Use of Word Clouds to Understand Target Learners

Description

Currently, the physiotherapy programme includes 120- 190 students in a large-group teaching (lecture). While there is some benefits to delivering teacher-directed content to the students in this way, it is somewhat difficult to engage students and to establish the current understanding of the cohort as a whole.

While preparing for a lecture that was to be presented following the “lunchtime lull”, I considered introducing something different to help break the monotony; for students to interact and contribute to; to provide me with an understanding of their current learning so could refocus the remainder of my lecture; and for students to get instant feedback on what others had contributed to. In order to attend to the above, I utilised Mentimeter Word Clouds into the middle of my lecture.

Reflection on Understanding Target Learners

While I have reflected on the benefits and constraints of the use of Mentimeter in another post (see 1a); here, I will reflect on how the use of the interactive Word Cloud enabled a better understanding of the students’ current learning. 

I have always found it difficult to gauge the overall level of learning of students in large-group environments- and it appears when discussing with others that I am not alone. With close to 200 students in a lecture theatre, it is those in the front row or only a handful of the same individuals that seem to consistently share their opinions during the lecture. 

The use of the interactive Word Cloud enabled more engagement to the online-based questions than if this was asked verbally. For example- when asked, “what are some effects of aging on the neuromuscular system?”- there were over 80 responses. I found it interesting to see the momentum grow as subsequent students engaged with the interactive question. It seemed to me that by seeing peer responses go up on the data show in “real time”, this provided others confidence of what they were thinking. 

It was relatively easy to establish some of the common themes of what the students were considering in response- with those that had multiple responses represented either larger, or more central. This helped direct my understanding of their current knowledge, and what to emphasis on in the remainder of the lecture. Having the responses more central, did not equate to always being correct, however. However, this did provide me a great opportunity to address the understanding there and then. Likewise, what was more “on the rim” or smaller may have been deemphasised, with some discussion as to why a particular response could be warranted (and/ or correct)… 

In the future, I will use the MentiMeter Word Cloud function which enables student-directed learning as they self-pace through a series of questions. This may be provided ahead of the lecture (though may not provide the confidence to answer as described above); or made available during the time of the lecture only. Watch this space!

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