TY - GEN
T1 - Network analysis of university courses
AU - Slim, Ahmad
AU - Kozlick, Jarred
AU - Heileman, Gregory L.
AU - Wigdahl, Jeff
AU - Abdallah, Chaouki T.
N1 - Publisher Copyright:
© Copyright 2014 by the International World Wide Web Conferences Steering Committee.
PY - 2014/4/7
Y1 - 2014/4/7
N2 - Crucial courses have a high impact on students progress at universities and ultimately on graduation rates. Detecting such courses should therefore be a major focus of decision makers at universities. Based on complex network analysis and graph theory, this paper proposes a new framework to not only detect such courses, but also quantify their cruciality. The experimental results conducted using data from the (UNM) show that the distribution of course cruciality follows a power law distribution. The results also show that the ten most crucial courses at UNM are all in mathematics. Applications of the proposed framework are extended to study the complexity of curricula within colleges, which leads to a consideration of the creation of optimal curricula. Optimal curricula along with the earned letter grades of the courses are further exploited to analyze the student progress. This work is important as it presents a robust framework to ensure the ease of flow of students through curricula with the goal of improving a university's graduation rate.
AB - Crucial courses have a high impact on students progress at universities and ultimately on graduation rates. Detecting such courses should therefore be a major focus of decision makers at universities. Based on complex network analysis and graph theory, this paper proposes a new framework to not only detect such courses, but also quantify their cruciality. The experimental results conducted using data from the (UNM) show that the distribution of course cruciality follows a power law distribution. The results also show that the ten most crucial courses at UNM are all in mathematics. Applications of the proposed framework are extended to study the complexity of curricula within colleges, which leads to a consideration of the creation of optimal curricula. Optimal curricula along with the earned letter grades of the courses are further exploited to analyze the student progress. This work is important as it presents a robust framework to ensure the ease of flow of students through curricula with the goal of improving a university's graduation rate.
KW - Complex networks
KW - Cruciality
KW - Curriculium complexity
KW - Longest path
KW - Student progress
UR - http://www.scopus.com/inward/record.url?scp=84991014001&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991014001&partnerID=8YFLogxK
U2 - 10.1145/2567948.2579360
DO - 10.1145/2567948.2579360
M3 - Conference contribution
AN - SCOPUS:84991014001
T3 - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
SP - 713
EP - 718
BT - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PB - Association for Computing Machinery, Inc
T2 - 23rd International Conference on World Wide Web, WWW 2014
Y2 - 7 April 2014 through 11 April 2014
ER -