Content area

Abstract

This work presents a degree planning tool developed as part of the Pervasive Cyberinfrastructure for Personalized eLearning and Instructional Support (PERCEPOLIS) project which generates complete, valid, and personalized degree paths at any point from admission to graduation. This eliminates tedious calculation and double-checking, allowing advisors to focus on a student’s long-term plans and students to proactively explore potential degree paths. The original research contribution of this work is the use of a unified model for academic requirements to automatically translate complex, real-world curricula into a constraint programming model that can be quickly optimized based on personalized student criteria.

Automatically translating existing data into my unified model as an intermediary step allows complex requirements to be broken down into simple components, and lets data from multiple sources interoperate within the same model. I describe the implementation of translations from the PeopleSoft and uAchieve internal data formats, the two systems in use at Missouri S&T, but the unified model is general enough to represent a wide variety of requirements. The system can be straightforwardly extended to support academic requirements in different formats and from different universities. Supporting this complex, real-world data is what ultimately differentiates this approach; previous tools either limit the expressiveness of their academic requirements or only generate approximate degree paths. This creates a gap between the hypothetical world being explored by users and the real world they must make decisions in. Using this approach however, PERCEPOLIS gets the best of both worlds: users can trust that the generated degree paths satisfy all academic requirements while prioritizing their personal criteria like preferred courses, semester difficulty, and time-to-degree.

Details

1010268
Business indexing term
Title
Constraint Programming for Optimized Degree Paths
Number of pages
73
Publication year
2025
Degree date
2025
School code
0587
Source
MAI 87/2(E), Masters Abstracts International
ISBN
9798291565346
Committee member
Morales, Ricardo A.
University/institution
Missouri University of Science and Technology
Department
Computer Science
University location
United States -- Missouri
Degree
M.S.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
32166996
ProQuest document ID
3244507092
Document URL
https://www.proquest.com/dissertations-theses/constraint-programming-optimized-degree-paths/docview/3244507092/se-2?accountid=208611
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Database
ProQuest One Academic