Monitoring Students’ Professional Competencies in PBL: A Proposal Founded on Constructive Alignment and Supported by AI Technologies

Abstract

This Research Full Paper presents a proposal founded on the Constructive Alignment Theory and supported by Artificial Intelligence (AI) technologies, aiming to monitor professional competencies in Computing Higher Education (CHE) based on Problem- Based Learning (PBL). Within CHE, there is a growing movement to change an educational paradigm that goes beyond knowledge-based education. Therefore, active learning methodologies such as the PBL, have become increasingly popular to develop student’s technical knowledge, skills, and attitudes, translating in professional competencies. In this context, this research advocates the Constructive Alignment Theory by Biggs to monitor professional competencies in PBL experiences. Biggs suggests the alignment between the learning results from the student’s perspective and the objectives defined by the teacher in the course planning. This follow-up can be done in various ways and include many data sources like the usual student feedback questionnaires. However, it requires a lot of effort from the teacher/pedagogical team and involves difficulties related to effort, workload, and time spent to make improvements. SO, how to monitor students' professional competencies in an automated way, having as references the Constructive Alignment Theory and the course planning? For this, we propose an AI- based tool for processing student feedback, called SkillSight, helping teachers monitor competencies considering the learning outcomes. From Design Science Research cycles, the first evaluation results showed a good acceptance of this tool and suggestions for improvements, especially at the results visualization.