Resumo:
This study developed and evaluated a decision-support tool for academic managers, utilizing
NLP for textual data analysis and information visualization techniques. In the academic
context, interpreting qualitative data generated from responses to the CPA (Comissão
Própria de Avaliação) self-assessment questionnaire poses significant challenges due to
the complexity and volume of this data. To address these challenges, the DSRM (Design
Science Research Methodology) methodology was applied across three development cycles,
resulting in the artifact Analisa CPA, featuring functionalities tailored to the context of
institutional management. The artifact identified the sentiments and emotions of comments,
in addition to providing data visualizations adapted to different manager profiles, such
as directors and members of the Rectory and the CPA. An evaluation through interviews
with managers validated the positive impact of the solution, demonstrating that data-driven
tools enhance decision-making in this environment. It is concluded that the tool facilitates
the decision-making process, offering an accessible and functional interface that meets the
needs of academic managers.
