Melbourne Graduate School of Education - Research Publications
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ItemWhat data and analytics can and do say about effective learning(SPRINGERNATURE, 2017-12-09)The collection and analysis of data about learning is a trend that is growing exponentially in all levels of education. Data science is poised to have a substantial influence on the understanding of learning in online and blended learning environments. The mass of data already being collected about student learning provides a source of greater insights into student learning that have not previously been available, and therefore is liable to have a substantial impact on and be impacted by the science of learning in the years ahead. However, despite the potential evident in the application of data science to education, several recent articles have pointed out that student behavioural data collected en masse do not holistically capture student learning. Rogers contends that this positivist view of analytics in education is symptomatic of issues in the social sciences more broadly. While there is undeniable merit in bringing a critical perspective to the use of data and analytics, we suggest that the power and intent of data science for understanding learning is now becoming apparent. The intersection of the science of learning with data and analytics enables more sophisticated ways of making meaning to support student learning.
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ItemOn the Irrelevance of Neuromyths to Teacher Effectiveness: Comparing Neuro-Literacy Levels Amongst Award-Winning and Non-award Winning Teachers(FRONTIERS MEDIA SA, 2018-09-11)A number of studies have recently demonstrated a high level of belief in 'neuromyths' (fallacious arguments about the brain) amongst trainee and non-award winning educators. The authors of these studies infer this to mean that acceptance of these neuromyths has a negative impact on teaching effectiveness. In this study, we explored this assumption by assessing the prevalence of neuromyth acceptance amongst a group of internationally recognized, award-winning teachers and comparing this to previously published data with trainee and non-award winning teacher populations. Results revealed the acceptance of neuromyths to be nearly identical between these two groups, with the only difference occurring on 2 (out of 15) items. These findings suggest that one cannot make simple, unqualified arguments concerning the relationship between belief in neuromyths and teacher effectiveness. In fact, the idea that neuromyths negatively impact upon teaching might, itself, be a neuromyth.
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ItemExploring misconceptions as a trigger for enhancing student learning(Higher Education Research and Development Society of Australasia, Inc, 2017)This article addresses the importance of confronting misconceptions in the teaching of the STEM disciplines. First, we review the central place for threshold concepts in many disciplines and the threat misconceptions pose to quality education. Second, approaches will be offered for confronting misconceptions in the classroom in different contexts. Finally, we discuss what we can learn about these approaches and the common threads that reveal successful approaches. These steps have been explored in relation to four case studies across diverse disciplines. From these case studies, a set of principles about how best to address misconceptions in STEM disciplines has been distilled. As conceptual knowledge increases in importance in higher education, effective strategies for helping students develop accurate conceptual understanding will also be increasingly critical.
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ItemModels for understanding student engagement in digital learning environments(Australasian Society for Computers in Learning in Tertiary Education, 2016)Digital learning environments are increasingly prevalent in higher education. The flexible and less constrained nature of these environments, means students often need to be more autonomous in managing their own learning. This implies that students are sufficiently selfmotivated to successfully engage in autonomous learning. The concept of "student engagement" has shown promise in assisting researchers' and educators' understanding of how students' general involvement in study, and their more specific completion of learning tasks, can lead to beneficial outcomes in digital learning environments. However, student engagement has taken on multiple, diffuse definitions in higher education creating confusion about what engagement is and how best to promote it. In this paper we build on a model of engagement from organisational psychology that offers insight into task-level engagement. Established models in the area of student motivation are integrated to bring clarity to the construct at task-level in digital learning environments.
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ItemEditorial: Brain, mind and educational technology(ASCILITE, 2016)There has been substantial hype around the growing body of research investigating how learning occurs in the brain. Over the last century, in particular, we have learned more about how the brain functions than has been discovered throughout history (Albright, Jessell, Kandel & Posner, 2000). New imaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have been pivotal in driving this research agenda. The emergence of the field of cognitive neuroscience has further helped to align foundational work on uncovering how the brain works with what is known about learning from the psychological sciences. In combination with education, new fields such as ‘educational neuroscience’ have emerged with the aim of translating the findings from the laboratory to the classroom (e.g. Ansari, Coch & De Smedt, 2011).
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ItemConfidence drives exploration strategies in interactive simulations(ASCILITE, 2016-12-01)Maximising the benefits of digital learning environments requires understanding how students process what they are exposed to in these environments. Besides approaches based on examining information processing within the cognitive domain, the importance of including emotions has been recently addressed. This study aimed to explore emotional dynamics during discovery learning in an interactive simulation, with continuous measures of self-reported confidence and challenge. Interactions from participants were recorded and two groups were created according to the exploration strategy used: systematic or non-systematic. Visual exploration was also measured by eye tracking as well as knowledge at pre- and post-test. Results suggest that learners using a systematic exploration strategy ran significantly more simulation cycles than non-systematic learners. Moreover, the latter group reported to be significantly less challenged and more confident about understanding the material. These results emphasise the importance of student perceptions of their capabilities when learning in flexible, less structured digital environments.
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ItemAll roads lead to Rome: Tracking students’ affect as they overcome misconceptions(ASCILITE, 2016-11-28)Helping students to overcome misconceptions is a complex problem in digital learning environments in which students need to monitor their own progress and self-regulate their own learning. This is particularly so in flexible, discovery-based environments that have been criticised for the lack of support and structure provided to students. Emerging evidence suggests that discovery-based environments might be ineffective due to students becoming confused, frustrated or bored. In the study reported here, we examined the affective experience of students as they worked to overcome a common misconception in a discovery-based environment. While the results suggest that students experience a range of emotions, they all successfully overcame their initial misconception. Implications for the investigation of student affect in discovery-based environments and the design of these environments are also discussed.