Skip to main content

Evaluating Learning Outcomes and Intrinsic Motivation: A Case Study of DS-Hacker 3D

  • Conference paper
  • First Online:
Serious Games (JCSG 2023)

Abstract

This paper presents a comprehensive evaluation of an educational video game, DS-Hacker 3D, that incorporates analogies to enhance the learning of conceptual knowledge in computer science, specifically Binary Search Tree (BST) concepts. The study addresses the challenges students face in understanding complex computer science topics and the limited availability of well-evaluated educational video games in the field. DS-Hacker 3D targets undergraduate students and follows a constructivist learning approach, establishing connections between new information and familiar knowledge through analogies. The evaluation includes validated assessment tools to measure learning outcomes and intrinsic motivation. The results demonstrate the effectiveness of the educational video game in facilitating the acquisition of BST conceptual knowledge and promoting intrinsic motivation. The study contributes to the development of educational video games for teaching computer science concepts.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
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. Aho, A.V.: Estructuras de datos y algoritmos. Addison-Wesley, México (1988)

    Google Scholar 

  2. Association for Computing Machinery (ACM) Joint Task Force on Computing Curricula, IEEE Computer Society: Computer Science Curricula 2013: Curriculum Guidelines for Undergraduate Degree Programs in Computer Science. ACM, New York (2013)

    Google Scholar 

  3. Aubusson, P.J., et al.: Metaphor and analogy. In: Aubusson, P.J., et al. (eds.) Metaphor and Analogy in Science Education, pp. 1–9. Springer, Dordrecht (2006). https://doi.org/10.1007/1-4020-3830-5_1

    Chapter  Google Scholar 

  4. Becker, K.: Choosing and Using Digital Games in the Classroom. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-12223-6

    Book  Google Scholar 

  5. Biggs, J., Tang, C.: Teaching for Quality Learning at University. Open University Press, New York (2007)

    Google Scholar 

  6. Boyle, E.A., et al.: Engagement in digital entertainment games: a systematic review. Comput. Hum. Behav. 28(3), 771–780 (2012). https://doi.org/10.1016/j.chb.2011.11.020

    Article  Google Scholar 

  7. Calleja, G.: Digital game involvement: a conceptual model. Games and Cult. 2(3), 236–260 (2007). https://doi.org/10.1177/1555412007306206

    Article  Google Scholar 

  8. Campbell, J.: The Hero’s Journey, p. 10022. Harpercollins, New York (1991)

    Google Scholar 

  9. Chaffin, A., et al.: Experimental evaluation of teaching recursion in a video game. In: Proceedings of the 2009 ACM SIGGRAPH Symposium on Video Games, pp. 79–86. ACM, New York (2009). https://doi.org/10.1145/1581073.1581086

  10. Danielsiek, H., et al.: Detecting and understanding students’ misconceptions related to algorithms and data structures. In: Proceedings of the 43rd ACM technical symposium on Computer Science Education, pp. 21–26 Association for Computing Machinery, Raleigh (2012)

    Google Scholar 

  11. Doukakis, D., et al.: Using animated interactive analogies in teaching basic programming concepts and structures. In: Proceedings of the Informatics Education Europe II Conference IEEII 2007, Thessaloniki, Greece (2007)

    Google Scholar 

  12. Duit, R.: On the role of analogies and metaphors in learning science. Sci. Educ. 75(6), 649–672 (1991)

    Google Scholar 

  13. Fleury, A.E.: Parameter passing: the rules the students construct. SIGCSE Bull. 23(1), 283–286 (1991)

    Article  Google Scholar 

  14. Frasca, G.: Simulation versus narrative: introduction to ludology. In: Wolf, M.J.P., Perron, B. (eds.) The Video Game Theory Reader. Routledge, New York (2003)

    Google Scholar 

  15. Glynn, S.M.: Teaching Science with Analogies: A Strategy for Teachers and Textbook Authors. Reading Research Report No. 15. ERIC (1994)

    Google Scholar 

  16. Hays, R.T., Singer, M.J.: Simulation fidelity as an organizing concept. In: Hays, R.T., Singer, M.J. (eds.) Simulation Fidelity in Training System Design: Bridging the Gap Between Reality and Training, pp. 47–75. Springer, New York (1989). https://doi.org/10.1007/978-1-4612-3564-4_3

    Chapter  Google Scholar 

  17. Jiménez-Hernández, E.M., et al.: Using a serious video game to support the learning of tree traversals. In: 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT), pp. 238–244 (2021). https://doi.org/10.1109/CONISOFT52520.2021.00040

  18. Kaczmarczyk, L.C., et al.: Identifying student misconceptions of programming. In: Proceedings of the 41st ACM Technical Symposium on Computer Science Education, pp. 107–111. Association for Computing Machinery, Milwaukee (2010)

    Google Scholar 

  19. Kapp, K.M.: The Gamification of Learning and Instruction : Game-Based Methods and Strategies for Training and Education. Pfeiffer, United States of America (2012)

    Google Scholar 

  20. Kolb, D.A.: Experiential Learning: Experience as the Source of Learning and Development. Pearson, New Jersey (2014)

    Google Scholar 

  21. Lazar, J., et al.: Research Methods in Human-Computer Interaction. Morgan Kaufmann Publishers, Cambridge (2017)

    Google Scholar 

  22. Malone, T.W.: What makes things fun to learn? Heuristics for designing instructional computer games. In: Proceedings of the 3rd ACM SIGSMALL Symposium and the First SIGPC Symposium on Small Systems, pp. 162–169. ACM, Palo Alto (1980)

    Google Scholar 

  23. Mayes, T., de Freitas, S.: Review of e-learning theories, frameworks and models. Joint Information Systems Committee, London (2004)

    Google Scholar 

  24. McAuley, E., et al.: Psychometric properties of the intrinsic motivation inventory in a competitive sport setting: a confirmatory factor analysis. Res. Q. Exerc. Sport 60(1), 48–58 (1989). https://doi.org/10.1080/02701367.1989.10607413

    Article  MathSciNet  Google Scholar 

  25. McCracken, M., et al.: A multi-national, multi-institutional study of assessment of programming skills of first-year CS students. In: Working Group Reports from ITiCSE on Innovation and Technology in Computer Science Education, pp. 125–180. Association for Computing Machinery, Canterbury (2001)

    Google Scholar 

  26. Parsons, S., et al.: Psychological science needs a standard practice of reporting the reliability of cognitive-behavioral measurements. Adv. Methods Pract. Psychol. Sci. 2(4), 378–395 (2019)

    Article  Google Scholar 

  27. Petri, G., Gresse von Wangenheim, C.: How games for computing education are evaluated? A systematic literature review. Comput. Educ. 107(C), 68–90 (2017). https://doi.org/10.1016/j.compedu.2017.01.004

  28. Podolefsky, N.S., Finkelstein, N.D.: Use of analogy in learning physics: the role of representations. Phys. Rev. ST Phys. Educ. Res. 2(2), 020101 (2006). https://doi.org/10.1103/PhysRevSTPER.2.020101

  29. Qian, Y., Lehman, J.: Students’ misconceptions and other difficulties in introductory programming: a literature review. ACM Trans. Comput. Educ. 18, 1, Article 1 (2017)

    Google Scholar 

  30. Randolph, J.J., et al.: A methodological review of computer science education research. J. Inf. Technol. Educ. Res. 7(1), 135–162 (2008)

    Google Scholar 

  31. Rojas-Salazar, A.: Game-based learning of data structures based on analogies: learning gains and intrinsic motivation in higher education environments. Trinity College Dublin (2022)

    Google Scholar 

  32. Rojas-Salazar, A., Haahr, M.: Theoretical foundations and evaluations of serious games for learning data structures and recursion: a review. In: Ma, M., et al. (eds.) Serious Games. Lecture Notes in Computer Science, vol. 12434, pp. 135–149. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-61814-8_11

    Chapter  Google Scholar 

  33. Ryan, R.M.: Control and information in the intrapersonal sphere: an extension of cognitive evaluation theory. J. Pers. Soc. Psychol. 43(3), 450–461 (1982). https://doi.org/10.1037/0022-3514.43.3.450

    Article  Google Scholar 

  34. Sanders, K., et al.: Inferential statistics in computing education research: a methodological review. In: Proceedings of the 2019 ACM Conference on International Computing Education Research, pp. 177–185. Association for Computing Machinery, Toronto (2019)

    Google Scholar 

  35. Sedgewick, R., Wayne, K.: Algorithms. Addison-Wesley, Boston (2014)

    Google Scholar 

  36. Shabanah, S.S., et al.: Designing computer games to teach algorithms. In: 2010 Seventh International Conference on Information Technology: New Generations, pp. 1119–1126 (2010). https://doi.org/10.1109/ITNG.2010.78

  37. Sirkiä, T., Sorva, J.: Exploring programming misconceptions: an analysis of student mistakes in visual program simulation exercises. In: Proceedings of the 12th Koli Calling International Conference on Computing Education Research, pp. 19–28. Association for Computing Machinery, New York (2012). https://doi.org/10.1145/2401796.2401799

  38. Sleeman, D., et al.: Pascal and high school students: a study of errors. J. Educ. Comput. Res. 2(1), 5–23 (1986). https://doi.org/10.2190/2XPP-LTYH-98NQ-BU77

    Article  Google Scholar 

  39. Squire, K.: Video Games and Learning: Teaching and Participatory Culture in the Digital Age. Teachers College Press, New York (2011)

    Google Scholar 

  40. Šuníková, D. et al.: A mobile game to teach AVL trees. In: 2018 16th International Conference on Emerging eLearning Technologies and Applications (ICETA), pp. 541–544 (2018). https://doi.org/10.1109/ICETA.2018.8572263

  41. Taylor, C., et al.: Computer science concept inventories: past and future. Comput. Sci. Educ. 24(4), 253–276 (2014). https://doi.org/10.1080/08993408.2014.970779

    Article  Google Scholar 

  42. Touré‐Tillery, M., Fishbach, A.: How to measure motivation: a guide for the experimental social psychologist. Soc. Pers. Psychol. Compass. 8 (2014). https://doi.org/10.1111/spc3.12110

  43. Wassila, D., Tahar, B.: Using serious game to simplify algorithm learning. In: International Conference on Education and e-Learning Innovations, pp. 1–5 (2012). https://doi.org/10.1109/ICEELI.2012.6360569

  44. Whitton, N.: Digital Games and Learning: Research and Theory. Routledge, New York (2014)

    Book  Google Scholar 

  45. Yee, N.: Motivations for play in online games. J. CyberPsychol. Behav. 9(6), 772–775 (2006). https://doi.org/10.1089/cpb.2006.9.772

    Article  Google Scholar 

  46. Zingaro, D. et al.: Identifying student difficulties with basic data structures. In: Proceedings of the 2018 ACM Conference on International Computing Education Research, pp. 169–177. Association for Computing Machinery, Espoo (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alberto Rojas-Salazar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Rojas-Salazar, A., Rojas-Salazar, J., Haahr, M. (2023). Evaluating Learning Outcomes and Intrinsic Motivation: A Case Study of DS-Hacker 3D. In: Haahr, M., Rojas-Salazar, A., Göbel, S. (eds) Serious Games. JCSG 2023. Lecture Notes in Computer Science, vol 14309. Springer, Cham. https://doi.org/10.1007/978-3-031-44751-8_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-44751-8_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-44750-1

  • Online ISBN: 978-3-031-44751-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics