Computerized adaptive testing as a tool for assessment and preparation for Enade

Abstract

This thesis investigated the impact of using Computerized Adaptive Testing (CAT) on the perception and acceptance of students in Computing Education programs regarding their preparation for the National Student Performance Exam (Enade). The research stems from the observation that many students face difficulties in engagement and motivation during exam preparation, as well as a possible disconnection between classroom teaching and the assessment format. Considering the strategic role of Enade within the National Higher Education Evaluation System (SINAES), the central problem addressed is the search for technological strategies that make the exam preparation process more personalized, motivating, and effective. To address this issue, the study proposed and developed a solution based on an adaptive model that integrates CAT logic with the Elo rating system, implemented in the Questione platform. The investigation followed the principles of the Design Science Research Methodology (DSRM), encompassing the stages from problem identification to the development, demonstration, and evaluation of the artifact. The proposed model was validated through an empirical study that compared student performance and perception in fixed and adaptive mock exams, using the Technology Acceptance Model (TAM) as the theoretical basis for acceptance analysis. The results showed that, although the average performance was slightly lower in adaptive mock exams (due to the higher level of question difficulty) students demonstrated greater acceptance, with significant improvements in the dimensions of perceived usefulness, attitude, and intention to use. The study concludes that the adaptive model positively impacts student acceptance and represents an alternative for personalizing Enade preparation, contributing both methodologically and technologically to the field of large-scale adaptive assessment. Future directions include the automated expansion of the question bank supported by language models, the use of multidimensional adaptive models, and the enhancement of accessibility in adaptive educational contexts.