skip to main content
10.1145/3010915.3010967acmotherconferencesArticle/Chapter ViewAbstractPublication PagesozchiConference Proceedingsconference-collections
short-paper

Voluntary participation in discussion forums as an engagement indicator: an empirical study of teaching first-year programming

Published:29 November 2016Publication History

ABSTRACT

Computer programming is a required skill for most STEM (Science, Technology, Engineering and Mathematics) students. However, teaching novices programming has long been considered a big challenge by computer science educators as manifested by the observation that first-year programming topics tend to have a higher failure rate than other first-year topics. Existing studies have discovered that lack of engagement in learning programming is a key determinant of a student's poor performance. Therefore, it is beneficial to perceive a student's lack of engagement so that appropriate actions can be taken ahead of time. However, first year topics especially programming topics usually have very large enrolments, making it hard for a lecturer to keep track of each individual student's engagement level. As learning management systems (LMS) have been widely adopted by universities, in this paper we suggest using a student's voluntary participation in a programming topic's discussion forum provided by LMS as an engagement indicator so that the lecturer can constantly monitor and re-engage those who present low or no engagement. This recommendation is based on an empirical study of a first-year programming topic that reveals a positive correlation between one's voluntary participation in peer interaction through the topic's discussion forum and one's learning outcome in the topic.

References

  1. Agresti, A. (2002). "Logit models for multinomial responses." Categorical Data Analysis, Second Edition: 267--313. Google ScholarGoogle ScholarCross RefCross Ref
  2. Bennedsen, J. and Caspersen, M. E. (2007). "Failure rates in introductory programming." ACM SIGCSE Bulletin 39(2): 32--36. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Brooks, R. (1977). "Towards a theory of the cognitive processes in computer programming." International Journal of Man-Machine Studies 9(6): 737--751.Google ScholarGoogle ScholarCross RefCross Ref
  4. Butler, M. and Morgan, M. (2007). "Learning challenges faced by novice programming students studying high level and low feedback concepts." Proc. ASCILITE Singapore: 99--107.Google ScholarGoogle Scholar
  5. Brooks, R. (1977). "Towards a theory of the cognitive processes in computer programming." International Journal of Man-Machine Studies 9(6): 737--751. Google ScholarGoogle ScholarCross RefCross Ref
  6. Butler, M. and Morgan, M. (2007). "Learning challenges faced by novice programming students studying high level and low feedback concepts." Proc. ASCILITE Singapore: 99--107.Google ScholarGoogle Scholar
  7. Byrne, P. and Lyons, G. (2001). "The effect of student attributes on success in programming." ACM SIGCSE Bulletin 33(3):49--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Caspersen, M. E. and Kolling, M. (2009). "STREAM: A first programming process." ACM Transactions on Computing Education (TOCE) 9(1): 4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. de Raadt, M., Hamilton, M. et al. (2005). "Approaches to learning in computer programming students and their effect on success." Proc. The 28th HERDSA Annual Conference: 407--414.Google ScholarGoogle Scholar
  10. Ellison, N. B., Steinfield, C. et al. (2011). "Connection strategies: Social capital implications of Facebook-enabled communication practices." New media & society 13(6):873--892. Google ScholarGoogle ScholarCross RefCross Ref
  11. Ford, M. and Venema, S. (2010). "Assessing the success of an introductory programming course." Journal of Information Technology Education 9(1): 133--145.Google ScholarGoogle ScholarCross RefCross Ref
  12. Gomes, A. J., Santos, A. N. et al. (2012). "A study on students' behaviours and attitudes towards learning to program." Proc. 17th ACM annual conference on Innovation and technology in computer science education: 132--137. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Gries, D. (1974). What should we teach in an introductory programming course?" ACM SIGCSE Bulletin 6(1): 81--89. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hockings, C., Cooke, S. et al. (2008). "Switched off? A study of disengagement among computing students at two universities." Research Papers in Education 23(2): 191--201. Google ScholarGoogle ScholarCross RefCross Ref
  15. Hollander, M. and Wolfe, D. A. (1999). "Nonparametric statistical methods." J Wiley New York.Google ScholarGoogle Scholar
  16. Huggard, M. (2004). Programming trauma: Can it be avoided." Proc. BCS Grand Challenges in Computing: Education: 50--51.Google ScholarGoogle Scholar
  17. Jenkins, T. (2002). "On the difficulty of learning to program." Proc. The 3rd Annual Conference of the LTSN Centre for Information and Computer Sciences.Google ScholarGoogle Scholar
  18. Lau, W. W. and Yuen, A. H. (2011). "Modelling programming performance: Beyond the influence of learner characteristics." Computers & Education 57(1): 1202--1213. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Ma, L., Ferguson, J. et al. (2007). "Investigating the viability of mental models held by novice programmers." ACM SIGCSE Bulletin 39(1): 499--503. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Malhotra, N. (2013). "Experimenting with Facebook in the college classroom." Faculty Focus.Google ScholarGoogle Scholar
  21. McCracken, M., Almstrum, V. et al. (2001). "A multinational, multi-institutional study of assessment of programming skills of first-year CS students." ACM SIGCSE Bulletin 33(4): 125--180. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. McGettrick, A., Boyle, R. et al. (2005). "Grand Challenges in Computing: Education---A Summary." The Computer Journal 48(1): 42--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. McGettrick, A. D. (2004). "Grand challenges in computing: Education." British Computer Society.Google ScholarGoogle Scholar
  24. Nandi, D., Hamilton, M. et al. (2015). "Investigation of participation and quality of online interaction." International Journal of Modern Education and Computer Science 7(8): 25. Google ScholarGoogle ScholarCross RefCross Ref
  25. Robins, A., Rountree, J. et al. (2003). "Learning and teaching programming: A review and discussion." Computer Science Education 13(2): 137--172. Google ScholarGoogle ScholarCross RefCross Ref
  26. Roddan, M. (2002). "The determinants of student failure and attrition in first year computing science." Computing Science, Glasgow University, project Summer.Google ScholarGoogle Scholar
  27. Ross, C., Orr, E. S. et al. (2009). "Personality and motivations associated with Facebook use." Computers in Human Behaviour 25(2): 578--586. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Shih, R.-C. (2011). "Can Web 2.0 technology assist college students in learning English writing? Integrating Facebook and peer assessment with blended learning." Australasian Journal of Educational Technology 27(5): 829--845. Google ScholarGoogle ScholarCross RefCross Ref
  29. Shneiderman, B. and Mayer R. (1979). "Syntactic/semantic interactions in programmer behaviour: A model and experimental results." International Journal of Computer & Information Sciences 8(3): 219--238. Google ScholarGoogle ScholarCross RefCross Ref
  30. Soloway, E. and Spohrer, J. C. (1989). "Studying the Novice Programmer." Erlbaum Associates.Google ScholarGoogle Scholar
  31. Clear, T., Edwards, J. et al. (2008). "The Teaching of Novice Computer Programmers: Bringing the Scholarly Research Approach to Australia." Proc. The 10th conference on Australasian Computing Education: 63--68.Google ScholarGoogle Scholar
  32. Tracz, W. J. (1979). "Computer programming and the human thought process." Software: Practice and Experience 9(2): 127--137. Google ScholarGoogle ScholarCross RefCross Ref
  33. Walsh, K. (2012). "Can social media play a role in improving retention in higher education? research says it can." EmergingEdTech.Google ScholarGoogle Scholar
  34. Wu, P. and Hsu, L. (2011). "EFL learning on social networking site?: An action research on Facebook." Teaching & Learning with Vision Conference.Google ScholarGoogle Scholar
  35. Xia, C., Fielder, J. et al. (2013). "Achieving better peer interaction in online discussion forums: A reflective practitioner case study." Issues in Educational Research 23(1): 97--113.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    OzCHI '16: Proceedings of the 28th Australian Conference on Computer-Human Interaction
    November 2016
    706 pages
    ISBN:9781450346184
    DOI:10.1145/3010915

    Copyright © 2016 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 29 November 2016

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • short-paper

    Acceptance Rates

    Overall Acceptance Rate362of729submissions,50%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader