(untitled) (Innovation & Development in Engineering and Applied Science, 2024)
In response to various causes leading to poor academic performance among students in Mathematics, the objective was to establish a matrix method metric for assessing Complex Mathematics learning; taking into account attitudinal, procedural, and cognitive axes, as well as conceptual, algebraic, and graphic-numerical aspects, i.e., a 3x3 matrix that allowed for the collection of specific data. Following the application of experimental trials focused on the acquisition, processing, and interpretation of numerical data, the result was two specific evaluation matrices. A "state matrix" describes the student’s knowledge before the activity’s execution and another at the trial’s end, which allows for the comparison of knowledge before and after, expressing it as the extremes of a Markov chain; also, comparing it with other existing evaluation metrics, with the matrices serving as a grading rubric that helps identify shortcomings and propose improvements. Through a program in MATH LAB, a second outcome in the form of a "Transformation Matrix" was identified, which determines the evolution of the state matrix, i.e., quantitatively visualizes learning and thus measures the academic activity’s efficiency. This involved analyzing the existence of eigenvalues and eigenvectors, which are interpreted in the discussion stage.