Modelos de inteligencia artificial para asesorar el proceso evaluador de trabajos informáticos complejos

Laburpena

We propose the use of artificial intelligence (AI) mo- dels to help evaluate complex projects in computer science courses that involve technical and creative components. The goal is to provide a methodology to analyze the main variables that describe the evaluation, to discover possible biases and discrepancies, and to generate appropriate rubrics that avoid them. The pro- posed methodology has been applied to a first-year in- troductory course on computer science, which is taught in both computer science and mathematics degrees. In that course, the students must develop a web page ac- cording to some technical requirements (compatibility with standards, number of HTML and CSS files, etc.), but it also possesses a creative component (layout, ap- pearance, etc.). Optimized AI models have been de- veloped using evolutionary algorithms to identify the most important variables that took part in the evalua- tion of these projects during five courses. The results obtained allow us to draw conclusions about the eva- luation process, possible improvements in the impar- tiality of the evaluation, and the possibility of gene- rating suitable rubrics for grading assignments. The methodology is applicable to projects in other sub- jects since this technical-creative typology is frequent in university tasks.