INVESTIGATING DIFFERENCES BETWEEN INSTRUCTOR EXPECTATION AND STUDENT WORKLOAD IN UNDERGRADUATE ENGINEERING

Abstract

For the past two years at the University of X, first-year engineering undergraduate students have been asked to fill out workload questionnaires. These questionnaires were sent to random samples of the first-year class weekly, where they were prompted to answer questions regarding how much time they devoted outside of the classroom to each particular class. Workload data for 2018 and 2019 showed upward of 30 hours of work outside of the classroom, after the first few weeks of classes once major assignments and examinations began. Evidence in the literature [1,2] suggests that university students face a shortage of time, specifically with first-year students lacking the essential time management skills to be efficient. In the present study, we aim to find a correlation between how long the first-year engineering students spend on a class each week versus how long instructors anticipate the average student would spend on their respective class. In order to do so, we examined the data gathered for 2018 and 2019 fall terms from each student for a specific class and week. Furthermore, additional relevant information will be gathered from the instructors and course coordinators to obtain an estimate on how many anticipated hours a student would have to spend on a class each week versus how long instructors anticipate the average student would spend on their respective class. In order to do so, we examined the data gathered for 2018 and 2019 fall terms from each student for a specific class and week. Furthermore, additional relevant information will be gathered from the instructors and course coordinators to obtain an estimate on how many anticipated hours a student would have to spend on their course that week, given what assessments are in that week. Through analyzing multiple courses, we expect to find a relationship that would suggest whether the hours students spend on assignments is less than, equal to, or greater than what instructors expect for first-year engineering students at University of X to spend. The outcome of this analysis would be beneficial to understand the workloads as perceived by professors and experienced by first-year engineering students. Furthermore, it can highlight potential misjudging of difficulty of each course and assignment, helping instructors to update their expectations and propose fair deadlines and grades for assessments. It can also assist program coordinators to distribute major assessments better towards a steadier and more manageable workload for the students. The students can also benefit from the findings to understand their time commitments.