Mapping node criticalities in a curriculum network
Abstract
Remedial education is compulsory for students who have insufficient reading, writing and mathematical skills statutory for more advanced courses in the curriculum. Scholars argue that enrolling in remedial courses stigmatizes students and discourages them by compromising the continuity of their academic time line. Therefore, a careful and thorough investigation of the curriculum structure is necessary. This paper deals with the detection of crucial subjects in the curriculum using the network approach. From the list of courses offered in UP Diliman (BS Physics (P–BS), BS Applied Physics (AP–BS), BS Physics–MS–PhD (P-BSMSPhD) and BS Applied Physics–MS-PhD (AP-BSMSPhD)), we construct a float time network to detect node criticalities. P–BS has more crucial nodes than AP–BS. Criticalities desaturate across the merged undergraduate-graduate curricula (P-BSMSPhD and AP-BSMSPhD), this time rendering PhD dissertations critical. We also classify AP–BS curriculum as a combination of random and scale–free network.