SOLO Taxonomy in the Evaluation of Engineering Students: A Case Study in Mathematics

This paper presents the results of a study whose main objective was to analyze the assessments by exam in higher education according to the SOLO Taxonomy (Structure of the Observed Learning Outcome) over the last five years, in particular the cognitive complexity required in each question and the "quality" of the exam. The data were collected in the Mathematical Analysis exams of the Degree in Electrical and Computer Engineering. In total, 130 items presented in 10 exams (2 per year) from 2019 to 2023 were surveyed. The SOLO index of these exams was always higher than 16, with the exception of one exam from 2023 with an index of 14.55. The analysis reveals that the exams are composed of items classified at the highest levels of cognitive complexity, according to the SOLO Taxonomy, and associated with the student's deep learning. Thus the authors were able to study their pedagogical practices in relation to the assessment and, consequently, to consciously prepare the assessment.