A Motivation-Aware Diagnostic Instrument for Personalized and Gamified Computing Education
Resumo
Semester-start evidence can inform instructional adaptation before disengagement or low performance becomes visible. This paper presents a preliminary empirical assessment of a motivation-aware diagnostic instrument used in three undergraduate computing courses, with 245 valid responses: 81 from Human–Computer Interaction, 133 from Compilers, and 31 from Introduction to Gamification. The instrument combines course-specific self-assessments of prior knowledge with common blocks on instructional perceptions, challenge, autonomy, performance expectations, social connection, curiosity, and course motivation. The study positions the instrument as a screening and planning aid rather than a validated psychometric scale or an automatic intervention engine. The combined common-item subset showed preliminary internal consistency (α = 0.880). Small-sample reliability estimates were treated as exploratory, and selected correlations were reported with confidence intervals. The main contribution is an operational protocol that links diagnostic patterns to universal, targeted, and short-cycle instructional responses, including feasible options for heterogeneous classes and constrained computing curricula.
Palavras-chave:
Computing education, Diagnostic assessment, Gamification, Motivation, Learning analytics, Personalized learning
Referências
Aho, A. V., Lam, M. S., Sethi, R., and Ullman, J. D. (2006). Compilers: Principles, Techniques, and Tools. Pearson/Addison-Wesley, Boston, MA, 2 edition.
Ali, M., Ghosh, S., Rao, P., Dhegaskar, R., Jawort, S., Medler, A., Shi, M., and Dasgupta, S. (2023). Taking stock of concept inventories in computing education: A systematic literature review. In Proceedings of the 2023 ACM Conference on International Computing Education Research - Volume 1, pages 397–415. ACM.
Barbosa, P. L. S., do Carmo, R. A. F., Gomes, J. P. P., and Viana, W. (2024). Adaptive learning in computer science education: A scoping review. Education and Information Technologies, 29:9139–9188.
Bernacki, M. L., Greene, J. A., and Lobczowski, N. G. (2021). A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose(s)? Educational Psychology Review, 33:1675–1715.
Black, P. and Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1):7–74.
Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11:87–110.
Caponetto, I., Earp, J. M., and Ott, M. (2014). Gamification and education: A literature review. In Proceedings of the 8th European Conference on Games Based Learning, pages 50–57.
Chou, Y.-k. (2015). Actionable Gamification: Beyond Points, Badges, and Leaderboards. CreateSpace Independent Publishing Platform.
de Freitas, S. A. A., Farias, M. A. S., Ramos, C. S., Martins, M. V. P., Alves, J. M., and Pinto, L. C. S. (2024a). Crafting personalized learning environments through motivational profiling. In 2024 IEEE Frontiers in Education Conference (FIE), pages 1–9. IEEE.
de Freitas, S. A. A., Ramos, C. S., Bessa, E., Mortari, M. R., and Viana, D. M. (2024b). Implementing neuroscientific principles in gamified software engineering courses. In 2024 IEEE Frontiers in Education Conference (FIE), pages 1–9. IEEE.
Dehghanzadeh, H., Farrokhnia, M., Dehghanzadeh, H., Taghipour, K., and Noroozi, O. (2024). Using gamification to support learning in K–12 education: A systematic literature review. British Journal of Educational Technology, 55(1):34–70.
Deterding, S., Dixon, D., Khaled, R., and Nacke, L. (2011). From game design elements to gamefulness: Defining gamification. In Proceedings of the 15th International Academic MindTrek Conference, pages 9–15.
Dinçer, S. (2020). The effects of materials based on ARCS model on motivation: A meta-analysis. Elementary Education Online, 19(2):1016–1042.
Fang, X., Ng, D. T. K., Leung, J. K. L., and Xu, H. (2024). The applications of the ARCS model in instructional design, theoretical framework, and measurement tool: A systematic review of empirical studies. Interactive Learning Environments, 32(10):5919–5946.
Göksu, I. and Bolat, Y. I. (2021). Does the ARCS motivational model affect students' achievement and motivation? a meta-analysis. Review of Education, 9(1):27–52.
Hamari, J., Koivisto, J., and Sarsa, H. (2014). Does gamification work? A literature review of empirical studies on gamification. In 2014 47th Hawaii International Conference on System Sciences, pages 3025–3034.
Hunicke, R., LeBlanc, M., and Zubek, R. (2004). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI.
Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19(4):509–539.
Keller, J. M. (2010). Motivational Design for Learning and Performance: The ARCS Model Approach. Springer.
Lavoué, E., Monterrat, B., Desmarais, M., and George, S. (2019). Adaptive gamification for learning environments. IEEE Transactions on Learning Technologies, 12(1):16–28.
Malkewitz, C. P., Schwall, P., Meesters, C., and Hardt, J. (2023). Estimating reliability: A comparison of Cronbach's alpha, McDonald's omega t and the greatest lower bound. Social Sciences & Humanities Open, 7(1):100368.
Mislevy, R. J., Steinberg, L. S., and Almond, R. G. (2003). On the structure of educational assessments. Measurement: Interdisciplinary Research and Perspectives, 1(1):3–62.
Pellegrino, J. W., Chudowsky, N., and Glaser, R. (2001). Knowing What Students Know: The Science and Design of Educational Assessment. National Academies Press, Washington, DC.
Rodrigues, L. A. L., Palomino, P. T., Toda, A. M., Klock, A. C. T., Pessoa, M. S. P., Pereira, F. D., Oliveira, E. H. T., Oliveira, D. F., Cristea, A. I., Gasparini, I., and Isotani, S. (2024). How personalization affects motivation in gamified review assessments. International Journal of Artificial Intelligence in Education, 34:147–184.
Rogers, Y., Sharp, H., and Preece, J. (2023). Interaction Design: Beyond Human-Computer Interaction. John Wiley & Sons, Hoboken, NJ, 6 edition.
Ryan, R. M. and Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1):68–78.
Ryan, R. M., Mims, V., and Koestner, R. (1983). Relation of reward contingency and interpersonal context to intrinsic motivation: A review and test using cognitive evaluation theory. Journal of Personality and Social Psychology, 45(4):736–750.
Smale-Jacobse, A. E., Meijer, A., Helms-Lorenz, M., and Maulana, R. (2019). Differentiated instruction in secondary education: A systematic review of research evidence. Frontiers in Psychology, 10:2366.
Tavakol, M. and Dennick, R. (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, 2:53–55.
Tomlinson, C. A. (2017). How to Differentiate Instruction in Academically Diverse Classrooms. ASCD, Alexandria, VA, 3 edition.
Werbach, K. and Hunter, D. (2012). For the Win: How Game Thinking Can Revolutionize Your Business. Wharton Digital Press.
Zeybek, N. and Saygı, E. (2024). Gamification in education: Why, where, when, and how? A systematic review. Games and Culture, 19(2):237–264.
Ali, M., Ghosh, S., Rao, P., Dhegaskar, R., Jawort, S., Medler, A., Shi, M., and Dasgupta, S. (2023). Taking stock of concept inventories in computing education: A systematic literature review. In Proceedings of the 2023 ACM Conference on International Computing Education Research - Volume 1, pages 397–415. ACM.
Barbosa, P. L. S., do Carmo, R. A. F., Gomes, J. P. P., and Viana, W. (2024). Adaptive learning in computer science education: A scoping review. Education and Information Technologies, 29:9139–9188.
Bernacki, M. L., Greene, J. A., and Lobczowski, N. G. (2021). A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose(s)? Educational Psychology Review, 33:1675–1715.
Black, P. and Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1):7–74.
Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11:87–110.
Caponetto, I., Earp, J. M., and Ott, M. (2014). Gamification and education: A literature review. In Proceedings of the 8th European Conference on Games Based Learning, pages 50–57.
Chou, Y.-k. (2015). Actionable Gamification: Beyond Points, Badges, and Leaderboards. CreateSpace Independent Publishing Platform.
de Freitas, S. A. A., Farias, M. A. S., Ramos, C. S., Martins, M. V. P., Alves, J. M., and Pinto, L. C. S. (2024a). Crafting personalized learning environments through motivational profiling. In 2024 IEEE Frontiers in Education Conference (FIE), pages 1–9. IEEE.
de Freitas, S. A. A., Ramos, C. S., Bessa, E., Mortari, M. R., and Viana, D. M. (2024b). Implementing neuroscientific principles in gamified software engineering courses. In 2024 IEEE Frontiers in Education Conference (FIE), pages 1–9. IEEE.
Dehghanzadeh, H., Farrokhnia, M., Dehghanzadeh, H., Taghipour, K., and Noroozi, O. (2024). Using gamification to support learning in K–12 education: A systematic literature review. British Journal of Educational Technology, 55(1):34–70.
Deterding, S., Dixon, D., Khaled, R., and Nacke, L. (2011). From game design elements to gamefulness: Defining gamification. In Proceedings of the 15th International Academic MindTrek Conference, pages 9–15.
Dinçer, S. (2020). The effects of materials based on ARCS model on motivation: A meta-analysis. Elementary Education Online, 19(2):1016–1042.
Fang, X., Ng, D. T. K., Leung, J. K. L., and Xu, H. (2024). The applications of the ARCS model in instructional design, theoretical framework, and measurement tool: A systematic review of empirical studies. Interactive Learning Environments, 32(10):5919–5946.
Göksu, I. and Bolat, Y. I. (2021). Does the ARCS motivational model affect students' achievement and motivation? a meta-analysis. Review of Education, 9(1):27–52.
Hamari, J., Koivisto, J., and Sarsa, H. (2014). Does gamification work? A literature review of empirical studies on gamification. In 2014 47th Hawaii International Conference on System Sciences, pages 3025–3034.
Hunicke, R., LeBlanc, M., and Zubek, R. (2004). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI.
Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19(4):509–539.
Keller, J. M. (2010). Motivational Design for Learning and Performance: The ARCS Model Approach. Springer.
Lavoué, E., Monterrat, B., Desmarais, M., and George, S. (2019). Adaptive gamification for learning environments. IEEE Transactions on Learning Technologies, 12(1):16–28.
Malkewitz, C. P., Schwall, P., Meesters, C., and Hardt, J. (2023). Estimating reliability: A comparison of Cronbach's alpha, McDonald's omega t and the greatest lower bound. Social Sciences & Humanities Open, 7(1):100368.
Mislevy, R. J., Steinberg, L. S., and Almond, R. G. (2003). On the structure of educational assessments. Measurement: Interdisciplinary Research and Perspectives, 1(1):3–62.
Pellegrino, J. W., Chudowsky, N., and Glaser, R. (2001). Knowing What Students Know: The Science and Design of Educational Assessment. National Academies Press, Washington, DC.
Rodrigues, L. A. L., Palomino, P. T., Toda, A. M., Klock, A. C. T., Pessoa, M. S. P., Pereira, F. D., Oliveira, E. H. T., Oliveira, D. F., Cristea, A. I., Gasparini, I., and Isotani, S. (2024). How personalization affects motivation in gamified review assessments. International Journal of Artificial Intelligence in Education, 34:147–184.
Rogers, Y., Sharp, H., and Preece, J. (2023). Interaction Design: Beyond Human-Computer Interaction. John Wiley & Sons, Hoboken, NJ, 6 edition.
Ryan, R. M. and Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1):68–78.
Ryan, R. M., Mims, V., and Koestner, R. (1983). Relation of reward contingency and interpersonal context to intrinsic motivation: A review and test using cognitive evaluation theory. Journal of Personality and Social Psychology, 45(4):736–750.
Smale-Jacobse, A. E., Meijer, A., Helms-Lorenz, M., and Maulana, R. (2019). Differentiated instruction in secondary education: A systematic review of research evidence. Frontiers in Psychology, 10:2366.
Tavakol, M. and Dennick, R. (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, 2:53–55.
Tomlinson, C. A. (2017). How to Differentiate Instruction in Academically Diverse Classrooms. ASCD, Alexandria, VA, 3 edition.
Werbach, K. and Hunter, D. (2012). For the Win: How Game Thinking Can Revolutionize Your Business. Wharton Digital Press.
Zeybek, N. and Saygı, E. (2024). Gamification in education: Why, where, when, and how? A systematic review. Games and Culture, 19(2):237–264.
Publicado
05/10/2026
Como Citar
DE FREITAS, Sergio Antônio Andrade; DA ROCHA, Daniel Rodrigues; DA ROCHA, Davi Rodrigues; FARIAS, Mylena Angélica Silva.
A Motivation-Aware Diagnostic Instrument for Personalized and Gamified Computing Education. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 37. , 2026, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 662-676.
DOI: https://doi.org/10.5753/sbie.2026.27258.
