Abstract
Computer Science degrees are often seen as challenging by students, especially in what concerns subjects such as programming, data structures or algorithms. Many reasons can be pointed out for this, some of which related to the abstract nature of these subjects and the lack of previous related knowledge by the students. In this paper we tackle this challenge using gamification in the teaching/learning process, with two main goals in mind. The first is to increase the intrinsic motivation of students to learn, by making the whole process more fun, enjoyable and competitive. The second is to facilitate the learning process by providing intuitive tools for the visualization of data structures and algorithmic output, together with a tool for automated assessment that decreases the dependence on the teacher and allows them to work more autonomously. We validated this approach over the course of three academic years in a Computer Science degree of the Polytechnic of Porto, Portugal, through the use of a questionnaire. Results show that the effects of using games and game elements have a generally positive effect on motivation and on the overall learning process.
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References
Ahmad, A., Zeshan, F., Khan, M.S., Marriam, R., Ali, A., Samreen, A.: The impact of gamification on learning outcomes of computer science majors. ACM Trans. Comput. Educ. (TOCE) 20(2), 1–25 (2020)
Aho Alfred, V., et al.: Data Structures and Algorithms. Addison-Wesley, Boston (1983)
Biernat, M.J.: Teaching tools for data structures and algorithms. ACM SIGCSE Bull. 25(4), 9–12 (1993)
Carneiro, D., Barbosa, R.: A framework for online education in computer science degrees with a focus on motivation. In: De la Prieta, F., et al. (eds.) MIS4TEL 2021. LNNS, vol. 326, pp. 137–146. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-86618-1_14
Carneiro, D.R., Silva, R.J.: Game elements, motivation and programming learning: a case study. In: First International Computer Programming Education Conference (ICPEC 2020). Schloss Dagstuhl-Leibniz-Zentrum für Informatik (2020)
Dijkstra, E.W., et al.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959)
Draft, S.: Computer Science Curricula 2013. ACM and IEEE Computer Society, Incorporated, New York (2013)
Floyd, R.W.: Algorithm 97: shortest path. Commun. ACM 5(6), 345 (1962)
Gross, J.L., Yellen, J., Anderson, M.: Graph Theory and Its Applications. Chapman and Hall/CRC, London (2018)
Ibanez, M.B., Di-Serio, A., Delgado-Kloos, C.: Gamification for engaging computer science students in learning activities: a case study. IEEE Trans. Learn. Technol. 7(3), 291–301 (2014)
Kruskal, J.B.: On the shortest spanning subtree of a graph and the traveling salesman problem. Proc. Am. Math. Soc. 7(1), 48–50 (1956)
Prim, R.C.: Shortest connection networks and some generalizations. Bell Syst. Tech. J. 36(6), 1389–1401 (1957)
Siklóssy, L., Rich, A., Marinov, V.: Breadth-first search: some surprising results. Artif. Intell. 4(1), 1–27 (1973)
Su, S., Zhang, E., Denny, P., Giacaman, N.: A game-based approach for teaching algorithms and data structures using visualizations. In: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, pp. 1128–1134 (2021)
Tarjan, R.: Depth-first search and linear graph algorithms. SIAM J. Comput. 1(2), 146–160 (1972)
Vallerand, R.J., Pelletier, L.G., Blais, M.R., Briere, N.M., Senecal, C., Vallieres, E.F.: The academic motivation scale: a measure of intrinsic, extrinsic, and amotivation in education. Educ. Psychol. Measur. 52(4), 1003–1017 (1992)
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This work has been supported by national funds through FCT - Fundação para a Ciência e Tecnologia through project UIDB/04728/2020.
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Carneiro, D., Carvalho, M. (2023). Teaching Data Structures and Algorithms Through Games. In: Kubincová, Z., Melonio, A., Durães, D., Rua Carneiro, D., Rizvi, M., Lancia, L. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning, Workshops, 12th International Conference. MIS4TEL 2022. Lecture Notes in Networks and Systems, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-031-20257-5_1
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