Work

Building a specialist agent to assist in the implementation of Game Learning Analytics techniques

Year: 2024

Type: conference-paper

Abstract: 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.

DOI: 10.5753/sbie.2024.244936

Authors: Fabrizio Honda, Fernanda Pires, Marcela Pessoa, Elaine H. T. Oliveira

Institutions: Universidade Federal do Amazonas, Universidade do Estado do Amazonas

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado do Amazonas

OpenAlex ID: W4404849745

FWCI: 2.233

Cites: 18

Cited by: 5

Related to: 10