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The interdisciplinary mathematics and science (IMS) project
The challenge
The Interdisciplinary Mathematics and Science (IMS) project is a response to a widely recognised need for significant innovation in primary school mathematics and science learning. Despite decades of curriculum reform, a growing number of students fail to acquire the essential quantitative and scientific skills required for work and life, and increasingly students do not engage with post compulsory pathways in these subjects.
IMS aims to address these problems by researching the development of an inter-disciplinary pedagogical approach and curriculum framework where primary school students generate and evaluate representations and models to support key foundational learning in the STEM disciplines of mathematics and science.
IMS aims to enrich learning through two interconnected principles, which are key to the nature of the unit design and the pedagogy. The first principle concerns a focus on students constructing, evaluating, and refining multimodal representations, enacted through a four-stage IMS pedagogical model. The second principle concerns the nature of the interdisciplinary relationship: that mathematics and science are mutually reinforcing such that fresh learning occurs in both subjects.
Project overview
This international, longitudinal project aims to investigate the effectiveness of an innovative interdisciplinary learning approach in mathematics and science. Through collaborating primary schools in Australia and the United States of America (USA), it is investigating how students’ invention and transformation of representational systems can connect to support deeper reasoning and learning. The project will form the bases for new curricular designs that leverage students’ representational practices across science, technology, engineering and mathematics (STEM) disciplines to promote more robust and generative knowledge within and across these subjects.
Our inter-disciplinary approach focuses on students creating, organising and analysing representations of visual and numerical data. These processes align with how scientists and mathematicians reason through using material tools and representational systems to build knowledge in each discipline. Through a guided inquiry pedagogy, students in our study explore topics that entail dynamic systems, such as ecology and astronomy, where data generation, modelling, and claim-making can draw meaningfully on methods, processes and concepts from each discipline. Both disciplines provide potential representational entry points to deeper learning. For example, students construct and analyse patterns in ecosystem function and organisation to develop the mathematics of data variability, chance, and measure. This in turn raises questions and deepens science understandings.
The project aims to:
- Develop an inter-disciplinary framework, focused on the creation and evaluation of representational systems, to guide students’ foundational learning in science and mathematics.
- Design, implement and evaluate a longitudinal intervention for primary students using this framework.
- Develop constructs to characterise and assess students’ developing understanding and dispositions over the course of the study
- Identify strategies that support teacher professional learning relevant to this approach
- Review and inform current Australian curricular policy and practice in mathematics and science.
The interdisciplinary framework has two main components. The first involves the strategic design of tasks that link mathematics and science, in different topics for each subject. This inevitably involves judgments about curriculum fit, and level of knowledge and practice of the students, such that the two subjects talk to each other in fresh and productive ways.
The second component is the pedagogy through which students are guided through a cycle of representation construction, evaluation and refinement, aligned with the scientific and mathematical disciplinary practices. While the approach reflects principles developed in previous research, designing details of pedagogical practice for the different sequences involves close collaboration with teachers.
Outcomes
The project has created 13 learning sequences and developed theoretical and practical perspectives that have been presented at a range of conferences, teacher workshops, pre-service teacher resources, and in journal publications and book chapters.
- The learning sequences, which exemplify the theoretical and practical outcomes of the project, are presented on this website.
- The major research findings relate to:
- The development of a pedagogy based on the construction and collaborative refinement of representations, reflecting mathematics and science disciplinary epistemic processes
- The articulation of ways in which mathematics and science productively interrelate to support learning in each, across a range of topics, concepts and practices
- The nature and quality of student learning deriving from the approach
- Teachers’ responses to the approach – challenges, and enablers.
Building on previous work that productively linked science and mathematics, particularly that of Lehrer and Schauble, IMS has explored this interdisciplinary linking across a range of science topics and mathematical concepts and practices. The key principles are that a) the mathematics and science concepts and practices are mutually reinforcing, b) the interdisciplinary tasks lead to fresh learning in each subject, and not simply application of known procedures and concepts, and b) that the reasoning and learning in each subject reflects disciplinary knowledge building practices, involving the invention and guided refinement of representational systems.
Project team
- Deakin Distinguished Professor Russell Tytler (Deakin University)
- Associate Professor Peta White (Deakin University)
- Professor Vaughn Prain (Deakin University)
- Dr Lihua Xu (Deakin University)
- Professor Joanne Mulligan (Macquarie University)
Partner investigators
- Professor Richard Lehrer (Vanderbilt University)
- Professor Leona Schauble (Vanderbilt University)
PhD candidate
- Chris Nielsen (Deakin University)
Research assistants
- Melinda Kirk (Deakin University)
- Dr Chris Speldewinde (Deakin University)
Timeline
2018 – 2022
Project partners
- Deakin University
- Macquarie University
- Vanderbilt University
Funding
This project is funded by a Discovery Project grant from Australian Research Council to the value of $434,716