TAN Chun Liang
Department of Architecture,
College of Design and Engineering (CDE), NUS
Tan, C. L. (2024). Infusing contextual elements with generative AI tools to reinforce learning for students [Lightning talk]. In Higher Education Conference in Singapore (HECS) 2024, 3 December, National University of Singapore. https://blog.nus.edu.sg/hecs/hecs2024-cltan/
SUB-THEME
Opportunities from Generative AI
KEYWORDS
Urban Greening, Site context, Video assignment, Peer review
CATEGORY
Lightning Talk
EXTENDED ABSTRACT
The recent rise of AI content generators has had significant impact on both learning and teaching in educational institutions. Although the university encourages the responsible use of AI content-generation tools, a point of concern is on the authenticity of student report submissions. How do we ensure that usage of such platforms can help us augment the learning experience and not become a tool for students to conveniently churn out AI-generated reports at the eleventh hour to submit as their own?
This is an important question to address for the course LA5303 “Urban Greening: Technologies and Techniques”, where students are taught ways to utilise urban greenery to improve the environment. Without a real understanding of the course content, students may not learn about the proper ways of urban greening and fall back to more superficial and cosmetic treatments of the landscape, leading to greenwashing.
Drawing on the Significant Learning pedagogical framework (Fink, 2013), I try to tap on the Human Dimension, in learning about oneself in others to reinforce learning. I explored peer learning and the theory of Distributed Cognition (Hutchins, 2020) to acquire knowledge through an individual’s social and physical environment. In this manner, cognitive resources can be shared socially, and students can achieve more as a group than with just individual effort.
Strategy 1: Experiential learning, peer learning, and industry talks
Singapore is adorned with many examples of urban greenery projects, ranging from ground-level parks to sky-rise greenery projects. Since this course is about urban greenery, I began to introduce more activities to encourage more experiential and peer learning: where students go for site visits, assess real projects in Singapore and learn from each other instead of having me give them second- or third-hand information via lectures.
Figure 1. Learning journey to SproutHub @ Henderson
Learning journeys to prominent urban greening spaces such as SproutHub@Henderson (Figure 1) and talks by industry partners (Figure 2) were organised to let students gain first-hand experience of the components of urban greenery covered in this course.
Figure 2. Talks by Mr Christopher Leow, prominent urban farmer (Top row) and Representatives from Elmich Pte Ltd, sharing green wall and green roof products (Bottom row)
In addition, students were tasked to visit urban greenery projects of their choosing and to create bite-sized (1-minute) videos documenting their learning (Figure 3). The videos were subsequently uploaded onto an online bulletin board (Miro) for others to review and comment on (Figure 4). Students were given the opportunity to provide comments on the videos produced by their peers. This directly increased their learning of urban greenery projects by 50 (total number of students in the course), as knowledge is now crowdsourced and contextual.
Figure 3. Screenshots of a video done by a student, documenting urban greenery learning
Figure 4. Comments from peers on the Miro board
Strategy 2: Pre-emptive strike to nullify the impact of A.I. generated content
Instead of warning students not to use AI-generated content, I insisted that it was the first thing they did for their assignment. Students had to append their prompts and AI-generated results in their report and show how they built on the AI content to come up with their final report. The AI-generated content thus became another layer of educational scaffolding for the students. More importantly, students were instructed to include specific examples of how to improve on urban greening using examples of videos done by their peers from Strategy 1. In this case, it became less likely for students to cheat with AI content generators such as ChatGPT because the examples are unique.
REFERENCES
Fink, L. D. (2013). Creating significant learning experiences: An integrated approach to designing college courses. John Wiley & Sons.
Hutchins, E. (2020). The distributed cognition perspective on human interaction. In Roots of human sociality (pp. 375-398). Routledge.