Masters Theses

Author

Tyler Morrow

Keywords and Phrases

Automated Advising; Context-aware Recommendations; Course Planning; Course Scheduling; Integer Linear Programming; Ontology

Abstract

"The work presented in this thesis utilizes context-aware recommendation to facilitate personalized education and assist students in selecting courses (or in non-traditional curricula, topics or modules) that meet curricular requirements, leverage their skills and background, and are relevant to their interests. The original research contribution of this thesis is an algorithm that can generate a schedule of courses with consideration of a student's profile, minimization of cost, and complete adherence to institution requirements. The research problem at hand - a constrained optimization problem with potentially conflicting objectives - is solved by first identifying a minimal sets of courses a student can take to graduate and then intelligently placing the selected courses into available semesters.

The distinction between the proposed approach and related studies is in its simultaneous achievement of the following: guaranteed fulfillment of curricular requirements; applicability to both traditional and non-traditional curricula; and flexibility in nomenclature - semantics are extracted from syntax to allow the identification of relevant content, despite differences in course or topic titles from one institution to the next. The course selection algorithm presented is developed for the Pervasive Cyberinfrastructure for Personalized eLearning and Instructional Support (PERCEPOLIS), which can assist or supplement the degree planning actions of an academic advisor, with the assurance that recommended selections are always valid. With this algorithm, PERCEPOLIS can recommend the entire trajectory that a student could take to graduation, as opposed to just the next semester, and it does so with consideration of course or topic availability"--Abstract, page iii.

Advisor(s)

Hurson, A. R.
Sedigh, Sahra

Committee Member(s)

Jiang, Wei

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2017

Pagination

xii, 87 pages

Note about bibliography

Includes bibliographic references (pages 83-86).

Rights

© 2017 Tyler Morrow

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11106

Electronic OCLC #

992440423

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