Oh Dear, Oh Dear! I Shall Be Late

Written by Dr Judi McCuaig, Associate Professor in the School of Computer Science. Dr McCuaig has recently received funding from the Learning Enhancement Fund, the SOTL fund, and PSEER.

Science, Technology, Engineering and Math (STEM) disciplines have a reputation for difficult courses that require long hours from students[1]. Students in those disciplines often take several high workload courses in a single semester and usually those courses are prerequisites for continued study, which means that success is necessary in every course. To further complicate the STEM students’ lives,  student-instructor ratios are often exceptionally high, especially in introductory courses, which impacts student achievement[2].

When the lens is focused more tightly on Computer Science, we find additional factors. Student (and sometimes parental) employment expectations are often out of synch with the likely scenario (not everyone is going to create video games for a living) which sometimes leaves students disengaged with curriculum that doesn’t directly teach what they believe they will do for a living. Sadly there are still well-documented racial and gender imbalances[3] in all aspects of the computer science industry that add work and stress to impacted students. Finally, the stereotypical image of people in computer science is one of poor work-life balance. They are characterized as workaholics who live at and for their job. The broad acceptance of that stereotype breeds reluctance to talk about issues of work-life balance, for fear of being labelled as weak or unfit for the domain.

Over the last few years, I've noticed that the struggle for work-life balance begins as soon as students enter a CS program. Students sometimes have the luxury of being a full-time student during their first year of study, but often are working at least a few hours per week in order to pay bills.  By second year it seems that most CS students have a part-time (or even full time) job to pay bills while they go to school. In 2013 the Canadian Federation of Students reported that Ontario University students worked an average of 16.5 hours per week[4]. A 2015 study from Georgetown University found that 70-80% of students were working while going to school[5]. About 40% of undergraduate students were working at least 30 hours per week. Sixty percent of the working students were women. These numbers likely haven't decreased between 2015 and now.

Consider the following scenario involving a hypothetical 3rd-semester student. This student is taking five technical courses in computer science, each with 3 hours of lecture. Three of the five courses have a 2 hour/week lab, two have 1 hour/week labs. Our hypothetical student has 23 hours per week of instruction. Let’s say that our student is working 15 hours per week – slightly under the 2013 average. The student needs 10 hours per day to sleep, eat, shower, etc. For the purposes of our example, work + classes + basic life essentials take 108 hours per week. A 7-day week has 168 hours. So far, our student has 60 hours left in their week for transportation, religious obligations, homework, exercise, socialization, shopping for and preparing food, home cleaning/maintenance, and recreation.

If each of the five courses has three assignments, and an assignment takes, on average, 15 hours to research/review and complete, that is 225 hours of assignment work over a 12-week semester or 19 hours/week. Our student spends 5 hours/week on other learning activities such as review, preparing for labs, studying for exams. The student has 36 hours left in their week (5 hrs/day) and we don't have any time allocated for transportation, exercise, religious obligations, food preparation, or recreation. Furthermore, the time estimates we used are probably low. It is equally likely that our fictional undergraduate student is employed for 20 or more hours per week. At least half of the assignments are likely to take 20-30 hours to complete and lab preparation will likely consume at least 4 hours/week. The additional 5 hours/week of employment drops free time to 31 hours. The extra time for assignments and lab preparation reduces free time by another 7 hours per week, leaving the daily available time at less than 3.5 hours. That 3.5 hours is all that is available for friends, family, exercise, community, shopping, food preparation, leisure activities, etc. 

There simply aren't enough hours in the day to be this hypothetical CS student and remain healthy mentally and physically, and yet that hypothetical situation is all too real.  We are teaching post-secondary computer science students from their first days in our programs to sacrifice themselves and their health for work. We model the stereotype of work-addicted technology workers, and we expect students to adopt it. The end result is that students are suffering. Students who have the privilege of being able to cut back on employment hours, or who can afford to take an extra year and take a reduced course load are advantaged. Those students can find the hours to put into high work courses. Students whose socioeconomic background gave them a high school education in computer science are also advantaged because they can spend less time on coursework but still succeed. 

Persons without these advantages may drop out or under-perform, simply because they do not have enough hours in a day to be successful in the current climate for CS education. Like the White Rabbit from Alice in Wonderland, they must always juggle time and are often late. Our current approach to CS education is rewarding privilege as much, or more than it is rewarding ability. Small wonder that Indigenous persons, women, and other minorities are under-represented.

STEM/SOTL researchers have shown that engaged students who actively participate in learning do better. Adherence to best practices has resulted in clearly stated learning outcomes for an increasing number of post-secondary courses. Educators now need to give the responsibility for learning back to students. We can’t possibly assess every tiny detail of knowledge, nor can we realistically ask students to complete homework for every detail. Instead, we need to make sure students know what to learn, how to go about learning it, and how we intend to measure their learning. We need to provide a variety of experiences that promote learning, feedback on those experiences, and fair evaluations of the knowledge and skills represented in the learning outcomes for our courses.  However, doing so is fraught with challenges. Large classes prevent instructors from scaffolding students through their learning tasks. Instructors do not have the resources to deconstruct every learning opportunity with respect to its impact on student time. Post-secondary instructors usually are trained in their content area (i.e. computer science) but often have no teaching training. This makes it challenging for instructors to create experiences that focus on course learning outcomes and facilitating deep learning. Even the education community has no clear understanding of how to accurately evaluate student knowledge in a large classroom, so it is no surprise that individual instructors often feel limited to tests of recall and reproduction. 

Our research group has ongoing research projects designed to address some aspects of this “let the learner own the learning” philosophy.  We are exploring the impact of automated formative assessment on students. Our Immediate Feedback System (IFS) provides programming students with non-graded feedback about their programming assignments.  The feedback can be obtained on demand at any time. We anticipate that, by providing immediate feedback explaining common errors that can be time consuming for novices to identify, we can help students to focus on the learning outcomes for the assignment rather than the minutia, hopefully resulting in an improved rate of assignment correctness. A second aspect of this work will provide formative feedback for instructors about the student experience with assignments. We believe instructors may find it easier to write concise, learning-outcome driven assignments when given feedback about student confusion, length of time spent on specific modules, and common error situations. CS educators have a responsibility to ensure that access to computer science programs is limited only by ability. We hope that IFS will help make that truer.

[1]        L. C. contributor lifestyles, “Freshman experience varies by liberal arts or STEM major,” Collegiate Times. [Online]. Available: http://www.collegiatetimes.com/lifestyles/freshman-experience-varies-by-liberal-arts-or-stem-major/article_f31eddc0-c9a1-11e7-af4a-d77dd98e3e73.html. [Accessed: 22-Jun-2018].

[2]        Science and Policy Exchange, “Student perspective of STEM education in Canada.” 2015.

[3]        A. D. Rayome, “The state of women in computer science: An investigative report,” TechRepublic. [Online]. Available: https://www.techrepublic.com/article/the-state-of-women-in-computer-science-an-investigative-report/. [Accessed: 22-Jun-2018].

[4]        “Student Employment: Eroding academic success.” http://dev.cfswpnetwork.ca/wp-content/uploads/sites/71/2015/07/Factsheet-2013-11-Student-Employment-EN.pdf .

[5]        A. Carnevale, N. Smith, M. Melton, and Price, E, “Learning While Earning: The New Norm.”