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Exploring the Acceptance of the Web-Based Coding Tool in an Introductory Programming Course: A Pilot Study

  • Igor ŠkorićEmail author
  • Tihomir Orehovački
  • Marina Ivašić-Kos
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1253)

Abstract

Web-based coding tools are a popular alternative to desktop applications widely employed in education. Understanding the factors that affect the acceptance of web-based coding tools is a prerequisite for their successful application. With an aim to determine to what extent students’ attitude towards programming and their previous programming knowledge affect students’ acceptance of the web-based programming tool, an empirical study was carried out in which the technology acceptance model (TAM) was employed as a theoretical backbone. Participants in the study were students enrolled to the introductory programming course who used Repl.it as a representative sample of the web-based coding tool. The psychometric features of the introduced research framework were examined by means of the partial least square structural equation modelling technique. The study findings revealed that attitude towards programming does not play an important role in the adoption of a web-based coding tool.

Keywords

Web-based coding tool Technology acceptance model Introductory programming course Empirical study Post-use questionnaire 

References

  1. 1.
    Valentine, D.W.: CS educational research: a meta-analysis of SIGCSE technical symposium proceedings. ACM SIGCSE Bull. 36(1), 255–259 (2004)CrossRefGoogle Scholar
  2. 2.
    Watson, C., Li, F.W.: Failure rates in introductory programming revisited. In: Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education, pp. 39–44. ACM (2014)Google Scholar
  3. 3.
    Sheard, J., Simon, S., Hamilton, M., Lönnberg, J.: Analysis of research into the teaching and learning of programming. In: Proceedings of the Fifth International Workshop on Computing Education Research Workshop, pp. 93–104. ACM (2009)Google Scholar
  4. 4.
    Davis, F., Venkatesh, V.: A critical assessment of potential measurement biases in the technology acceptance model: three experiments. Int. J. Hum Comput Stud. 45(1), 19–45 (1996)CrossRefGoogle Scholar
  5. 5.
    Bergin, S., Reilly, R.: Programming: factors that influence success. In: 36th SIGCSE Technical Symposium on Computer Science Education, pp. 411–415 (2005)Google Scholar
  6. 6.
    Hagan, D., Selby, M.: Does it help to have some programming experience before beginning a computing degree program? In: 5th Annual SIGCSE/SIGCUE ITiCSE Conference on Innovation and Technology in Computer Science Education, pp. 25–28 (2000)Google Scholar
  7. 7.
    Holden, E., Weeden, E.: The impact of prior experience in an information technology programming course sequence. In: 4th Conference on Information Technology Curriculum, pp. 41–46 (2003)Google Scholar
  8. 8.
    Wilson, B., Shrock, S.: Contributing to success in an introductory computer science course. ACM SIGCSE Bull. 33(1), 184–188 (2001)CrossRefGoogle Scholar
  9. 9.
    Baser, M.: Attitude, gender and achievement in computer programming. Online Submiss. 14(2), 248–255 (2013)Google Scholar
  10. 10.
    Facey-Shaw, L., Golding, P.: Effects of peer tutoring and attitude on academic performance of first year introductory programming students. In: Frontiers in Education 35th Annual Conference (2005)Google Scholar
  11. 11.
    Sarstedt, M., Cheah, J.: Partial least squares structural equation modeling using SmartPLS: a software review. J. Mark. Anal. 7(3), 196–202 (2019)CrossRefGoogle Scholar
  12. 12.
    Hulland, J.: Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strat. Manag. J. 20(2), 195–204 (1999)CrossRefGoogle Scholar
  13. 13.
    Hair, J., et al.: PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19(2), 139–152 (2011)CrossRefGoogle Scholar
  14. 14.
    Hartshorne, R., Ajjan, H.: Examining student decisions to adopt Web 2.0 technologies: theory and empirical tests. J. Comput. High. Educ. 21, 3 (2009)CrossRefGoogle Scholar
  15. 15.
    van der Heijden, H.: Factors influencing the usage of websites: the case of a generic portal in The Netherlands. Inf. Manag. 40(6), 541–549 (2003)CrossRefGoogle Scholar
  16. 16.
    Orehovački, T.: Methodology for evaluating the quality in use of Web 2.0 applications. University of Zagreb (2013). (in Croatian)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Igor Škorić
    • 1
    Email author
  • Tihomir Orehovački
    • 1
  • Marina Ivašić-Kos
    • 2
  1. 1.Faculty of InformaticsJuraj Dobrila University of PulaPulaCroatia
  2. 2.Department of InformaticsUniversity of RijekaRijekaCroatia

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