Assisting students to prepare long-term Course plans towards timely graduation is a challenging and time-consuming advising activity. Unless appropriate decisions are made, undesirable consequences may occur. Earlier, an approach called Interactive Decision Support for Course Planning (IDiSC) was developed. IDiSC performs a pro-active analysis of the impact of the different aspects of the problem and eventually suggests a study plan that balances students' preferences and advisors' recommendations, without violating any regulations. IDiSC employs mathematical optimization and follows an evolutionary and iterative decision support framework, called EVOLVE*. This paper proposes IDiSC, which is an improvement over IDiSC The contribution of IDiSC(+) is twofold. First, in order to address uncertainties and implicit concerns not formally described in the original problem statement, IDiSC(+) adopts a diversification algorithm that, instead of providing a single study plan,,generates a set of optimal or near optimal alternative plans that are of a similar quality and yet structurally different. Human intelligence is then employed to analyze these alternatives and to either approve one of them or refine the problem settings for generating further solutions. Second, IDiSC(+) uses a more advanced and representative formal model that overcomes key assumptions and limitations of its predecessor and thus addresses the problem in a more realistic way. A real-world application of IDiSC(+) is presented in order to illustrate its added value. (C) 2015 Elsevier B.V. All rights reserved.
