Applications: Graduate School Admissions Screening

A knowledge-based decision support system for screening graduate school applicants.

The Information Problem

Every year at the School of Public Administration at the University of Victoria, staff and faculty address student admissions. Each year a new committee is formed to screen and select students for their master's program. The annual turnover of committee members led to a problem in establishing a consistent selection procedure.

In addition, the committee members were required to read, categorize, and select new students from approximately 300 applications. This task took a considerable amount of time from highly trained faculty members that were already facing increased workloads.

Existing Practice

Faculty members tackled the problem in two stages: screening; and selection. Each committee member had to read all the applications and categorize them into "accept", "discuss" and "reject". Next the committee reviewed the categorized applications and selected students according to the number of places available.

The highest level of expertise was involved in selecting students from the "discuss" category. This situation arose when there were more places available than there were students in the "accept" category.

A New Approach

A graduate student, in conjunction with the committee chairperson, suggested that assistance with this task could be provided in the form of a knowledge-based system for graduate student selection. The idea met with interest and approval. Acquire^® was chosen as the application development tool because of its knowledge acquisition capabilities.

The Application Screening System

They decided to tackle the screening problem and leave the final selection process up to the committee members. Knowledge about departmental guidelines and acceptance criteria was acquired for a knowledge-based system that would review each application and categorize the applicant into one of three categories – "accept", "discuss", or "reject". Committee members need only consider applications in the "accept" or "discuss" categories. This reduced the work load of this task considerably.

If the school had places for 10 new students and the "accept" category contained 10 or more applications, the committee need only review the students in this category. Two categories could be omitted from their consideration.

If the "accept" category had fewer than 10 applications, then the committee need only review the "discuss" category for selection of the remaining students. With this system the committee members need only read and evaluate the students in one of the three categories produced by the knowledge-based system.

Conclusion

In this age of economic restraint, the workload of professors is increasing while the allocated resources remain constant or decrease. The Graduate School Admissions Screening system described here is a very appropriate use of knowledge-based technology. The committee members' task is effectively re-engineered through the use of knowledge-based technology. More appropriate use of faculty members' time and expertise is achieved by automatic screening of applications, leaving final selection to the faculty members.

The knowledge-based system enables the entire task to be accomplished with a high degree of skill, and in much less time. Administrative support staff can enter the data for each applicant, run the system and forward the categorized applications to committee members. Further to this, the new committee members can readily gain an appreciation of the applicant selection criteria by reviewing the contents of the knowledge base – thereby removing a considerable training burden from the previous year's committee members.