Developing Resilient Agency in Learning: The Internal Structure of Learning Power

Abstract

Understanding students' learning dispositions has been a focus for research in education for many years. A range of alternative approaches to conceptualising and measuring this broad construct have been developed. Traditional psychometric measures aim to produce scales that satisfy the requirements for research; however, such measures have an additional useto provide formative feedback to the learner. In this article we reanalyse 15 years of data derived from the Effective Lifelong Learning Inventory. We explore patterns and relationships within its practical measures and generate a more robust, parsimonious measurement model, strengthening its research attributes and its practical value. We show how the constructs included in the model link to relevant research and how it serves to integrate a number of ideas that have hitherto been treated as separate. The new model suggests a view of learning that is an embodied and relational process through which we regulate the flow of energy and information over time in order to achieve a particular purpose. Learning dispositions reflect the ways in which we develop resilient agency in learning by regulating this flow of energy and information in order to engage with challenge, risk and uncertainty and to adapt and change positively.

Designing for student-facing learning analytics

“…Indeed, some of the participants in the trial were students who were simply more inquisitive, or hoping to "up their grades". At present the sample size of data collected from these trials is too small to make any strong claims, but future work will seek to establish whether student-facing LA is merely useful for piquing the curiosity of students who are already interested in understanding their digital profile, rather than helping students from many different backgrounds and learning dispositions (Deakin Crick, Huang, Ahmed Shafi, & Goldspink, 2015).…”

Towards Analytics for Wholistic School Improvement: Hierarchical Process Modelling and Evidence Visualization

“…Significant bodies of research underpin the need for schools to focus on wider outcomes, such as student experience (Blackwell, Trzesniewski, & Dweck, 2007;Dweck, 2000); learning how to learn and resilient agency (Claxton, 2008;Deakin Crick, Huang, Ahmed Shafi, & Goldspink, 2015); well-being and complex problem solving skills for successful living in the complex and inter-related world of the 21st century (McCombs & Miller, 2008;McCombs, Daniels, & Perry, 2008;Thomas & Seely Brown, 2009.…”

Learning Analytics for 21st Century Competencies

“…Complex systems perspectives are beginning to be applied to learning analytics to help make sense of the organizational dynamics of introducing analytics (Macfadyen, Dawson, Pardo, & Gasevic, 2014;Colvin, et al 2016). We also note important work in the Science and Technology Studies community on information and knowledge infrastructures (Bowker & Star, 1999;Edwards et al 2013), and the growing body of work on big data, ethics, and society (e.g., CBDES, http://bdes.datasociety.net/).…”