TY - GEN
T1 - The complexity of university curricula according to course cruciality
AU - Slim, Ahmad
AU - Kozlick, Jarred
AU - Heileman, Gregory L.
AU - Abdallah, Chaouki T.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/1
Y1 - 2014/10/1
N2 - Many universities have recently focused significant efforts on enhancing their graduation rates. Numerous factors may impact a student's ability to succeed and ultimately graduate, including pre-university preparation, as well as the student support services provided by a university. However, even the best efforts to improve in these areas may fail if other institutional factors overwhelm their ability to facilitate student progress. Specifically, in this paper we consider degree to which the underlying curriculum that a student must traverse in order to earn a degree impacts progress. Using complex network analysis and graph theory, this paper proposes a framework for analyzing university course networks at the university, college and departmental levels. The analyses we provide are based on quantifying the importance of a course based on its delay and blocking factors, as well as the number of curricula that incorporate the course, leading to a metric we refer to as the course cruciality. Experimental results, using data from the University of New Mexico, show that the distribution of course cruciality follows a power law distribution. Applications of the proposed framework are extended to study the complexity of curricula within colleges as well as the tendency of a university's disciplines to associate with others that are unlike them. This work may be useful to both students and decision makers at universities as it presents a robust framework for analyzing the ease of flow of students through curricula, which may lead to improvements that facilitate improved student success.
AB - Many universities have recently focused significant efforts on enhancing their graduation rates. Numerous factors may impact a student's ability to succeed and ultimately graduate, including pre-university preparation, as well as the student support services provided by a university. However, even the best efforts to improve in these areas may fail if other institutional factors overwhelm their ability to facilitate student progress. Specifically, in this paper we consider degree to which the underlying curriculum that a student must traverse in order to earn a degree impacts progress. Using complex network analysis and graph theory, this paper proposes a framework for analyzing university course networks at the university, college and departmental levels. The analyses we provide are based on quantifying the importance of a course based on its delay and blocking factors, as well as the number of curricula that incorporate the course, leading to a metric we refer to as the course cruciality. Experimental results, using data from the University of New Mexico, show that the distribution of course cruciality follows a power law distribution. Applications of the proposed framework are extended to study the complexity of curricula within colleges as well as the tendency of a university's disciplines to associate with others that are unlike them. This work may be useful to both students and decision makers at universities as it presents a robust framework for analyzing the ease of flow of students through curricula, which may lead to improvements that facilitate improved student success.
KW - complex networks
KW - institutional analytics
KW - university curricula
UR - http://www.scopus.com/inward/record.url?scp=84908868910&partnerID=8YFLogxK
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U2 - 10.1109/CISIS.2014.34
DO - 10.1109/CISIS.2014.34
M3 - Conference contribution
AN - SCOPUS:84908868910
T3 - Proceedings - 2014 8th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2014
SP - 242
EP - 248
BT - Proceedings - 2014 8th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 8th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2014
Y2 - 2 July 2014 through 4 July 2014
ER -