SAGE: A dataset for Smart Adaptive Gamified Education

  • Armando Toda Durham University / USP
  • Luiz Rodrigues SENAI PR University Center
  • Paula T. Palomino FATEC
  • Ana C. T. Klock Tampere University
  • Filipe D. Pereira UFRR
  • Elaine H. T. de Oliveira UFAM
  • Isabela Gasparini UDESC
  • Seiji Isotani Harvard Graduate School of Education
  • Alexandra I. Cristea Durham University


Gamification design in education is the process of planning gamification strategies aligned with educational needs. However, the literature states that generating those strategies is not trivial, and it requires a lot of effort from gamification designers and educators due to the large number of game elements, especially since some of these elements are defined in confusing or misleading ways, context specificities in the teaching-learning processes, and the interaction between them. Based on this premise, this paper presents the design and data collection of a dataset composed of 1929 items (line entries in the dataset). This dataset was made through a survey data that went through a data filtering process and can be used to support tailored gamified tools or AI-based tools (e.g., recommendation systems) for educational environments, based on students’ profiles and favorite game elements.


Bai, S., Hew, K. F., and Huang, B. (2020). Does gamification improve student learning outcome? evidence from a meta-analysis and synthesis of qualitative data in educational contexts. Educational Research Review, 30.

Bentley, F., Neill, K. O., Quehl, K., and Lottridge, D. (2020). Exploring the quality , efficiency , and representative nature of responses across multiple survey panels. pages 1–12. ACM.

Cordova, K. A., Klock, A. C. T., and Gasparini, I. (2022). Rumo à concepção de diretrizes para design da gamificação sob a ótica da ihc feminista. In Anais Estendidos do XXI Simpósio Brasileiro de Fatores Humanos em Sistemas Computacionais, pages 116– 119. SBC.

De-Marcos, L., Garcia-Lopez, E., and Garcia-Cabot, A. (2016). On the effectiveness of game-like and social approaches in learning: Comparing educational gaming, gamification & social networking. Computers & Education, 95:99–113.

Deterding, S., Sicart, M., Nacke, L., O’Hara, K., and Dixon, D. (2011). From game design elements to gamefulness: Defining ”gamification”. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems - CHI EA ’11, page 2425.

Harilal, A., Toffalini, F., Homoliak, I., Castellanos, J. H., Guarnizo, J., Mondal, S., and Ochoa, M. (2018). The wolf of sutd (twos): A dataset of malicious insider threat behavior based on a gamified competition. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 9(1):54–85.

Klock, A. C. T., Gasparini, I., Pimenta, M. S., and Hamari, J. (2020). Tailored gamification: A review of literature. International Journal of Human-Computer Studies, page 102495.

Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Research methods in human-computer interaction. Morgan Kaufmann, 2nd edition.

Meder, M., Plumbaum, T., and Albayrak, S. (2017). A primer on data-driven gamification design.

Mora, A., Riera, D., González, C., and Arnedo-Moreno, J. (2017). Gamification: a systematic review of design frameworks. Journal of Computing in Higher Education.

Palomino, P. T., Toda, A., Oliveira, W., Rodrigues, L., Cristea, A. I., and Isotani, S. (2019). Exploring content game elements to support gamification design in educational systems : Narrative and storytelling. pages 773 – 782.

Palomino, P. T., Toda, A. M., Rodrigues, L., Oliveira, W., and Isotani, S. (2020). From the lack of engagement to motivation: Gamification strategies to enhance users learning experiences. SBC – Proceedings of SBGames 2020, pages 1127–1130.

Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Pessoa, M., Pereira, F. D., Oliveira, E. H., Oliveira, D. F., Cristea, A. I., Gasparini, I., et al. (2023). How personalization affects motivation in gamified review assessments. International Journal of Artificial Intelligence in Education, pages 1–38.

Rodrigues, L., Toda, A. M., Palomino, P. T., Oliveira, W., and Isotani, S. (2020). Personalized gamification: A literature review of outcomes, experiments, and approaches. ACM International Conference Proceeding Series, pages 699–706.

Spiel, K., Haimson, O. L., and Lottridge, D. (2019). How to do better with gender on surveys: a guide for hci researchers. Interactions, 26(4):62–65.

Tavakol, M. and Dennick, R. (2011). Making sense of cronbach’s alpha. International journal of medical education, 2:53.

Toda, A., Pereira, F. D., Klock, A. C. T., Rodrigues, L., Palomino, P., Oliveira, W., Oliveira, E. H. T., Gasparini, I., Cristea, A. I., and Isotani, S. (2020). For whom should we gamify? insights on the users intentions and context towards gamification in education. pages 471–480.

Toda, A. M., Klock, A. C. T., Oliveira, W., Palomino, P. T., Rodrigues, L. L., Shi, L., Bittencourt, I., Gasparini, I., Isotani, S., and Cristea, A. I. (2019). Analysing gamification elements in educational environments – using an existing gamification taxonomy. Smart Learning Environments, 6:16.
TODA, Armando et al. SAGE: A dataset for Smart Adaptive Gamified Education. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 34. , 2023, Passo Fundo/RS. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 1098-1108. DOI: