Gamification Analytics Model for Teachers

• Kamilla Tenório Universidade Federal de Alagoas
• Diego Dermeval Unversidade Federal de Alagoas https://orcid.org/0000-0002-8415-6955
• Alan Pedro da Silva Universidade Federal de Alagoas

DOI: https://doi.org/10.5753/cbie.wcbie.2020.72

Resumo

Despite the growing interest in applying gamification in the technology-enhanced learning context, previous studies have reported unexpected results concerning students' engagement, learning outcomes, and motivation in gamified learning systems. A possible solution to avoid these unexpected outcomes is the use of the gamification analytics approach, that is the data-driven process of monitoring and adapting gamification designs. Therefore, this dissertation proposes a gamification analytics model for teachers. In this model, the teacher defines interaction goals, monitor students' interaction with the learning resources and the gamification elements, and adapt the gamification design through missions for students that are not achieving the goals. A gamification analytics model-based tool, GamAnalytics, was developed, implementing the most well-rated design concepts validated by teachers through a speed dating method. Teachers evaluated the developed tool where perceived usefulness, perceived ease of use, behavioral intention, relevance, perceived enjoyment, and self-efficacy metrics were measured, and results showed a high acceptance and approval of the tool. Furthermore, to investigate the impact of the use of gamification analytics model by teachers through the GamAnalytics tool on students, a case study was conducted. The results suggest an improvement in students engagement, learning outcomes, and a positive effect on students motivation.

Palavras-chave: Gamification Analytics, Technology-enhanced Learning, Students Engagement, Students Motivation

Referências

Tenório, K., Chalco Challco, G., Dermeval, D., Lemos, B., Nascimento, P., Santos, R.,and Pedro da Silva, A. (2020a). Helping Teachers Assist Their Students in Gamified Adaptive Educational Systems: Towards a Gamification Analytics Tool. In: Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. (eds) Artificial Intelligence in Education. (Org.). Lecture Notes in Computer Science. 1ed.Cham: Springer International Publishing, 2020, v. 12164, p. 312-317.


Tenório, K., Dermeval, D., Monteiro, M., Peixoto, A., and Pedro, A. (2020b). Raising Teachers Empowerment in Gamification Design of Adaptive Learning Systems: A Qualitative Research. In: Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. (eds) Artificial Intelligence in Education. (Org.). Lecture Notes in Computer Science. 1ed. Cham: Springer International Publishing, 2020, v. 12163, p. 524-536.


Tenório, K., Dermeval, D., Chalco Challco, G., Lemos, B., Nascimento, P., Santos, R.,and Pedro da Silva, A. An Evaluation of the GamAnalytics Tool: Is the Gamification Analytics Model Ready for Teachers? (to be published). In: Simpósio Brasileiro de Informática na Educação (Brazilian Symposium on Computers in Education), 2020, Natal. Anais do Simpósio Brasileiro de Informática na Educação, 2020.