Who?
Dr. Precious A. Brenni, Assistant Professor in Finance at the Durham University Business School.
What?
The activity involved the use of LEGO® bricks for collaborative model-building, aimed at demonstrating how economic fundamentals can help explain changes in house prices.
When?
The activity was held in the first term of the 2024/25 academic year as part of a workshop in Real Estate Finance, a third-year undergraduate module. Of the 177 registered students, 112 attended the LEGO®-based sessions.
Why?
In the past, the workshop followed the traditional format, where students received questions in advance and were expected to attempt them before the session. During the workshop, the tutor would review the expected solutions and address any student queries. Specifically, students were expected to read a relevant paper about housing bubbles (Mayer, 2011) and provide individual written responses to the associated questions. There was no use of LEGO®.
Over the years, my experience with the traditional format has revealed significant challenges with student engagement. Most students were reluctant to participate, sometimes only offering to contribute to discussions after directly volunteering them. Similar observations have been echoed by colleagues in the department, reinforcing this concern. This lack of active involvement highlights the need to explore alternative teaching methods/activities that encourage greater student engagement and foster a more interactive learning environment, hence the decision to introduce the LEGO®-based activity. This was along the lines of playful learning, which has been shown to help students develop greater creativity (Chang et al., 2011) and improve educational experiences for both students and tutors (Whitton and Langan, 2018).
How?
Students were provided with the LEGO® bricks for the exercise. They were randomly assigned to activity groups, with the average group having six students. Each workshop had an average of five activity groups. Each group had to select one of three distinct models (finance, construction-cost and affordability-based) to build, and this had to be decided on collectively. This was aimed at fostering teamwork and enhancing their decision-making skills. Students were still encouraged to read at least relevant portions of Mayer (2011) prior to the activity. However, unlike in previous years, they were not asked to speak to their written responses. Instead, they applied their understanding of the paper to building the models. Students were also encouraged to utilise generative AI to support idea generation and refinement prior to building the models. Each group had just under 30 minutes to build and explain their model, and to respond to any questions.
How did it go?
Overall, the activity was a great way of ascertaining student assimilation of concepts related to economic fundamentals and house prices, which had previously been covered in class. It was very hands-on, facilitating active student participation and innovative learning. Apart from allowing students to learn while having fun, it was a great way to encourage greater engagement with academic literature. The use of generative AI by the students was also a powerful reminder of the changing technological landscape, which makes it relevant to incorporate generative AI into low stakes learning activities and equip students for life beyond university.
Fitting in another “traditional” workshop question during the 50-minute timeslot allocated for each workshop meant that the students had very limited building and discussion time. There were also a tiny minority of students, who though assigned to a group, chose not to engage much with their teammates during the activity.
Students were invited to respond to an anonymous online survey after completing the activity, with a valid response rate of about 29%. The close-ended questions were mostly based on a standard 5-point Likert scale. Highlights of the results indicate that the activity was enjoyable and not frivolous, although students would have wanted more discussion time. There was also a desire to see other modules replicating playful learning approaches. The open-ended responses to two questions are presented in the word cloud figures below.
What’s next?
Future rollouts will seek to enhance peer-to-peer learning by creating ample time and opportunities for discussion and interaction across activity groups. This will also allow students the opportunity to learn about models they did not create. Further, it will be great to also showcase good model exemplars to firm up students’ understanding in future. Against the backdrop of the few students who chose not to engage with their groups, it would be useful to study personality differences and responses to playful learning activities in small group contexts.
References
Chang C. P., Chuang, H. W. & Bennington, L. (2011). Organizational climate for innovation and creative teaching in urban and rural schools. Quality and Quantity: International Journal of Methodology, 45, 935–951.
Mayer, C. (2011). Housing bubbles: A survey. Annu. Rev. Econ., 3(1), 559-577.
Whitton, N. & Langan, M. (2018). Fun and games in higher education: an analysis of UK student perspectives. Teaching in Higher Education, 24(8), 1000–1013.