Study plan: um software para orientação personalizada de planos de estudo

Abstract

Undergraduate students in Computer Science often face challenges that lead them to extend the time needed to complete the course or to abandon it before finishing. These obstacles typically stem from a significant load of extracurricular activities, competing with academic commitments, and making it challenging to dedicate exclusive time to studies. In this work, we developed the Study Plan, software aimed at recommending personalized study plans for undergraduate students, taking into account thepersonal context of the learner. The ultimate goal is ensuring students succeed academically without exceeding their limits. We evaluated with an expert who, based on the system’s recommendations for five students, examined each suggestion to analyze the relevance of the recommended subjects to the student’s profile, suitability to the current emester, and compliance with course specifications. As a result, the system proved efficient, meeting the course demands satisfactorily and providing consistent and coherent recommendations. However, during the evaluation, areas for improvement were identified, such as including a learning mechanism based on the student’s history and onsidering a minimum number of recommended subjects, as stipulated for students with scholarship permanence. Additionally, it is suggested to integrate recommendations with priority levels and include student involvement in research, teaching, and extension projects as relevant criteria in the recommendations. These proposed improvements aim to make the system more adaptable and effective, providing students with more personalized and balanced academic guidance. Keywords: Dynamic Programming; Snapsack Problem; Context Science; Profile of students; Recommended Study Plans.