SPEI: Una herramienta web de intervención temprana para el desempeño académico de estudiantes de cursos de programación

José Miguel Llanos Mosquera; Victor Andrés Bucheli Guerrero; Felipe Restrepo Calle

doi:10.14482/inde.43.02.519.852

Authors

José Miguel Llanos Mosquera Universidad del Valle
Victor Andrés Bucheli Guerrero Universidad del Valle
Felipe Restrepo Calle Universidad Nacional de Colombia

DOI:

https://doi.org/10.14482/inde.43.02.519.852

Keywords:

academic performance, CS1, early intervention, early intervention tool, prediction model

Abstract

In introductory programming courses (CS1), students often exhibit low academic performance, a common issue in higher education institutions that is attributed to the complexity of the concepts and a lack of programming experience. One way to address this situation is by implementing tools that allow for early intervention in the learning process to improve academic performance. This study presents the Student Performance Early Intervention (SPEI), a web-based tool that integrates an academic performance prediction model and two types of early interventions for CS1 courses. The aim of this article is to evaluate the effectiveness of SPEI on the academic performance of students in a CS1 programming course. SPEI was developed using the Model-Template-View architecture and integrates prediction, preventive intervention, and proactive intervention modules. The results show that SPEI accurately identifies students with low academic performance and enables personalized interventions that contribute to improving their performance. The conclusions suggest that SPEI is an effective tool to support the learning process and could be replicated in other courses to enhance students' academic performance in CS1 courses.

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