i Deakin Crick, R., Huang, S., Ahmed Shafi, A. & Goldspink, C. 2015, ‘Developing Resilient Agency in Learning: The Internal Structure of Learning Power’, British Journal of Educational Studies, vol. 63, no. 2, pp. 121-60.
Loops – feedback and feedforward
Rapid feedback of meaningful data is key to enhancing self-directed learning. The Learning Journey Platform hosts the CLARA learning power assessment tool, the TESA teacher development tool for pedagogy which supports deep student engagement and Angela Duckworth’s GRIT survey. Feedback to the user is immediate and provides a framework for reflection – ‘backwards’ towards identity and purpose and ‘forwards’ to a particular purposeful outcome.
The Learning Journey Platform aggregates anonymised data in real time for coaches, teachers and leaders to interrogate in different ways. This capability is possible because of the underlying data architecture which allows for a ‘single view of the learner’. The data belongs to the learner and they can take their learning journeys with them from school to school and on to University and into the work place.
Processes – the learning journey
A key design principle underpinning the Learning Journey Platform is that learning is a journey that begins with a purpose and moves towards an outcome or ‘performance’ of some sort. When a student defines and owns their own purpose – the why – they are at the beginning of resilient agency. They need to use their learning dispositions – their learning power – to understand themselves as learners and to figure out how to move towards their purpose. The what is the data, information, experience and new knowledge they need to identify, collect, curate and re-construct in order to achieve their purpose. This is a familiar enquiry cycle for most educators – the key difference here is the emphasis on purpose and agency and self-directed navigation. It’s also a process that is core to improvement science approaches.
The learning journey metaphor is simple and yet profound in terms of mind-set shifts. A person leads a journey, you can be on your own or with others, there’s a terrain, a map if you’re lucky, challenges, diversions and a destination. Journeys have endings and beginnings and way-points, and come in all shapes and sizes.
The Learning Journey Platform builds on best practice in data architecture from FinTech in customer journeys and uses AI to support the individual learner in navigating their learning. Whereas in the commercial world the focus is on the ‘next best action’, in the world of learning the focus is on the ‘next best offer’. Dialogue and discourse are at the heart of learning.
Layers – students, teachers, leaders, system leaders
Schools are complex living systems which are multi-layered. We know how important teacher professional learning is – you can’t give what you haven’t got. Moving towards education 3.0 means to be part of a worldview shift which is happening around us because of the challenges of life in the 21C. A worldview shift of this type is uncomfortable and challenging. It’s best encountered and managed through deep professional learning – for leaders and teachers. The Learning Journey Platform captures the data, analyses it and returns aggregated anonymised data as feedback to teachers and leaders for more focused interventions and better decision making. Personal data is only viewed by another person with explicit permission: it belongs to the Learner.
The focus for the next stage of the Learning Journey Platform is on enhancing the use of AI to support purposeful conversations – enhancing, not replacing, the face to face relationships of trust, affirmation and challenge that are at the heart of learning. ‘Buddy’ already asks questions and ‘calls time’ for reflection at key junctures in each journey and he’ll get cleverer as time goes by. The second focus is on developing support and scaffolding for a whole authentic enquiry project.
The Learning Journey Platform is available for use by schools and HE in this phase of development. Its capability to collect and integrate data around rapid cycles of enquiry make it an ideal candidate to support professional learning and improvement science approaches to educational transformation. Its partnership with Declara – social learning and knowledge curation – mean that through the INSIGHTS tab capability users can access ‘knowledge pathways’ – units of relevant learning material which sit within Declara. The potential for scaling up professional learning across geographies and time is significant.
This sort of education innovation requires new business models that allow for collaboration, innovation and evolution. The Learning Emergence Partnership is developing a wholistic approach where the same learning design principles are used in industry for cultural transformation both in terms of employees and different types of users and customers. In between education and industry there is ‘community engagement’ and ‘vocational education’. Our vision is to make this work accessible for all schools, working with both industry and philanthropy. Learning Emergence has an asset locked Foundation to ensure this.
i – https://www.weforum.org/agenda/2017/09/skills-children-need-work-future-play-lego
ii – Crick, R. 2017, ‘Learning Analytics: Layers, Loops and Processes in a Virtual Learning Infrastructure’ , in G. Siemens & C. Lang (eds), Handbook of Learning Analytics & Educational Data Mining 1st edn, Society of Learning Analytics Research, SOLAR, pp. 291-307
iii – Deakin Crick, R., Huang, S., Ahmed Shafi, A. & Goldspink, C. 2015, ‘Developing Resilient Agency in Learning: The Internal Structure of Learning Power’, British Journal of Educational Studies, vol. 63, no. 2, pp. 121-60.