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.
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References
Aho, A.V.: Estructuras de datos y algoritmos. Addison-Wesley, México (1988)
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)
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
Becker, K.: Choosing and Using Digital Games in the Classroom. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-12223-6
Biggs, J., Tang, C.: Teaching for Quality Learning at University. Open University Press, New York (2007)
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
Calleja, G.: Digital game involvement: a conceptual model. Games and Cult. 2(3), 236–260 (2007). https://doi.org/10.1177/1555412007306206
Campbell, J.: The Hero’s Journey, p. 10022. Harpercollins, New York (1991)
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
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)
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)
Duit, R.: On the role of analogies and metaphors in learning science. Sci. Educ. 75(6), 649–672 (1991)
Fleury, A.E.: Parameter passing: the rules the students construct. SIGCSE Bull. 23(1), 283–286 (1991)
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)
Glynn, S.M.: Teaching Science with Analogies: A Strategy for Teachers and Textbook Authors. Reading Research Report No. 15. ERIC (1994)
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
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
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)
Kapp, K.M.: The Gamification of Learning and Instruction : Game-Based Methods and Strategies for Training and Education. Pfeiffer, United States of America (2012)
Kolb, D.A.: Experiential Learning: Experience as the Source of Learning and Development. Pearson, New Jersey (2014)
Lazar, J., et al.: Research Methods in Human-Computer Interaction. Morgan Kaufmann Publishers, Cambridge (2017)
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)
Mayes, T., de Freitas, S.: Review of e-learning theories, frameworks and models. Joint Information Systems Committee, London (2004)
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
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)
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)
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
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
Qian, Y., Lehman, J.: Students’ misconceptions and other difficulties in introductory programming: a literature review. ACM Trans. Comput. Educ. 18, 1, Article 1 (2017)
Randolph, J.J., et al.: A methodological review of computer science education research. J. Inf. Technol. Educ. Res. 7(1), 135–162 (2008)
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)
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
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
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)
Sedgewick, R., Wayne, K.: Algorithms. Addison-Wesley, Boston (2014)
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
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
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
Squire, K.: Video Games and Learning: Teaching and Participatory Culture in the Digital Age. Teachers College Press, New York (2011)
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
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
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
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
Whitton, N.: Digital Games and Learning: Research and Theory. Routledge, New York (2014)
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
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)
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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
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