From the Guest Editors: The Science Of Learning Centre: A collaboration of neuroscience,psychology and education to inform evidence-based practice in classrooms

Introduction

This special issue comprises a set of contributions that represent a small selection of the work that is being undertaken by researchers involved in the Science of Learning Research Centre (SLRC). The SLRC is a special initiative funded by the Australian Research Council (ARC) to create a trans-disciplinary research centre that brings together researchers from education, psychology and neuroscience in order to contribute new perspectives on educational issues. It is funded under an Australian Research Council Grant: ARC-SRI: Science of Learning Research Centre (project number: SR120300015). At the time of this issue, the SLRC has been in existence for three years. As a consequence, the work represented here is necessarily preliminary and primarily a work-in-progress.

It seems valuable, however, to report some early findings from the SLRC's work for a couple of reasons. Firstly, the research itself and the findings presented are valuable. Secondly, an underlying theme that connects the papers is the challenge of conducting trans-disciplinary work, as well as illustrating to readers the demands of bringing together different research methods and perspectives. Some of our readers will probably be able to relate similar experiences from such endeavours.

The SLRC is not the first centre of its type in the world, but it is the first in Australia and still only a relatively small number of research hubs are trying to bring the three disciplines together. The National Science Foundation in the USA, for example, has set up five research centres including the Center of Excellence for Learning in Education, Science, and Technology, Center for Learning in Informal and Formal Environments, Pittsburgh Science of Learning Center for Robust Learning, Spatial Intelligence and Learning Center; Temporal Dynamics of Learning Center and the Visual Language and Visual Learning Center. In London, the Centre for Educational Neuroscience is a collaboration among Birkbeck, University of Central London Institute of Education, and the University College London. The University of Chile has established a Laboratory of Neuroscience and Cognition within its Center for Advanced Research in Education. In Singapore, the Nanyang Technological University has established a Centre for Research and Development in Learning, which is focused on educational neuroscience. The University of Hong Kong’s Faculty of Education is creating a Sciences of Learning Strategic Research Theme. This is certainly not an exhaustive list but illustrates that this area of research is emerging across the globe.

There are mixed opinions about how successful a trans-disciplinary approach might be. Some have reservations. John Bruer (1997) questioned how useful neuroscience can be for education and called the link between the two disciplines a ‘bridge too far.’ Bruer felt that, “neuroscience has discovered a great deal about neurons and synapses, but not nearly enough to guide educational practice.” That may have been true at the time of writing in 1997, but since then, as noted above, there are now many researchers worldwide committed to building the bridge between the disciplines. More recent opinions, however, are in favour of creating a trans-discipline of the Science of Learning. For example, Sigman et al. (2014) point out that Breuer’s bridge too far argument assumes a linear flow from neuroscience to cognitive psychology and education. They propose that “neuroscience and cognitive psychology should work in synergy, providing complementary tools to understand the mind and act in concert to improve education.” It is this latter approach that the SLRC is taking in its research and expressly sees there being a two-way pipeline from the neuroscience laboratory to the classroom and from the classroom to the neuroscience laboratory.

To facilitate this bi-directional flow, the SLRC invested in two research classrooms. The Educational Neuroscience Classroom, located at the University of Queensland, provides a small space with computers, eye-tracking hardware, and electroencephalograph (EEG) equipment that can be used to study small groups of learners. The Learning Interactions Classroom, at the University of Melbourne, provides a full-sized classroom equipped with an array of high definition cameras and directional microphones that can capture a live lesson from multiple angles for later analysis. These two spaces provide research opportunities that range between a real classroom and a laboratory. The SLRC also uses equipment in actual classrooms, and the research featured in this special issue was conducted in these different research facilities.

This issue contains four articles which illustrate the range of work that is being pursued in the SLRC.

The first paper by Morris and Sah, Neuroscience and education: mind the gap, discusses the challenges of the research in the Science of Learning trans-disciplinary space. It highlights a history of research in education on learning that operated in parallel with, rather than informing – and potentially being informed by – other fields such as cognitive psychology and neuroscience. Funding and research initiatives from organisations such as the OECD and others – including our own ARC – have provided greater impetus to collaborate across these fields, but fundamental challenges exist at a number of levels. For example, how can models of learning from animal-based neuroscience research be translated to models of classroom practice involving multiple interacting humans? Similarly, the new ‘science of learning research’ needs to identify differences in conceptual understanding within and between disciplines that interferes with collaboration. The authors not only provide examples of successful translation, including the intermediate steps between the more disparate fields that assisted with this translational process but also advocate for a model of ‘bottom-up’ approach to trans-disciplinary research where experience and expertise is gained in each other's fields.

The article on Multimodal representations during an inquiry problem-solving activity in a Year 6 science class: A case study investigating cooperation, physiological arousal and belief states by Gilles, Carroll, Cunnington, Rafter, Palghat and Bednark, provides an example of the issues that researchers must address in shaping research projects in the trans discipline that forms the Science of Learning. The study brings together educational theory on group work in the classroom and on the use of representations in science learning with measures of students’ individual physiological reactions. Neuroscience methods for sensing brain activity are generally designed for controlled, laboratory settings, usually working with individuals. Therefore, they are not easy to adapt to studying interactivity among students in the uncontrolled setting of a live classroom. As a result, proxy methods have to be used, such as measuring physiological arousal. The Gilles et al. study describes how doing so requires the application of methods that are new in classroom research and result in the need for new ways of interpreting data. For example, Figure 1 in the article shows the use of connectivity analysis to represent the interpersonal correlation between students’ physiological electrodermal activity during whole class activities compared to small group activities. While the paper describes just a single case study from a larger study, it shows the challenges and opportunities offered by taking a trans-disciplinary approach to examining learning activities in live classrooms.

The article by Timms, DeVelle and Lay entitled, Towards a model of how learners process feedback: A deeper look at learning illustrates the challenges of bringing a trans-disciplinary perspective to research on learning in digital environments. The authors describe the early steps they have taken to investigate and validate the theoretical model they have created of Learner Processing of feedback in intelligent learning environments (LP-FILE). The research begins by looking at intelligent learning environments (ILE) that have been used in actual classrooms and are now brought into the SLRC Learning Interactions Classroom in order to study them in a more controlled environment. The paper describes a small behavioural study in which learners’ use of the ILE was recorded along with video, audio and physiological data. The study found, though, that there are limits to what can be derived from data gathered in this way and the authors are exploring how other methods from the learning sciences, such as eye-tracking, EEG or functional magnetic resonance imaging (fMRI) might be more suited to studying learners’ processing of feedback in order to validate the LP-FILE model.

The article by Buckley, Reid, Goos, Lipp and Thomson Understanding and addressing mathematics anxiety using perspectives from education, psychology and neuroscience, highlights the potential to translate findings by identifying strategies to reduce the negative consequences of mathematics anxiety (MA). State-based MA affects task performance, while trait-based MA leads to the avoidance of study and employment involving mathematics. The authors emphasise that cognitive psychology and neuroscience have made significant advances in identifying the effects of MA on performance, which have resulted in the development of interventions in clinical psychology and education to reduce the negative consequences of MA. Buckley and coworkers hypothesise that a trans-disciplinary approach to intervention appears the most efficacious approach. Understanding and treating both the physiological basis of symptoms and the cognitive/emotional consequences of state MA on performance could potentially aid students with the management of their anxiety during mathematics performance, while also helping to address the underlying beliefs that contribute to avoidant behavior. The authors highlight that such interventions must also be able to target pre-service teachers, whose MA negatively influences their teaching and the performance and MA of their students.

Conclusion

The articles presented in this special issue give an indication of how researchers in the SLRC are attempting to build bridges between the research disciplines of education, cognitive psychology and neuroscience. They show how the authors are approaching this challenge by designing research studies that apply methods and equipment from across the three disciplines. The research presented is still in its early stages and we look forward to seeing further publications as the work progresses.