Academic advising, eh : a profile of undergraduate academic advising at Ontario universities

Despite its importance to postsecondary students' success, there is little known about academic advisement in Canada. Academic advising can be a very intensive and demanding job, yet it is not well understood what duties or student populations of advising make it so. On a practical level, this study sought to learn more about academic advisement in Ontario universities and provide a general overview of who advisors are and what they do. This study also investigated academic advising duties and time allocation for these responsibilities in an attempt to relate theory to practice incorporating Vilfredo Pareto's theoretical underpinnings to confirm or negate the applicability of the Pareto Principle in relationship to time utilization by advisors. Essentially this study sought to discover which students require the greatest advisement time and effort, and how advisors could apply these findings to their work. Academic advising professionals in Ontario universities were asked to complete a researcher-designed electronic survey. Quantitative data from the responses were analyzed to describe generalized features of academic advising at Ontario universities. Discussion and implications for practice will prompt advisors and institutions using the results of this study to measure themselves against a provincial assessment. Advisors' awareness of time allocation to different student groups can help focus attention where new strategies are needed to maximize time and efforts. This study found that caseload and time spent with student populations were proportional. Regular undergraduate students accounted for the greatest amount of caseload and time followed by working with students struggling academically. This study highlights the need for further evaluation, education, and research in academic advising in Canadian higher education.

Using genetic algorithms for the single allocation hub location problem

Hub location problem is an NP-hard problem that frequently arises in the design of transportation and distribution systems, postal delivery networks, and airline passenger flow. This work focuses on the Single Allocation Hub Location Problem (SAHLP). Genetic Algorithms (GAs) for the capacitated and uncapacitated variants of the SAHLP based on new chromosome representations and crossover operators are explored. The GAs is tested on two well-known sets of real-world problems with up to 200 nodes. The obtained results are very promising. For most of the test problems the GA obtains improved or best-known solutions and the computational time remains low. The proposed GAs can easily be extended to other variants of location problems arising in network design planning in transportation systems.