Team Teaching: Make it two!

In this small research summary of my 2016 article in Teaching in Higher Education (here), I make the case for team teaching, including PhD students in your lecturing! In our specific case, we teach software modelling. However, the concept might apply to many different lecture setups.

Team Teaching and Pair Lecturing

In team teaching, multiple teachers are involved in teaching a single course. Often, the format is to include different experts to teach different parts of a multi-disciplinary course. For example, I am currently taking a course on medicine for engineers. Here, lectures on different parts of the body, e.g., the cardiovascular system and the central nervous system, are given by different specialists in the respective areas.

Another case of team teaching is pair lecturing, giving a single lecture in a pair (or a team) of teachers. In this case, the teachers take turns explaining things and jump in when needed. The rationale is that multiple lecturers can give multiple explanations to a complex topic, thus facilitating understanding. Also, when one teacher is currently talking, the other teacher can observe. As most of us know from our student times (and from talks we have listened to at conferences), it rather easy to spot as a bystander when the audience is not following. In those cases, the bystander jumps in and gives another explanation that might help the audience to understand.

Pair Lecturing to Verbalise Cognitive Processes

When lecturing about software modelling, we often face the challenge that modelling is a cognitive process. Apart from design patterns, there are very few established principles on how software models are built, what they should contain, and how you construct them in a step-wise fashion. Essentially, the process of building an abstract model of something is mainly going on inside our heads. Making this process explicit to students is challenging.

One way to explain this process is, according to our experience, pair lecturing. In class, we exemplify the modelling process by constructing software models together at the whiteboard. While we built the model, we have to explain to each other what we are drawing. Additionally, we might have to clarify, if our explanation is insufficient, argue, if our approach is questioned by the other teacher, or correct, if we together reach the conclusion that a different solution is better. This discussion at the whiteboard is, essentially, a verbalisation of the cognitive process that would be hidden to students if we simply drew the solution on the board. Similarly, by just explaining our own solution, much of the discussion would be omitted.

Apart from verbalising the modelling process to students, a positive side-effect is that many of the questions students might have during class are already brought up by the other teacher. This encourages further questions and participation from student side (in our experience), and makes sure that questions are actually asked.

Teacher Synchronisation & Costs

Traditionally, pair lecturing has been criticised for its high costs. Clearly, including two teachers instead of one raises the teaching costs.

Our approach to lower these costs dramatically is to include PhD students instead of members of the faculty. As the main teacher is still present, the PhD student does not need to be as knowledgeable in the topic as the main teacher. In fact, not knowing too much might be helpful, as the PhD student will in this case ask similar questions as the audience would – he/she builds a bridge between the main teacher and the students.

Now you might ask yourself: “OK, so those guys just use their PhD students because they’re cheaper. That’s it?”. No. The use of PhD students in pair lecturing is far from accidental in our case. In the Swedish university system, PhD students have a certain percentage of teaching duties. Typically, this duty is spent on group supervision in labs or project work. This, however, means that the PhD students need sufficient knowledge to supervise. Furthermore, they constantly need to synchronise with the main teacher on course contents, progress, and similar issues.

Including PhD students in the lectures effectively removes the need for additional synchronisation. At all times, the PhD student is aware of what is going on in the lectures and knows what the main teacher explained. Hence, additional synchronisation meetings are not needed. Furthermore, there is a lower risk that the PhD student will give explanations in the supervision sessions that are in contrast to the lectures.

Finally, pair lecturing using PhD students facilitates teacher succession. In our case, we had a large staff turnover in the last couple of years. This turnover suddenly left a lot of courses without teacher. In the case of the software modelling course, the PhD student that was involved in pair lecturing knew about all course moments, rationale behind them, and could essentially take over the course, or at least easily hand it over to the new teacher. Even if the main teacher kept teaching the course, it was easier to handle issues such as sick leave, business travel, or other cases in which the main teacher could not be present.


To sum up the entire article: In our experience, pair lecturing (lecturing with two teachers at the same time) using PhD students as part of the lecturing team helps:

  • by giving students multiple explanations to a single problem,
  • by verbalising thought processes and discussions,
  • and by engaging the student audience more than traditional lectures.

Our course evaluations also clearly show that students see these benefits!

With respect to the course setup, pair lecturing helps:

  • by synchronising between the main teacher and the teaching assistants, effectively removing the need for synchronisation meetings,
  • by avoiding contradicting statements between main teachers and teaching assistants,
  • and by effectively creating a “backup teacher” in case the main teacher is not available or even leaves the university/the course.

The full article includes a lot more details, empirical data, and reflections!

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