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A Topic-Based Approach Towards Quantitative Reasoning Education
conference contributionposted on 25.03.2022, 08:58 by Edmund Low
Quantitative reasoning (QR), the ability to thoughtfully, systematically make use of data as a resource to answer questions, as well as be critical consumers of information, is one of the essential skills of the 21st century (Song and Zhu, 2016). In the University Scholars Programme (USP) at the National University of Singapore (NUS), a topic-based approach is used for QR education to a multi-disciplinary cohort of students. Such an approach relies on a substantive topic to structure instruction and discussion on the mindset of reasoning with data, and skillsets including inferential statistics, data visualisation and modelling. Current topics span environmental quality, epidemics, and the psychology of human relationships. Having a “basket” of different modules provides curricular flexibility for students to choose the topic which most appeals to them to fulfil the core QR requirement at USP, while also keeping class sizes small. The use of a consistent topic, and specifically choice questions within said topic, to frame quantitative analyses facilitates students making connections between seemingly disparate quantitative concepts. Such connections-making is crucial to help students avoid “not seeing the forest for the trees”, and develop an overall mindset of quantitative thinking. Having this cohesive framework in linking to real-life applications also imparts relevance, tangibility and purpose to the teachings for the students, a benefit which has also been found in other studies (Theall, 2004; Schulten 2017). The common platform of a singular substantive topic in addition serves as an equaliser amongst the varied disciplinary backgrounds of USP students, allaying inhibitions in speaking out and thereby facilitating interactions that promote interdisciplinary learning. In particular, this presentation focuses on the pedagogical evolution of a QR module at USP that uses environmental quality as its substantive topic. Data in the form of student feedback and class assignments demonstrate that learning outcomes were generally met; student performance in independent research projects and events such as data hackathons also point to an ability to transfer what was learned beyond the classroom. Challenges for the topic-based approach include finding a common set of goals and skillsets that unify disparate modules with different subject foci. In support of the various topic-based QR modules, and to complement instructor consultations, a QR centre staffed by student assistants offering peer help to all students has also been set up.