Reimagining the Singapore Pre-university Biology Curriculum with Computational Thinking

Abstract

As the digital landscape expands and grows increasingly relevant, a worthwhile goal is to prepare and equip students with the necessary skills to thrive in such a society. Broadly known as computational thinking (CT), its wide reception is evident from educators’ efforts to incorporate it into national curricula worldwide. While some treat it as an independent discipline, this reflection argues that CT skills ought to be treated as an interdisciplinary skill. Using biology curricula as an example, we highlight the current gaps of integrating CT into biology through our teaching experiences at university level, which we believe stems from the descriptive nature that biology education has adopted in Singapore. With pre-university students seldom engaging in algorithmic approaches to analyse and understand biological data, we find that many students struggle to construct and test models using computational approaches at the university level. As such, we leverage on our experiences and propose a curriculum design at the pre-university level that embeds authentic application of CT into biological practice by mapping conceptual parallels between biology, computer science and CT. In the process, we detail elements of the curricula that are designed to cultivate deeper interdisciplinarity alongside the challenges that may be experienced in its setup. Envisioned to work in tandem with university courses, this works towards a first-point insertion for enabling future learners to understand more advanced digital literacies such as data analytics and machine learning that will be critical, if not commonplace, in the future field of biology.