Agent-based simulation model for identifying failure on students' project

In learning and development, students need to be made aware of their slips and mistakes in terms of acquiring the required knowledge, skills and competencies, especially, in active learning approaches. However, assessments may not necessarily lead to an effective understanding of student's errors. Most assessors are required to measure the extent of student's accurate output in terms of exam answers or practical assessments. Areas of failure tend to be overlooked and for this reason, learners at-risk of achieving poor results can become careless when completing assessments. In the present study, we examine the following research questions: (i) How can we simulate the landscape of data on both individual and team behaviour in terms of failure in their projects? (ii) How can we develop ways of identifying at-risk students in each team and support them immediately? Therefore, in order to address this problem, this research proposes an agent-based simulation of student projects, which considers both individual and team errors. This model is created on the basis of particular characteristics of individual learners within the team. We assume that individuals working within a team are subject to recognition-primed decision making when confronted with particular problems to solve. The adjustment proposed by this model includes analysing the problem using prior knowledge and planning as well as judgements on the suitability of particular solutions. This research will be further developed to identify at-risk learners in terms of investigating the areas they want to develop to achieve their learning goals in particular subjects and especially in the software development fields.