Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Exploring the Antecedents of Verificator Adoption

  • Conference paper
  • First Online:
Human-Computer Interaction. Design and User Experience Case Studies (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12764))

Included in the following conference series:

Abstract

This paper aims to identify the determinants of students’ behavioral intentions related to the use of Verificator, an educational tool designed for acquiring good programming habits. Based on the literature review, a research framework that represents an interplay of twelve adoption constructs was proposed. Data was collected by means of the post-use questionnaire. The sample of study participants was composed of novice programmers who were using Verificator at least one semester for the purpose of solving assignments during lab-based exercises. The psychometric features of the framework were examined by means of the partial least square structural equation modelling technique. Reported findings can be used as a foundation for future advances in the field with respect to the adoption of tools designed for learning programming concepts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ain, N., Kaur, K., Waheed, M.: The influence of learning value on learning management system use: an extension of UTAUT2. Inf. Dev. 32(5), 1–16 (2015)

    Google Scholar 

  2. Alenezi, A.R., Abdul Karim, A.M., Veloo, A.: An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students’ intention to use e-learning: a case study from saudi arabian governmental universities. Turkish Online J. Educ. Technol. 9(4), 22–34 (2010)

    Google Scholar 

  3. Alice (2020). http://www.alice.org

  4. Bhattacherjee, A.: Understanding information systems continuance: an expectation confirmation model. MIS Q. 25(3), 351–370 (2001)

    Article  Google Scholar 

  5. Brown, I.T.J.: Individual and technological factors affecting perceived ease of use of web-based learning technologies in a developing country. Electron. J. Inf. Syst. Dev. Countr. 9(5), 1–15 (2002)

    Google Scholar 

  6. Carlisle, M., Wilson, T., Humphries, J., Hadfield, M.: RAPTOR: introducing programming to non-majors with flowcharts. J. Comput. Sci. Colleg. 19(4), 52–60 (2004)

    Google Scholar 

  7. Chen, Y.-Y., Huang, H.-L., Hsu, Y.-C., Tseng, H.-C., Lee, Y.-C.: Confirmation of expectations and satisfaction with the internet shopping: the role of internet self-efficacy. Comput. Inf. Sci. 3(3), 14–22 (2010)

    Google Scholar 

  8. Chuo, Y.-H., Tsai, C.-H., Lan, Y.-L., Tsai, C.-S.: The effect of organizational support, self efficacy, and computer anxiety on the usage intention of e-learning system in hospital. Afr. J. Bus. Manage. 5(14), 5518–5523 (2011)

    Google Scholar 

  9. CodeCombat (2013). https://codecombat.com

  10. Cohen, J.: Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, Hillsdale (1988)

    MATH  Google Scholar 

  11. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)

    Article  Google Scholar 

  12. Esposito Vinzi, V., Trinchera, L., Amato, S.: PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. In: Esposito Vinzi, V., Chin, W.W., Henseler, J., Wang, H. (eds.) Handbook of Partial Least Squares, pp. 47–82. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-540-32827-8_3

    Chapter  Google Scholar 

  13. Fornell, C.G., Larcker, D.F.: Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Mark. Res. 18(3), 328–388 (1981)

    Article  Google Scholar 

  14. Gefen, D., Straub, D., Boudreau, M.C.: Structural equation modeling and regression: guidelines for research practice. Commun. Assoc. Inf. Syst. 4(7), 2–77 (2000)

    Google Scholar 

  15. Geisser, S.: The predictive sample reuse method with applications. J. Am. Stat. Assoc. 70(350), 320–328 (1975)

    Article  MATH  Google Scholar 

  16. Götz, O., Liehr-Gobbers, K., Krafft, M.: Evaluation of structural equation models using the Partial Least Squares (PLS) approach. In: Esposito Vinzi, V., Chin, W.W., Henseler, J., Wang, H. (eds.) Handbook of Partial Least Squares, pp. 691–711. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-540-32827-8_30

    Chapter  Google Scholar 

  17. Guido van Robot (2009). http://gvr.sourceforge.net

  18. Hackbarth, G., Grover, V., Yi, M.Y.: Computer playfulness and anxiety: positive and negative mediators of the system experience effect on perceived ease of use. Inf. Manage. 40(3), 221–232 (2003)

    Article  Google Scholar 

  19. Hair, J.F., Ringle, C.M., Sarstedt, M.: PLS-SEM: indeed a silver bullet. J. Market. Theory Pract. 19(2), 139–151 (2011)

    Article  Google Scholar 

  20. Hair, J.F., Sarstedt, M., Ringle, C.M., Mena, J.A.: An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Mark. Sci. 40(3), 414–433 (2012)

    Article  Google Scholar 

  21. Hart, M., Porter, G.: The impact of cognitive and other factors on the perceived usefulness of OLAP. J. Comput. Inf. Syst. 45(1), 47–56 (2004)

    Google Scholar 

  22. Henseler, J., Ringle, C.M., Sinkovics, R.R.: The use of partial least squares path modeling in international marketing. Adv. Int. Mark. 20, 277–319 (2009)

    Article  Google Scholar 

  23. Hsiao, C.-H., Chang, J.-J., Tang, K.-Y.: Exploring the influential factors in continuance usage of mobile social Apps: satisfaction, habit, and customer value perspectives. Telematics Inform. 33(2), 342–355 (2016)

    Article  Google Scholar 

  24. Hu, P.J.H., Clark, T.H.K., Ma, W.W.K.: Examining technology acceptance by school teachers: a longitudinal study. Inf. Manage. 41(2), 227–241 (2003)

    Article  Google Scholar 

  25. Hulland, J.: Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strateg. Manag. J. 20(2), 195–204 (1999)

    Article  Google Scholar 

  26. Idemudia, E.C., Dasuki, S.I., Ogedebe, P.: Factors that influence students’ programming skills: a case study from a Nigerian university. Int. J. Quant. Res. Educ. 3(4), 277–291 (2016)

    Article  Google Scholar 

  27. Jashapara, A., Tai, W.-C.: Knowledge mobilization through e-learning systems: understanding the mediating roles of self-efficacy and anxiety on perceptions of ease of use. Inf. Syst. Manage. 28(1), 71–83 (2011)

    Article  Google Scholar 

  28. Kang, M., Liew, B.Y.T., Lim, H., Jang, J., Lee, S.: Investigating the determinants of mobile learning acceptance in Korea using UTAUT2. In: Chen, G., Kumar, V., Kinshuk, Huang, R., Kong, S.C. (eds.) Emerging Issues in Smart Learning. LNET, pp. 209–216. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-44188-6_29

    Chapter  Google Scholar 

  29. Kim, Y.H., Kim, D.J., Wachter, K.: A study of mobile user engagement (MoEN): engagement motivations, perceived value, satisfaction, and continued engagement intention. Decis. Support Syst. 56, 361–370 (2013)

    Article  Google Scholar 

  30. Lee, M.-C.: Explaining and predicting users’ continuance intention toward e-learning: an extension of the expectation-confirmation model. Comput. Educ. 54(2), 506–516 (2010)

    Article  Google Scholar 

  31. Lin, C.S., Wu, S., Tsai, R.J.: Integrating perceived playfulness into expectation-confirmation model for web portal context. Inf. Manage. 42(5), 683–693 (2005)

    Article  Google Scholar 

  32. Moon, J.W., Kim, Y.G.: Extending the TAM for a world-wide-web context. Inf. Manage. 38(4), 217–230 (2001)

    Article  Google Scholar 

  33. Oliver, R.L.: A cognitive model for the antecedents and consequences of satisfaction. J. Mark. Res. 17, 460–469 (1980)

    Article  Google Scholar 

  34. Orehovački, T.: Methodology for evaluating the quality in use of web 2.0 applications (In Croatian: Metodologija vrjednovanja kvalitete u korištenju aplikacijama Web 2.0), Ph.D. thesis. University of Zagreb, Faculty of Organization and Informatics, Varaždin (2013)

    Google Scholar 

  35. Orehovački, T., Etinger, D., Babić, S.: Modelling an interplay of adoption determinants with respect to social Web applications used in massive online open courses. Univ. Access Inf. Soc. 18(3), 469–487 (2019). https://doi.org/10.1007/s10209-019-00673-y

    Article  Google Scholar 

  36. Orehovački, T., Radošević, D., Konecki, M.: Acceptance of verificator by information science students. Proceedings of the 34th International Conference on Information Technology Interfaces, Cavtat, pp. 223–230. IEEE (2012)

    Google Scholar 

  37. Orehovački, T., Radošević, D., Konecki, M.: Perceived quality of verificator in teaching programming. In: Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronics, Opatija, pp. 643–648. IEEE (2014)

    Google Scholar 

  38. Padilla-Meléndez, A., del Aguila-Obra, A.R., Garrido-Moreno, A.: Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Comput. Educ. 63, 306–317 (2013)

    Article  Google Scholar 

  39. Radošević, D., Orehovački, T., Lovrenčić, A.: New approaches and tools in teaching programming. In: Proceedings of the 20th Central European Conference on Information and Intelligent Systems, pp. 49–57. University of Zagreb, Faculty of Organization and Informatics (2009)

    Google Scholar 

  40. Radošević, D., Orehovački, T., Lovrenčić, A.: Verificator: educational tool for learning programming. Informatics in Education 8(2), 261–280 (2009)

    Article  Google Scholar 

  41. Radošević, D., Orehovački, T.: An analysis of novice compilation behavior using verificator. In: Proceedings of the 33rd International Conference on Information Technology Interfaces, Cavtat, pp. 325–330. IEEE (2011)

    Google Scholar 

  42. Raman, A., Don, Y.: Preservice teachers’ acceptance of learning management software: an application of the UTAUT2 model. Int. Educ. Stud. 6(7), 157–164 (2013)

    Article  Google Scholar 

  43. Reif, I., Orehovački, T.: ViSA: visualization of sorting algorithms. In: Proceedings of the 35th International Convention on Information and Communication Technology, Electronics and Microelectronics, Opatija, pp. 1146–1151. IEEE (2012)

    Google Scholar 

  44. Ringle, C.M., Wende, S., Becker, J.-M.: SmartPLS 3.3.3, SmartPLS GmbH, Boenningstedt (2021). http://www.smartpls.com

  45. Saadé, R.G., Kira, D.: Mediating the impact of technology usage on perceived ease of use by anxiety. Comput. Educ. 49(4), 1189–1204 (2007)

    Article  Google Scholar 

  46. Stone, M.: Cross-validatory choice and assessment of statistical predictions. J. Roy. Stat. Soc. B 36(2), 111–147 (1974)

    MathSciNet  MATH  Google Scholar 

  47. Stone, R.W., Baker-Eveleth, L.: Students’ expectation, confirmation, and continuance intention to use electronic textbooks. Comput. Hum. Behav. 29(3), 984–990 (2013)

    Article  Google Scholar 

  48. Tenenhaus, M., Esposito Vinzi, V., Chatelin, Y.-M., Lauro, C.: PLS path modeling. Comput. Stat. Data Anal. 48(1), 159–205 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  49. Terzis, V., Economides, A.A.: The acceptance and use of computer based assessment. Comput. Educ. 56(4), 1032–1044 (2011)

    Article  Google Scholar 

  50. Venkatesh, V.: Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 (2000)

    Article  Google Scholar 

  51. Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Dec. Sci. 39(2), 273–315 (2008)

    Article  Google Scholar 

  52. Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46(2), 186–204 (2000)

    Article  Google Scholar 

  53. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)

    Article  Google Scholar 

  54. Venkatesh, V., Thong, J.Y.L., Xu, X.: Consumer acceptance and use of information technology: extend-ing the unified theory of acceptance and use of technology. MIS Q. 36(1), 157–178 (2012)

    Article  Google Scholar 

  55. Zhao, X., Mattila, A.S., Tao, L.-S.E.: The role of post-training self-efficacy in customers’ use of self service technologies. Int. J. Serv. Ind. Manage. 19(4), 492–505 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Informatics, Juraj Dobrila University of Pula, Zagrebačka 30, 52100, Pula, Croatia

    Tihomir Orehovački

  2. Faculty of Organization and Informatics, University of Zagreb, Pavlinska 2, 42000, Varaždin, Croatia

    Danijel Radošević

Authors
  1. Tihomir Orehovački
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Danijel Radošević
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tihomir Orehovački .

Editor information

Editors and Affiliations

  1. The Open University of Japan, Chiba, Japan

    Masaaki Kurosu

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Orehovački, T., Radošević, D. (2021). Exploring the Antecedents of Verificator Adoption. In: Kurosu, M. (eds) Human-Computer Interaction. Design and User Experience Case Studies. HCII 2021. Lecture Notes in Computer Science(), vol 12764. Springer, Cham. https://doi.org/10.1007/978-3-030-78468-3_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78468-3_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78467-6

  • Online ISBN: 978-3-030-78468-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation