutor algebra. In: 8th International Conference on Computer Supported Collaborative Learning, pp. 39–41. ISLS, USA (2007)Google Scholar
  44. 44.
    Chen, J.W.: Designing a web-based Van Hiele model for teaching and learning computer programming to promote collaborative learning. In: 5th IEEE International Conference on Advanced Learning Technologies, pp. 313–317. IEEE, NJ (2005)Google Scholar
  45. 45.
    Stegmann, K., Weinberger, A., Fischer, F.: Facilitating argumentative knowledge construction with computer-supported collaboration scripts. Int. J. Comput. Support. Collaborative Learn. 2(4), 421–447 (2007)CrossRefGoogle Scholar
  46. 46.
    Lu, J., Lajorie, S.P., Wiseman, J.: Scaffolding problem-based learning with CSCL tools. Int. J. Comput. Support. Collaborative Learn. 5(3), 283–298 (2010)CrossRefGoogle Scholar
  47. 47.
    O’Donnell, A.M., Dansereau, D.F.: Scripted cooperation in student dyads: a method for analyzing and enhancing academic learning and performance. In: Hertz-Lazarowitz, R., Miller, N. (eds.) Interaction in Cooperative Groups: The Theoretical Anatomy of Group Learning, pp. 120–141. Cambridge Universirty Press, UK (1992)Google Scholar
  48. 48.
    Rummel, N., Spada, H.: Can people learn computer-mediated collaboration by following a script? In: Fischer, Frank, Kollar, Ingo, Mandl, Heinz, Haake, JörgM (eds.) Scripting Computer-Supported Collaborative Learning, pp. 39–55. Springer, USA (2007)CrossRefGoogle Scholar
  49. 49.
    Weinberger, A., Fischer, F., Mandl, H.: Fostering computer supported collaborative learning with cooperation scripts and scaffolds. In: 5th International Conference on Computer Supported Collaborative Learning, pp. 573–574. ISLS, USA (2002)Google Scholar
  50. 50.
    Bures, E.M., Abrami, P.C., Schmid, R.F.: Exploring whether students’ use of labelling depends upon the type of activity. Int. J. Comput. Support. Collaborative Learn. 5(1), 103–116 (2010)CrossRefGoogle Scholar
  51. 51.
    Prensky, M.: Digital game-based learning. Comput. Entertainment 1(1), 1–4 (2003)CrossRefGoogle Scholar
  52. 52.
    Tsiatsos, T.A., Konstantinidis, A.: Utilizing multiplayer video game design principles to enhance the educational experience in 3D virtual computer supported collaborative learning environments. In: 12th IEEE International Conference on Advanced Learning Technologies, pp. 621–623, IEEE, NJ (2012)Google Scholar
  53. 53.
    Doherty, L., Kumar, V.: Teaching programming through games. In: International Workshop on Technology for Education, pp. 111–113. IEEE, Bangalore (2009)Google Scholar
  54. 54.
    Rajaravivarma, R.A.: Games-based approach for teaching the introductory programming course. SIGCSE Bull. 37(4), 98–102 (2005)CrossRefGoogle Scholar
  55. 55.
    Paraskeva, F., Mysirlaki, S., Papagianni, A.: Multiplayer online games as educational tools: Facing new challenges in learning. Comput. Educ. 54(2), 498–505 (2010)CrossRefGoogle Scholar
  56. 56.
    Li, Y., Tian, X., Gao, P.: Research on the application of MMO games in education. In: International Conference on Industrial Control and Electronics Engineering (ICICEE), pp. 535–538. IEEE, NJ (2012)Google Scholar
  57. 57.
    Voulgari, I., Komis, V.: Massively multi-user online games: the emergence of effective collaborative activities for learning. In: 2nd IEEE International Conference on Digital Game and Intelligent Toys Based Education (DIGITEL), pp. 132–134. IEEE, Banff, BC (2008)Google Scholar
  58. 58.
    Slavin, R.E.: Research on cooperative learning and achievement: what we know, what we need to know. Contemp. Educ. Psychol. 21(1), 43–69 (1996)CrossRefGoogle Scholar
  59. 59.
    Johnson, D.W., Johnson, R.T., Karl Smith, K.: The state of cooperative learning in postsecondary and professional settings. Educ. Psychol. Rev. 19(1), 15–29 (2007)CrossRefGoogle Scholar
  60. 60.
    Roy, G.G.: Designing and explaining programs with a literate pseudocode. ACM J. Educ. Resour. Comput. 6(1), 1–18 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computing and Information TechnologyThe University of the West IndiesSt. AugustineTrinidad and Tobago

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