Congratulations to Alexander Howse, 2016 CUT Award Recipient – Svitlana Taraban-Gordon

As a way to recognize and celebrate teaching development efforts of Waterloo graduate students, the Centre for Teaching Excellence (CTE) and the Graduate Studies Office (GSO) offer the Certificate in University Teaching (CUT) Award. This annual award is given to a graduate student who demonstrates a strong commitment to teaching development and the highest achievement upon the completion of the CUT program. We are pleased to announce that Alexander Howse, PhD candidate in the Department of Applied Mathematics and a recent graduate of the CUT program, was selected as the recipient of the 2016 CUT Award.

With a little more than a year left in his PhD program, Alex Howse’s CV already boasts an impressive record of teaching accomplishments: three teaching certificates from two Canadian institutions and a course instructorship in MATH117: Calculus for Engineering. Alex became interested in learning about university teaching while pursuing his master’s degree at Memorial University where he completed a teaching development program for graduate students offered through the teaching and learning centre. The program piqued his interest in learning about university teaching and helped him to successfully manage his teaching responsibilities when he taught his first undergraduate course at Memorial as a master’s student.

Upon starting the PhD program at Waterloo, Alex heard about teaching certificate programs for graduate students offered by CTE and decided to continue learning about university teaching while working on his doctorate. After he successfully completed CTE’s Fundamentals of University Teaching program, he enrolled in the Certificate in University Teaching (CUT), a comprehensive teaching development program for PhD students who are interested in academic careers.  Although some of the topics discussed in the program, such as learning-centred teaching approaches, were not new to Alex, he believes that the learning activities that participants are asked to undertake as part of the CUT, such as creating a teaching dossier, are helpful not only for immediate teaching responsibilities at Waterloo but also as a preparation for the academic job market.

When asked to reflect on his recent teaching experience as an instructor, Alex credits the improvements that he made in his teaching to the feedback that he received from two sources: CTE staff members who observed his classroom teaching as part of the CUT program and a faculty member in his department who observed his class as part of a departmental lecturing requirement for math PhD students. The feedback that Alex received from his observers and the discussions that took place after the classroom visits addressed different aspects of his teaching approach and gave him ideas for the upcoming classes, such as ways for effective presentation of material and increasing student participation during lectures in his class with more than 100 students. “Often you think that as an instructor, you are doing what you intend to do but then you get caught up in the flow of the lecture and lose sight of student learning. It’s nice to have someone come in, observe your class and discuss it with you,” says Alex.

Using the feedback from his observers, Alex worked hard to improve his lectures and to help his students do well in the course. He fine-tuned his questioning strategies, resisted the urge to give out answers and experimented with the use of a think-pair-share technique which offered his students opportunities to solve problems on their own before discussing them with pairs and eventually as a large class. He looked for ways to explain the material in a way that would allow him to reach students with different levels of knowledge. When he heard about the muddiest point technique at one of the CUT teaching workshops, he implemented it in his class to identify areas of material that students found difficult. Based on student feedback about the material that was not clear to them, he created summary sheets as a supplementary study tool for his students.

For the CUT research project which is intended to familiarize graduate students with the research on teaching and learning in higher education, Alex decided to examine the higher education literature on math anxiety. He felt that this is an important topic for math instructors and something he encountered frequently when working with undergraduate students who were comfortable with math as high school students but were struggling with the subject at the university level. According to Alex, reading the research on math anxiety helped him to understand the issue more effectively and prepared him for conversations with students on learning strategies and ways to cope with math anxiety.

Looking back at his experience in the CUT, Alex is convinced that the time that he devoted to developing his teaching knowledge and skills by completing the program was well worth it. “I took the program seriously and put a lot of effort into it. It helped me to improve my teaching skills and put me in a good position for future academic job applications. I would strongly recommend the program to PhD students, especially if they plan to teach at the university.”

Congratulations on the CUT Award, Alex!

Better Teaching Through Chemistry — Dylon McChesney

analogyBecause I do research in philosophy, it might be confusing to some people why I talk about the hard sciences so much in relation to teaching. The reason is simple: philosophy is very abstract, and abstract things are not so easy to understand, thus I look to outside disciplines for strategies to concretize ideas. It turns out, of course, that philosophy has no monopoly on abstraction. Dorothy Gale (1999) shows that even elementary chemistry, that is, the kind of material covered in grade school, is abstract and “inexplicable without the use of analogies or models.” It is easy to assume that because a subject has to do with the natural world (for example) that it is de facto concrete, but this assumption is harmful to pedagogy.

Chemistry—like so many other things—is taught through dividing the world into hierarchical levels of abstraction: we establish the relationship between macro level phenomena like a glass of water, and the sub-micro level (H20) of that same phenomena. Simple, right? Well, as Gale notes in the aforementioned article, there are numerous obstacles to strengthening the understanding of each level and how they are interrelated. One obstacle is language choice. Many technical terms have different meanings when used in everyday communication, which can lead to a situation where a “student will be thinking one thing, the instructor another” (ibid.). Surely this situation is a nearly universal academic experience, a kind of growing pain for students and (hopefully) a wakeup call for instructors. Philosophers could be more self-aware that the term “realism” refers to a class of ideas that probably seem anything but realistic, and what counts as a valid argument in formal logic can look like a completely invalid argument from a common sense perspective. So, one thing we can all learn from Chemistry is to anticipate a struggle to “override” intuitive, non-technical definitions and concepts. From the privileged perspective of hindsight bias, these struggles might seem trivial, but they are not.

Perhaps the problem of technical language use is obvious, but what is likely less obvious is how we do—and how we should—use analogies in teaching. If Chemistry (taken here to be paradigmatic) is “inexplicable without the use of analogies or models” then we need to be very aware of the strengths and weaknesses of analogies. A convenient example is the Bohr “solar system” model of the atom. Because atomic particles are unobservable, they are much more difficult to conceptualize than dogs, trees, or even the components of cells which can at least be viewed through microscopes. But since planets are observable, a solar system is relatively easy to conceptualize. Drawing an analogy between a solar system and an atom (where the “star” is the nucleus and “orbiting planets” are electrons) allows for some visualization and a sort of functional template of understanding. This is extremely powerful! Unfortunately, sometimes these templates can cause misunderstandings. The Bohr model of the atom, despite its elegant simplicity, is not the best model. In fact, we now know it is misleading; yet for many the cognitive damage is already done and the inherent virtue of learning through connections will consequently be difficult to reverse.  Thus we have a ubiquitous example of how analogies can help and hurt all at once; although we need them to teach and learn, we also need to learn how to teach with them carefully. While it is unlikely that many of us will be able to anticipate specific paradigm shifts, such as transition from classical mechanics to quantum mechanics, we need to at least anticipate that some paradigm shifts are likely on the horizon. Analogies and models are indispensable, but promoting a critical stance and stressing the limitations of our best knowledge-generating tools might be even more so.

Although the objects of analysis differ substantially from discipline to discipline, ultimately we all face the same difficulty: making the leap from unknown to known. For both the arts and sciences this leap is theoretical and requires special attention to methodology. Since our theoretic knowledge of, well, almost everything, is so dependent on analogy, we are impelled to reflect on how it factors into our teaching in order to use it to its full potential.

References

Gale, D. 1999. Improving Teaching and Learning through Chemistry Education Research: A Look to the Future. Journal of Chemical Education, 76(4).

Graduate Student Teaching on Campus

As a Graduate Instructional Developer who works mainly with CTE’s Certificate in University Teaching (CUT) program, I have the privilege of observing graduate students teach in classrooms across campus. Over the past year, I’ve had the opportunity to observe over 35 classes taught by graduate students in all six faculties. I have been incredibly impressed by the quality of teaching by graduate students. They have taken concepts from CTE workshops (e.g., active learning, group work, formative assessment) and applied them directly in their teaching. They are using innovative teaching strategies, technologies, and engaging students in their lessons. The University of Waterloo community should be proud of graduate students’ dedication to, and passion for, teaching.

So how can we support graduate students in continuing to develop their teaching skills?

  • I think many of us would agree the best way to improve our teaching is to practice. In some departments, it’s difficult for graduate students to access teaching opportunities, but guest lectures are a great way to gain experience. If you’re teaching, consider asking the graduate students you supervise and/or your Teaching Assistants whether they’re interested in giving a guest lecture in the course.
  • If you know a talented Teaching Assistant or graduate student instructor, please nominate them for an award! Information regarding Graduate Student Teaching Awards can be difficult to find, so I’ve compiled a list here. If you know of any that are missing from this list, please post a comment and we will add them.

 

Graduate Student Teaching Awards

A) University-wide teaching awards

Amit & Meena Chakma Award for Exceptional Teaching by a Student (deadline: February)

B) Faculty-wide teaching awards

C) Department teaching awards

  • Biology – “Outstanding Graduate/Undergraduate Teaching Assistantship Award” (no link available)

 

Teaching Resources for Graduate Students:

Keys for a TA to Succeed in the Classroom — Aser Gebreselassie

TutorialAs an undergraduate student currently in my third year of ERS at the University of Waterloo, I have had the chance to interact with various types of Teaching Assistants (TAs) over the course of my studies, whether it be in labs, tutorials, in class, via email, or having assignments marked by them. There are plenty of great stories about TAs whom I have had in the past, and unfortunately, a few stories of some questionable TAs as well. Being a successful TA consists of many different aspects, but the three characteristics that I appreciate in a TA is their ability to relate to students, knowledge of the course content, and an ability to communicate effectively and efficiently.

Relating to your students helps build trust between the TA and the student which helps to manage the classroom effectively, as the students will have respect for the TA. Quick but effective activities which I have personally seen in my classes include icebreakers during the first day of meeting your students, as well as having a sense of humour and giving out a positive vibe. A few new things I learnt during the Building Rapport with Students workshop earlier this week was that maintaining positive body language throughout the session gives the students a positive impression about yourself, and learning the student’s names as soon as possible to help develop trust and understanding between the TA and the student.

Knowledge of course content is also key. Most people think that their TAs are those who have taken the course before and have done fairly well in it. This isn’t always the case. Sometimes the TA may never have taken the course, or sometimes they didn’t complete their undergraduate degree in the same faculty as the course they are TAs for. If this is the case, doing the readings and making detailed notes would help a lot. The students understand that a TA is a student as well, and if you as a TA can’t answer a question but are willing to do some research to find the right answer, students find that extremely helpful and are willing to wait to get a right answer, instead of getting a wrong or incomplete answer immediately.

Being able to communicate successfully can make or break the trust and respect that students have for a TA. Setting basic rules on the first day can help a TA significantly. I have had TAs in the past tell us a couple of ground rules: for example, they only will respond to emails during business hours (9 am to 5pm), and that students should not email questions about a majoTutorial 2r assignment the night before it is due as it will be too late to get a response of any value. Prompt responses and setting ground rules can help alleviate pressure from students, and can significantly help boost a TA and student’s relationship. Sometimes TAs respond weeks, even months after receiving an email and it destroys any rapport that they have built with the student.

Lastly, my pet peeve: it is frustrating when students compare grades after an evaluation, and have written two very similar things on their paper, but get two completely different marks. The TA has now lost a lot of the positive feelings that they may have gained over the semester by being inconsistent. Both students are now alienated and concerned, and will go through every little detail of their evaluation to make sure nothing else was missed. Both students will come to the TA with many concerns about their marks. Being consistent, whether it be giving both those students an 85% or a 55%, will save a TA a massive headache.

 

High Failure Rates in Introductory Computer Science Courses: Assessing the Learning Edge Momentum Hypothesis – John Doucette, CUT student  

valleyIntroductory computer science is hard. It’s not a course most students would take as a light elective, and failure rates are high (two large studies put the average at around 35% of students failing). Yet, at the same time, introductory computer science is apparently quite easy. At many institutions, the most common passing grade is an A. For instructors, this is a troubling state of affairs, which manifests as a bimodal grade distribution — a plot of students’ grades forms a valley rather than the usual peak of a normal distribution.

For most of the last forty years, the dominant hypothesis has been the existence of some hidden factor separating those who can learn to program computers from those who cannot. Recently this large body of work has become known as the “Programmer Gene” hypothesis, although most of the studies do not focus on actual genetic or natural advantages, so much as on demographics, prior education levels, standardized test scores, or past programming experience. Surprisingly, despite dozens of studies taking place over more than forty years, some involving simultaneous consideration of thirty or forty factors, no conclusive predictor of programming aptitude has been found, and the most prominent recent paper advancing such a test was ultimately retracted.

The failure of the “Programmer Gene” hypothesis to produce a working description of why students fail has led to the development of other explanations. One recently proposed approach is the Learning Edge Momentum (LEM) hypothesis, by Robins (2010). Robins proposes that the reason no programmer gene can be found is because the populations are identical, or nearly so. Instead of attributing the problem to the students, Robins argues that it is the content of the course that causes bimodal grade distributions to emerge, and that the content of introductory computer science classes is especially prone to such problems.

At the core of the LEM hypothesis is the idea that courses are composed of units of content, which are presented to students one after another in sequence. In some disciplines, content is only loosely related, and students who fail to learn one module can still easily understand subsequent topics. For example, a student taking an introductory history class will not have much more difficulty learning about Napoleon after failing to learn about Charlemagne. The topics are similar, but are not dependent. All topics lie close to the edge of student’s prior knowledge. In other disciplines however, early topics within a course are practically prerequisites for later topics, and the course rapidly moves away from the edges of students’ knowledge, into areas that are wholly foreign to them. The more early topics students master, the easier the later ones become. Conversely, the more early topics that students fail to acquire, the harder it is to learn later topics at all. This effect is dubbed “momentum.”

Robins argues that introductory computer science is an especially momentum-heavy area. A student who fails to learn conditionals will probably be unable to learn recursion or loops. A student who fails to grasp core concepts like functions or the idea of a program state will likely struggle for the entire course. Robins argues that success on early topics within the needed time period (before the course moves on) is largely random, and shows via simulation that, even if students all start with identical aptitude for a subject, if the momentum effect is increased enough, bimodal grade distributions will follow. However, no empirical validation of the hypothesis was provided, and no subsequent attempts at validation have been able to confirm this model. The main difficulty faced in evaluating the LEM hypothesis is that the predictions it makes are actually very similar to the “Programmer Gene” hypothesis. Both theories predict that students who do well early in a course will do well later on. The difference is the LEM hypothesis says this was mostly down to chance, while the “Programmer Gene” hypothesis says it was due to the students’ skill.

In my research project for the Certificate in University Teaching (CUT), I proposed a new method of evaluating the LEM hypothesis by examining the performance of remedial students — students who retake introductory computer science classes after failing them. The LEM hypothesis predicts that remedial classes should also have bimodal grade distributions, because student success on initial topics is largely random. Students taking the course for the second time should be just as likely to learn them as students taking the course the first time round. In contrast, the “Programmer Gene” hypothesis predicts that remedial courses should have normally distributed grades, with a low mean. This is because remedial students lack the supposed “gene”, and so will not be able to learn topics much more effectively the second time than they were the first time.

To evaluate this hypothesis, I acquired anonymized data from four offerings of an introductory computer science course: two with a high proportion of remedial students, and two with a very low proportion. I found weak evidence in support of the LEM hypothesis, as all grade distributions were bimodal when withdrawing students were counted as failing. However, when withdrawing students were removed entirely, only one non-remedial offering was bimodal, a result predicted by neither theory.

Although my empirical results were ultimately inconclusive, my research provides a clear way forward in evaluating different hypotheses for high failure rates in introductory computer science. A follow up study, conducted with data from a university that offers only remedial sections in the spring term (removing the confounding effects of out-of-stream students in the same class) may be able to put the question to rest for good, and facilitate the design of future curricula.

References:

Robins, A. (2010). Learning edge momentum: A new account of outcomes in CS1. Computer Science Education, 20 (1), 37-71.

The author of this blog post, John Doucette, recently completed CTE’s Certificate in University Teaching (CUT) program. He is currently a Doctoral Candidate in the Cheriton School of Computer Science.

Building Instructor-TA Rapport — Donata Gierczycka

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If you have some free time, search the Internet for student reviews of the University of Waterloo. The results may be shocking. While some of the negative reviews are obviously biased, there are some common pieces of advice for the University, contributed by alumni or senior students. Most of these recommendations are related to teaching. Education is what students pay for, and in return they expect a proper environment to develop their hard skills and intellectual capacity. Students also expect to learn how to deal with daily challenges, and want guidance in mastering problem-solving skills as well as soft skills.

Continue reading Building Instructor-TA Rapport — Donata Gierczycka

Make Tutorials Matter – Mihaela Vlasea, Graduate Instructional Developer

It is often mentioned that with large engineering classes, it is difficult to truly engage students and provide them with the opportunity to get involved in classroom activities. I recently had the opportunity to teach a tutorial review session, for which I prepared extensively. I presented the material in a very organized fashion, while being careful to periodically ask a few questions while I was solving problems on the blackboard. Based on the answers I was receiving, as well as some feedback from the class, I felt that students understood the material very well. However, upon marking a final exam question, one very similar to the one I had solved in class, I was quite surprised to see that the majority were not capable to meet the basic framework of the solution. Upon reflecting on this fact, I realized that there is a major difference between students understanding my approach and them being able to solve questions on their own. This realization was quite important, because it has forced me to somewhat re-think my tutorial teaching strategies in the future.

Gear Wheels - photo by Ian Britton via flickr
Get the Gear Wheels Turning  (Gear Wheels photo by Ian Britton via flickr)

Provide more opportunity for students to think about the problem

Instead of dwelling on copying the problem requirements on the board, I could provide students with a copy of the question (wither on a Power Point slide or a handout) and ask them to take two minutes to read it carefully. Then, I would ask students a few clarifying questions to make sure they have understood the problem requirements.

Provide more opportunities for students to solve the problem

After going through the first step, I would allow students to work in pairs or about 2-3 minutes to discuss a few ideas on how to start solving the question. I feel that it is important, as it would make students feel that their suggestions are valuable to the development of the solution. This would increase their level of “ownership” over what is discussed in the class, rather than having a one-way teaching approach.

Facilitate and moderate discussions on alternate solutions

Often times, students only have the opportunity to be exposed to a single solution to a problem. Offering students the opportunity to think and suggest alternate solutions in a supportive environment would be a great opportunity to expose students to more approaches as well as to encourage creativity in engineering classes. This is a critical point that should be endorsed in tutorials. Students may be encouraged to propose an alternate solution in class or they may be to be allowed to post their own solutions on a forum or wiki page, where their peers can discuss or correct their input (this would be a bit harder to moderate, but it would certainly be interesting).

In general, I think that tutorials in engineering should be more student-focused and should promote discussion, rather than being an extension of lecture time. These are just some of my ideas which stemmed from recent experience in teaching tutorials in large engineering classes.