Monitoring the progress of programming students supported by a digital teaching assistant

Abstract

Several studies have shown that there is an important link between continual monitoring by the teachers and the students’ performance. Unfortunately, the teachers cannot be continuously looking for what the students are doing. To overcome this situation, we propose the use of CodeInsights, a tool capable of capturing, in an autonomous, transparent and unobtrusive manner, information about the students’ performance and then, based on teacher’s expectations, notify them about possible deviations in the specific context of programming courses. The decision on whether the system should or should not notify the teacher is supported by an artificial cognitive selective attention mechanism. Although CodeInsights, provided with the described mechanism, hasn’t been fully tested in a real case scenario, we present some specific examples of how it can be used to assist teachers.