The objective of this thesis is to improve the co-operative (co-op) education process by analyzing the relationships among academic programs in the context of the co-op job market. To do this, we propose and apply a novel graph-mining methodology. The input to our problem consists of student-job interview pairs, with each student labelled with his or her academic program. From this input, we build a weighted directed graph, which we refer to as a program graph, in which nodes correspond to academic programs and edge weights denote the percentage of jobs that interviewed at least one student from both programs. For example, a directed edge from the Computer Engineering program to the Electrical Engineering program with weight 0.36 means that of all the jobs that interviewed at least one Computer Engineering student, 36 percent of those jobs also interviewed at least one Electrical Engineering student. Thus, the larger the edge weight, the stronger the relationship and competition between particular programs. The output consists of various graph properties and analyses, particularly those which find nodes forming clusters or communities, nodes that are connected to few or many clusters, and nodes that are strongly connected to their immediate neighbours. As we will show, these properties have natural interpretations in terms of the relationships among academic programs and competition for co-op jobs.
We applied the proposed methodology on one term of co-op interview data from a large Canadian university. We obtained interesting new insights that have not been reported in prior work. These insights can be beneficial to students, employers and academic institutions. Characterizing closely connected programs can help employers broaden their search for qualified students and can help students select programs of study that better correspond to their desired career. Students seeking a multi-disciplinary education can choose programs that are connected to other programs from many different clusters. Additionally, institutions can attend to programs that are strongly connected to (and face competition from) other programs by attracting more employers offering jobs in this area
