How Do Students Behave When Using A Tutoring System? Employing Data Mining to Identify Behavioral Patterns Associated to The Learning of Mathematics

Abstract

The inclusion of technology in the academic processes has led to constant innovation and investment of resources to offer a first-level educational service, with international standards, methodologies, study plans, and last generation laboratories. This paper focuses on how teachers can make use of an educational technology tool that will allow them to identify patterns that are associated with learning based on human-computer interaction. We present evidence of learning outcomes based on the detection of behaviors in Intelligent Tutoring Systems. These patterns pave the way for the auto-matic identification of patterns in association to students’ learning while using an educational technological tool. The results suggest a model for student’s behavior identification when interacting with the technological tool “Scooter”. This model identifies students with prospective better learning outcomes as well as students with difficulties to solve math prob-lems. Work for the future will analyze data that comes from different set-tings apart from solving exercises in Scooter to prove the hypothesis that there are patterns of behavior associated to learning outcomes in different problem-solving situations presented by educational technology.