Document Type

Closed Project

Publication Date

Winter 2018


Ramin Neshati

Course Title

Decision Making in Engineering and Technology Management

Course Number

EMGT 530/630


Hierarchical Decision Model, Decision making, Academic advising, Portland State University -- Curricula


With the increasing amount of technical employees needed to fill key jobs in the United States, the value of a graduate degree will increase the incentive for individuals with full time employment to pursue one. While many programs offer evening classes, a deeper analysis into the optimum combination of seasons, days offered, and class difficulty could help create a curriculum to meet the student’s specific needs. The desires of the students could then be reflected by the departments in the form of offering courses in different terms, on different days, in different locations, and in combinations that best complement each other. This could help ensure that classes reach their capacity and students are set up for success.

Academic advisors can help to guide students through their core classes to receive a degree in their specific field, but as a requirement of graduation, several elective courses must be completed. After the potential elective courses have been selected, the motives that would influence one course over another were researched. The criteria selected for the pairwise comparisons of the courses were broken into two categories, time and difficulty. The elective classes available vary by time in respect to the season (or school term) and the day of the week the class is offered. For the purposes of the model used in this study, the elective classes are from the Engineering and Technology Management (ETM) program at Portland State University (PSU), they are offered one night a week, during the fall, winter, spring, and summer terms. To increase the scope of defining a “difficult” class solely by the hours per week spent studying outside of class, the difficulty of a class was broken into two categories, workload and complexity. While the workload is the traditional quantitative measure of hour spent outside-of-class, the complexity is a qualitative assessment of other activities required to understand the themes and concepts of a given class. All of these criteria were entered into a Hierarchical Decision Modeling (HDM) program that is a variation of the Analytic Hierarchy Process (AHP) used in ETM at PSU. The model was sent to a group of seven experts, consisting of students currently enrolled in ETM, and their results for the best combination of elective classes included very little inconsistencies and serves as a sample for the analysis of alternative classes to be used outside of ETM at PSU.

Following the results for the sample model, more in depth research should be done using HDM to determine the best seasons and days of the week to schedule courses. Additionally, more research should be performed in measuring the difficulty of classes within a department to ensure that students are not being asked to do too much or too little. Combining the information of the effects of time and difficulty could also provide rich information for academic advisors to provide more realistic information that will help students achieve academic success.


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