Artificial intelligence applied in problem-oriented learning, to recover information in a game environment, on the knowledge track of public technology procurement, from the perspective of risk management

Abstract

Objective: Allow information retrieval, on the topic of technology bidding, with simulations generated by Artificial Intelligence, using gamification (game), from a risk management perspective, to increase student engagement and learning, in Brazilian government environments.
Methodology: Quantitative and qualitative research with the following steps: 1) Creation of 1 Case study (with prompt and chatgpt); 2) Application of the game of own design (reading the case studies). 3) Compilation of risks found. 4) Application of the LIKERT Form to assess the risks found. 5) Discussions.
Results: Compared to a traditional classroom, students showed an increase in the perception of learning when a game is used to retrieve information, in the context of public technology purchases.
Conclusions: It was demonstrated that the application of a game adapted to the reality of a public body can increase perception, learning and knowledge in a pre-defined path, which can improve the organization's decision-making process in specific legislation, so improving internal communication to avoid known errors.