The objective of this work is to demonstrate a mechanism to improve the advising of students in a nontraditional environment. Minority serving institutions, commuter campuses and institutions with a high percentage of student transfers are unable to keep a tightly controlled cohort of students progressing through the curriculum. Students usually have varied course loads and different priorities due to family, financial needs or other responsibilities. Therefore, it is critical an individualized approach to advising. The school administration faces more challenges scheduling courses and allocating diminishing resources to satisfy the student demand. In addition, the faculty needs to assess the efficacy of the curriculum in a program and collecting longitudinal student data is difficult. We are proposing the application of a multi-agent approach to allow the students to take more control over their individualized advising. In this context, the student tool becomes an agent and the school provides the environment with a desirable behavior for the system. We call the academic control objective the "Operator." This paper focuses on the agent system by building a simple dashboard tool that will collect students' information about their progress through the curriculum in a program and will generate advising recommendations. The agent logic employs principles used in project management tools designed to help the students complete their degree plan sooner. For example, it would provide a visualization map of course sequences, customized for each student, making advising adjustments that will optimize the time to obtain the degree under a constrained set of resources. At the same time, the agent system provides feedback to the Operator. The second tool will be the Operator dashboard that will consolidate the collected data from the agents through several semesters (historical data) plus the predicted effects of the recommended plans. This should enable a better resource allocation and deeper analysis of the curriculum effectiveness. This tool is still under development. Previous work has presented some limited insight into the multi-agent approach however research and mapping of the critical path to graduation has been done. The proliferation of mobile devices and cloud computing enables a larger scale application of the proposed methodology to be developed for mobile devices.
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