I have used various lightweight feedback methods in my teaching for many years. I began using these informal approaches when I started teaching in colleges. At this time, the college didn’t have any formal module feedback mechanisms (such as module evaluations) in place, and I needed insight from the students to develop my teaching style.
I started by conducting small question and answer sessions at the end of a lecture, where I would simply ask the students what they thought of the session, and if there was anything they were still unsure about. However, I quickly realised that the students would often tell me what I wanted to hear, rather than what they were actually concerned about. As such, the feedback I received was almost never critical, and rarely any use in developing my sessions.
I decided that the students needed some anonymity when providing feedback, so I moved into an anonymous online survey (powered by google docs). However, while the students were initially supportive of this initiative their interest (and engagement) didn’t last. The survey simply required too much investment from the learners.
Before my second semester at the college I read about an approach called “the muddiest point”, a lightweight feedback strategy. In the the muddiest point method students are asked to write down the one point of a lecture they found most confusing. The lecturer then collects these single items, collates them, and addresses them in the following lecture. The points are anonymous, and require very little investment from the student making it one of the simplest classroom assessment techniques. I felt that this was a format I could work with. A big advantage of these methods is how quickly the feedback can be collated. As you are only dealing with a post-it note, you can read and assess all the feedback quickly after a lecture. Even with class sizes of over 300 students, it has never taken me more than half an hour to go through all the notes. Furthermore, this speed allows you to make incremental changes to your delivery on a per-lecture basis, allowing students to quickly see the impact of the feedback they provide.
I devised my own similar approaches based on evidence I collected by through testing, and other similar lightweight methods. After a year of using these method I had developed three main variations.
Variation 1 (feedback faces): In the feedback faces approach the students are all provided with a post-it note at the beginning of the lecture. At the end of the lecture they are asked to draw either a smiley, indifferent, or frowny face on their note, and a short comment (a few words) on why they had left that particular rating of the lecture. This approach is particularly useful for gaining insight into the general satisfaction of the module cohort, and allows you to identify best practice.
Variation 2 (bimodal notes): In this method the cohort are given two different colours of post-it notes of a random distribution, (for illustration, pink and yellow). At the end of the session, all the students with one colour note (eg pink) are asked to write something positive about the session, all the students with the other colour (eg yellow) are asked to write something critical. Sometimes the vast majority of the learners have enjoyed the session and this is what they want to focus on in their feedback. This approach is great at forcing critical feedback out of the group, and I find it particularly useful when I am experimenting with a new delivery style.
Variation 3 (feedback graph): This method works well with smaller groups, I have used it with up to 90 students. In the feedback graph approach you again give students a postit note, and ask them to write down a single piece of feedback. They can determine whether it is positive, critical or otherwise. Outside the lecture theater you hang a large piece of flipchart paper, with two axis drawn on it. Each of these axis should represent something you wish to measure about your lecture, for example, “engagement” and “clarity”. At the end of the lecture the student should stick their post-it note on the graph in a position that represents how the lecture performed against these two measures.
I used these methods to develop my practice towards achieving my PGCertHE. It allowed me to make changes to my modules based on rapid student feedback without needing to wait for the data from module evaluations, which which generally arrives after the conclusion of a module.