Building a specialist agent to assist in the implementation of Game Learning Analytics techniques - Honda, Fabrizio; Pires, Fernanda; Pessoa, Marcela; Oliveira, Elaine H. T. (Anais do Simpósio Brasileiro de Informática na Educação (SBIE); 2024: Anais do XXXV Simpósio Brasileiro de Informática na EducaçãoDO - 10.5753/sbie.2024.244936, 2024)
Game Learning Analytics (GLA) involves capturing and analyzing data from educational games, enabling the identification of evidence of learning. A fundamental step before implementing GLA techniques is data modeling, which is not trivial. Using large language models (LLMs) can help in this context, as they can generate text like humans. Therefore, considering Chat-GPT and its customizable functionality, “MyGPTs,” this work proposes creating a specialist agent to assist learning designers in data modeling and implementing GLA techniques based on the GLBoard system. Preliminary results with GLA specialists were positive, indicating the agent’s potential.