The Learning Journey Platform

The goal of the Learning Journey Platform is to make Learning Power improvement accessible to anyone with a smart device.  Helping everyone to succeed not only in their study, but also in their work and in the community.

From Classroom to Boardroom – Learning Power drives success

Developed through 18 years of academic research, the Learning Power platform and previous versions have been used over 120,000 times to help individuals and teams improve their capacity to learn.

Learning Power Home

With the ability to support multiple languages and tones of voice tailored to each audience, it is a unique capability that enables continuous Learning Power improvement throughout the journey of a learner – from school, to college, to university and into work.

It’s also a powerful tool for supporting community engagement – addressing shared problems that matter.

With an obvious home in Education, the Learning Journey Platform is increasingly being used by Business around the world to improve performance by increasing the Learning Power of individuals, teams and organisations, enabling them to transform, adapt and succeed.

Its a new and unique opportunity to build sustainable Learning Power improvement into individual and organisational learning.

The Platform’s features and benefits

It is more than just a diagnostic tool – it supports the entire Learning Power improvement cycle, from purpose to performance.

  • It is ‘always on’ – the platform is constantly available to provide new and rapid feedback, not just a one-off assessment
  • It is accessible and easy to use
  • It supports and informs coaches and leaders as well as their teams
  • It generates a rich and growing data set to drive collaborative research, development and continuous improvement

Without purpose, learning is a journey without a destination

The first stage in any learning journey is understanding why you are attempting something – establishing purpose.  The platform makes this very simple, guiding you through a series of questions that tease out the purpose.

Discovering your personal Learning Power profile

Next, the platform takes you through the Learning Power profile, answering simple questions about how you think, feel and behave while learning. Based on these answers, a personalised Learning Power profile is generated, helping you to understand your capacity to learn based on eight dimensions of learning.

Learning Power Results

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Improving your Learning Power

Being able to improve your Learning Power is at the heart of the platform.  By identifying which learning power dimensions to improve, you give a new shape to your profile, creating a visual target for your improvement plan.

Change my profileThe platform makes this easy by enabling you to drag and stretch your selected dimension scores on the spider diagram of your Learning Power profile and by prompting and recording the improvement strategies you create which enable you to achieve your targets.

Doing something about it…

The next step is also simple, but often overlooked – it’s about putting a plan into action and doing something differently, to practice and improve your Learning Power.  We call this Doing The Job.  It is when Learning Power is used in action to build new knowledge, achieve goals and create new value.

Lending a helping hand

To help you on your journey, we have created your own ‘buddy’ that will offer personalised help along the way. 

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Offering helpful hints and tips, this will make sure you get the most out of your learning journey.

Tracking progress

The last step in any learning journey is to measure the progress made against your learning objectives.

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The platform makes it easy to retrieve and compare previous learning power profiles and to track your progress over time.

Unique access to learning data

The platform also provides access to the underlying data to enable valuable analytical insights, for coaches and leaders, of the individual and group feedback.

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Access to this level of learner data is ground-breaking as it allows for integration with wider data sets for further analytical insight and to drive Research and Development opportunities.

A Digital Learning Infrastructure for self-directed learning

Why does this matter?

Complex problem solving, critical thinking and creativity are the three most important capabilities for thriving in the Fourth Industrial Revolution.  These are not traditionally developed through legacy learning and development systems (human or digital)because they require real-world, purposeful problems and contexts, the ability to work across silos, new measurement models and courageous leadership. Learning design for teachers is about creating the conditions where students can take responsibility for their own learning by invoking their own passion and purpose and the agency to pursue these through a learning journey in contexts where the outcome is not known in advance

What are we measuring?

The most important unit of change is the story and identity of the learner – not the teacher, the curriculum or the measurement model. Legacy systems tend to privilege the content of the curriculum, a reductionist measurement model and the teacher as agent of change.  The challenge for learning analytics is to build a digital infrastructure based on a data architecture which provides a ‘single view of the learner’, where data belongs to the learner and can be used, one student at a time, across transitions, and in real-time, for better decision-making as they navigate their way through complex problems to solutions that matter to them.  This is sometimes described as a call to move towards Education 3.0 – a challenging worldview shift from a top down, individualist and dualistic worldview (Education 1.0) towards an integral, participatory and wholistic one.   For a discussion about these ideas see the first Handbook for Learning Analytics and a chapter called Layers, Loops and Processes.

What this Post is About

I want to focus on the challenges and opportunities of building such a Digital Learning Infrastructure and will use examples from the new Learning Emergence Learning Journey Platform.  The first release of the platform is live with a group of schools in the UK and  with another group of schools in the Hunter, NSW, sponsored by Hunter Water Corporation. Hunter Water are using the same Learning Journey Platform as a vehicle for cultural transformation as they move into the uncertainty and challenges of infrastructure resilience and sustainability for the future of the region.

The Learning Journey Platform

The purpose of the Learning Journey Platform is to enhance self-directed learning capabilities, and thus the resilient agency, of students, teachers and leaders and schools across the world. It provides scaffolding support for people in authentic enquiry learning journeys which contribute measurably to data-informed local solutions that matter and empower self-directed, resilient learners. ‘Learning Power’ is a term which describes this approach. Resilient people are a pre-requisite for resilient and sustainable practices at all levels of society. See this link for an introduction.

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 TESAteacher 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 learningjourneys 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.

What Next

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.

 

 

 

 

 

 

Learning Power: new research identifies Mindful Agency as central to resilience

For learning in the complex world of risk,  uncertainty and  challenge, what matters is being able to identify, select, collect, collate, curate and collaboratively re-construct information to suit a particular purpose. This is why there has been a sustained and growing interest in learning dispositions and the personal qualities people, teams and communties need to flourish. As Edgar Morin says:

edgar morinWe need a kind of thinking that reconnects that which is disjointed and compartmentalized, that respects diversity as it recognizes unity, and that tries to discern interdependencies. We need a radical thinking (which gets to the root of problems), a multidimensional thinking, and an organizational or systemic thinking

Ruth Deakin Crick 2015After fifteen years of experience in the research and practical application of learning power using a survey tool called the Effective Lifelong Learning Inventory (ELLI), Professor Crick, one of the originators, led the research team in a thorough review and reanalysis of the data.  Supported by the Learning Emergence Network of international researchers, the results are now published for the first time in the British Journal of Educational Studies:

Ruth Deakin Crick, Shaofu Huang, Adeela Ahmed Shafi & Chris Goldspink (2015): Developing Resilient Agency in Learning: The Internal Structure of Learning Power. British Journal of Educational Studies. DOI: 10.1080/00071005.2015.1006574. Open Access Eprint:  http://dx.doi.org/10.1080/00071005.2015.1006574

Interestingly, the support for this re-analysis came from the Systems Engineers in the Engeering Faculty at the University of Bristol  as part of the International Centre for Infrastructure Futures, rather than ELLI’s original home in the Graduate School of Education….where Crick, Broadfoot and Claxton began in 2000.  Perhaps Morin would have something to say about this — we think so!

The new self assessment tool, called the Crick Learning for Resilient Agency Profile (CLARA) identifies Mindful Agency as a key learning power dimension — which predicts the set of active dimensions: Creativity, Curiosity, Sense-Making and Hope & Optimism.   Two distinct Relationship dimensions measure Belonging and Collaboration.  Finally, an Orientation to Learning indicator measures a person’s degree of Openness to change — in contrast to either fragile dependency or rigid persistence.

Internal Structure of LP with simplied view 19 August

The new measurement model represented by CLARA resulted from a detailed  exploration of the patterns, relationships  and interdependencies within the key constructs through structural equation modelling (diagrammatic summary above).  It is a more robust, parsimonious measurement model, with strengthened research attributes and greater practical value. The research  demonstrates how the constructs included in the model link to the wider body of research, and how it serves to integrate a number of ideas that have hitherto been treated as separate. For more details from a user perspective see  Introducing CLARA.

The CLARA model suggests a view of learning that, after Siegel 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. They enable us to engage mindfully with challenge, risk and uncertainty and to adapt and change in a way which is positively alinged with our purpose.

Resilient Agency is our capacity to move iteratively between purpose and performance, utilising our learning power and generating and re-structuring knowledge to serve our purpose.

Learning JourneyLearning, from this viewpoint, is a journey which moves between purpose and performance – to put it another way, without having purpose we’re not really going to learn in a context of complexity and information overload. To learn, when the outcome is not known in advance (which is most real world learning) requires that we are able to navigate learning as a journey, utilising our Mindful Agency, restructuring information to achieve the outcome we need.

BlueThe Learning Emergence Network has teamed up with eXplorance Blue, one of the world’s leading survey providers based in Montreal, to create the SOLA platform (Surveys for Open Learning Analytics) which can host CLARA and other assessment tools, and importantly, provide rapid feedback to users for improvement purposes.

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Visual feedback to the learner from CLARA

The rapid analytic feedback to users who complete the questionnaire is returned in the form of a spider diagrame which forms a framework for a coaching conversation which can move between learning identity and purpose and the formulation of strategies for change.  The new assessment tool is a focus for research and development around the world. Crick and Buckingham Shum are now based in the pioneering Connected Intelligence Centre and the School of Education at the University of Technology Sydney, where CLARA forms part of a research programme into dispositional learning analytics — alongside other learning analytics approaches designed to make visible – to learners and educators – the dynamics of lifelong learning qualities.

by-nc-nd (1)CLARA, and the knowledge and know-how in the research paper, have been made available for research and development under the terms of a Creative Commons Attribution-NonCommercial-NoDerivatives License. This permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

We welcome all contributions to the ongoing research and development of this work which has applications in education, industry and community.  We have translated CLARA into Chinese, Russian and Spanish. For more details and opportunities for collaborative research and development please contact info@learningemergence.com

Learning to Learn – International Perspectives

Learning to learn is crucial for success in our complex, unpredictable and data-drenched world.

L2LfrontcoverThis new book from members of the Learning Emergence Network explores learning to learn from theory and practice around the world.  See our people pages for many of the authors. 

Learning to learn is both a process and an outcome of formal education, along with other trans-disciplinary and life-wide competences. It goes deep into pedagogy and practice and is influenced by culture and context. As an outcome, it is a competence we aspire to measure and celebrate.

Learning how to learn is a crucial competence for human flourishing in 21st century conditions of risk and uncertainty.  It is one of eight key competencies identified by the European Union as a key goal within the Lisbon and the 2020 strategies (European Council 2006). The European Union maintains a keen interest in this topic as demonstrated by the European network of policy makers and several working groups on key competencies, including the creation of the European Network on Learning to Learn (Hoskins & Fredriksson, 2008). Internationally, learning to learn is emerging as a focus for school improvement and as a foundation for lifelong and lifewide learning. UNESCO includes approaches to learning as a key domain which should be an entitlement for all children, and one which needs to be assessed.

Language matters.

There is a real need for serious debate about the term ‘learning to learn’ which is frequently used in different ways and in different contexts without clear definition.  Often it is used within a conceptually narrow framework, limited to “measurable” study strategies and learning styles (OECD 2009) for which there is little evidence of success. There is an urgent need for a research validated foundation for learning to learn and what constitutes it.

Practitioners, university lecturers, teachers and schools around the world are interested in their students becoming able to take responsibility for their own learning and achievement – and for this they need to learn how to learn.  Existing funds of knowledge are all ‘out there on the internet’ and what matters is how individuals and teams make sense out of and utilise the mass of information which bombards them every day. Dialogue between research and practice is crucial to underpin this movement, generating a discipline of research-informed practice which frames and informs both commercial and policy interests. In the absence of a ‘pensee unique’  the global community of scholarship in education provides an important voice which should make a healthy, collaborative contribution to the formation of policy and practice.

Assessment of competence in learning to learn is a critically important policy ideal – one which the European Union embraced and embarked upon with Learning to Learn working group. After some serious effort we came to the conclusion that there are so many different approaches to learning to learn from across the EU, that it was impossible in 2007 to arrive at a consensus in its measurement. Before we can ever effectively assess something we need to know exactly what it is we are measuring – as a matter of professional ethics. We also need to know what measurement models are most suitable and what is the purpose of the assessment before we develop our assessment technologies. This book was conceived by people who participated in that EU project and, we hope, in an important way it keeps the dialogue alive.

Complexity and Learning to Learn

Learning to learn is a complex process rather than either a simple or even a complicated one.  Demetriou’s chapter explores an architecture of mind that incorporates four inter-related systems all of which may be relevant to learning to learn. Each contributor proposes a complex mix of processes that coalesce into learning to learn – including affective, cognitive and dispositional factors. All agree that learning to learn is about the promotion of self-directed learning, the cultivation of intrinsic motivation for learning and the development of intentional agency on the part of the learner.  All agree that contextual factors – such as pedagogy, assessment regimes, quality of relationships and socio-cultural factors – together interact and influence the ability of an individual to learn how to learn and to become an agent in their own learning journey. Learning to learn is messy and complex.

The implications of this complexity are enormous. edgar morinAs Edgar Morin argues (and Jung before him), Western thought has been dominated by the principles of disjunction, reduction and abstraction. Engaging with learning to learn as a complex process requires a paradigm of distinction-conjunction, so that we can distinguish without disjoining and associate without identifying or reducing.  In short we need to develop new and more holistic ways of understanding, facilitating and enabling learning to learn in our education communities, so that we can hold in tension the inner personal aspects of agency, purpose and desire and dispositions and the more measurable external and public manifestations of learning and performance and collaboration with others in learning to learn. We need measurement models that can account for quality of trust as a core resource, and story as a vehicle for agency as well as the more traditional and familiar measures of performance and problem solving.

Becoming self-organising agents in our own lives

If learning to learn is about human beings becoming self-organising agents of their own lives, as our contributors suggest, then it is clear that ‘top down’, transmission oriented approaches to learning, teaching and school improvement are no longer enough. The challenge is how to create the conditions in which individual students are able to take responsibility for their own learning over time.  By definition, this cannot be done for them. It has to be by invitation, allowing learning to learn to emerge and fuel agency and purpose.

The establishment of the framework for international comparison of educational achievement provided by the OECD through the Program for International Student Assessment (PISA) and the means for regularly compiling the data is a considerable achievement. It has provided an evidence base for Governments to inform domestic educational policy and against which to allocate priorities. What this data set is less effective at revealing are the reasons behind international and regional difference: we still understand too little about what drives these broad numbers. Furthermore the numbers continue to reveal deep, intractable challenges in education such as embedded disadvantage linked to geography, economics and ethnicity.

There is a pressing need to assemble an internationally comparable set of data which can better inform our understanding of factors such as learning how to learn and how this varies within and between different contexts. The academic and theoretical work that has been undertaken on these issues to date, while rich and deep, has focused on aspects of the problem, often failing to cross disciplinary boundaries. The real world challenge of educational improvement, meanwhile, is relentlessly trans-disciplinary, involving a complex interplay between social, institutional and individual factors. It presents a challenge both to theory and practice. The PISA data by comparison achieves comparability through the use of widely available proxy indicators but lacks the depth and resolution needed to provide an understanding of the mechanisms driving the patterns it surfaces.

Valuing Difference

What is also clear from this volume is the value of different cultures in the debate about learning to learn. Two chapters are written explicitly from an Eastern perspective  – demonstrating how Confucian philosophy can enrich our understanding of learning to learn and challenging some deeply held Western assumptions.  We have contributions from Australia, New Zealand, Finland, UK, Spain, Austria, China, Italy and the USA and uniquely, a set of case studies from learning to learn projects in remote Indigenous communities where the cultural differences are enormous. This  is a ‘brolga’ a community  metaphor for creativity for children in Daly River School, in Northern Territory.
Creativity

However comprehensive, this volume does not address a number of research and practice themes or leaves unanswered questions for further research. Among these, perhaps the most relevant is the road towards the assessment of learning to learn which is a daunting endeavour – although it provides a foundation for this through its contribution in exploring what it is that should be assessed in learning to learn and why. Other open questions concern the deployment of learning to learn in school improvement; in the training of trainers, educators and educational leaders; in personal development and empowerment. The connection of learning to learn with other key competencies, such as active citizenship and entrepreneurship, also requires further study.

This book draws on a rich, global tradition of research and practice. It is written by researchers and  practitioners who care deeply about education and about learning how to learn in particular. Our purpose is to generate debate, to link learning communities and to make a contribution to the ways in which societies worldwide are seeking to re-imagine their education systems. Our hope is that learning to learn will soon find a consistent place in educational policies worldwide.

Hampshire Teaching Schools Alliance: Becoming Research Teachers focused on improving Deep Learning Across Transitions

Screen Shot 2013-10-06 at 18.40.50The Hampshire Teaching Schools Alliance has formed a Networked Improvement Community with structured social arrangements which joins academic research, clinical practice and commercial expertise in sustained programmes of Design Educational Engineering and Development (Bryk et al 2010).  This is an approach to improvement which is being developed in education by the Carnegie Foundation for the Advancement of Teacher Education

Pioneer Teaching School AllianceIt  offers a productive synthesis across the research-practice divide. It aims to meld the conceptual strength and methodological norms associated with traditional research  with the contextual specificity, deep clinical insight and practical orientation characteristic of action research.

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Participants in a Networked Improvement Community endorse shared, precise, measureable targets which achieve a shared purpose.  They address shared,complex problems and participate in whole systems designing processes aimed at clarifying the problem/challenge/solution space. On the basis of rich data from this process they design interventions which may lead to improvement.  These interventions are rapidly prototyped, and  participants agree to use what is learned from working toward meeting the targets, to setting new targets aimed at ever more ambitious goals. In this regard, shared measureable targets help a community stay focused on its core purpose, from the community’s perspective. They catalyze discussions among participants as to why we should attend to this rather than that. They demand about what is likely to afford more immediate progress.  They introduce discipline in priority setting as it interacts with the individualistic rhetoric of “I am interested in…”

The problem identified in the HTSA NIC is the problem of student progress in learning and achievement across key transitions.

Our shared understanding of the problem we are seeking to address is that we lack a common approach to teaching, learning and assessment across transitions. Specifically we tend to:nsitions in education. Throughout 2012/13 academic year, as well as setting in place the social arrangements, they have engaged in a systems analysis of the problem. This is presented in the first diagram below, Problem Solution Space. From here the potential solutions were identified in the second diagram: Driver Diagram.

  • create dependent learners
  • lack a shared language and repertoire of learning routines & practices
  • lack pro-active and shared rich student academic & learning assessment data
  • lack trust between teachers in different contexts
  • are influenced by anxiety about performance criteria

Our shared hypothesis:

If we focus on a common approach to developing self-directed learning and knowledge construction for students across the transitions then we will enable students to maintain progress in learning and performance because they will carry this competence into their new context, which will have key pedagogical characteristics in common with the one they have left.

Our shared purpose is: 

To design and implement approaches to teaching and learning which facilitate deep & self-directed learning in students which they carry across the transition, which is recognised and supported in the new context, and which leads to sustained progress and improved attainment.

In order to do this, our initial focus is on teacher professional learning – how we work together, harness our collective intelligence and learn across the Alliance. We work creatively within a common, disciplined framework with shared design principles.

Design Principles

(Key practices which are (i) disciplined and pervasive characteristics of our shared approach to pedagogy, (ii) evidence based and (iii) communicated to our communities in many different ways)

Developing Deep & Self-Directed Learning through

  • a shared language for learning and knowledge construction
  • a common approach to teaching as learning design
  • a common set of assessment strategies – using rich data
  • a common set of values which pervade the learning environments
  • authentic pedagogy for deep engagement

Project Methodology

A shared question  & a context specific response

#Each Project will make a unique contribution to addressing the question of what type of pedagogical practices  contribute to the development of deep and self-directed learning across the transition.

Who will we work with?

Each project team works collaboratively with a year group before and after the transition (for example year 5 and year 7)  using the rapid prototype methodology based on the Plan Do Study Act cycle.

A rapid prototype is a short, small project (24 weeks) designed and implemented by the teacher/researchers following the Plan, Do, Study, Act cycle. It addresses all or some of the project’s shared design principles but in a way which is appropriate for that particular context. It is evaluated locally – and using disciplined metrics which are agreed by the whole group. Eventually the project will harvest the learning from all the prototypes, which can be scaled up across the communities.

There will be two prototypes, one between December and March and the second between April and June. The second one is improved in the light of the evaluation of the first one.  Each project team is responsible for designing and implementing their own research project, including data collection and analysis methods and presentation of findings.  Two project workshops will provide a collaborative learning event for each cycle where each group presents their findings – what works, and key concepts.  These will be synthesised & shared for improvements in the next prototypes.

Each prototype will contribute its learning to the whole via the Evidence Hub in the form of stories of significant change, videos, etc.  Each project will have an academic critical friend from a local University. Each project will adopt the Ten Up methodology across the cohort.  From the target year group, focus on 10 students to study in depth as case studies for professional learning, whilst the whole year group benefits from the intervention.  These students could also provide case studies for students in the partner HEIs who need data and can add value.

Overall Disciplined Evaluation Framework

Each project will commit to working with the shared, disciplined evaluation framework for the whole project.  As well as contributing equally to the whole project systems designing and solutions space, they will agreed to collect and provide data which will be used to evaluate the project as a whole, over the four year lifecyle.  This whole project data is designed to measure the target outcome which is ‘student self-directed learners’ and the relationship between this outcome measure and student progress across transitions. It will also enable the project to idenfity a ‘control group’ in another teaching schools alliance elsewhere in the UK if appropriate, which is not addressing the problem of transitions in this way.

Learning to Achieve  is a handbook for teachers who want to understand more about implementing learning power.