The Caledonian Academy is in discussions with the Caledonian Graduate Centre to plan a joint proposal for a Marie Curie training network during the 2009-10 academic year.
If successful the ‘Learn 2 Work’ programme would be led by Glasgow Caledonian University (Caledonian Academy, the Graduate Centre and two academic schools) in collaboration with around ten leading academic and industry partners from a range of countries across Europe (including the UK, Netherlands, Austria and Germany). The programme would provide a first-rate comprehensive training programme focused at improving the transition between university and the public and private sectors. This Interdisciplinary training network will integrate:
a research programme on work related learning - an area central to the university's ambitions in learning innovation; with
a comprehensive training programme for early career researchers.
Potential industry partners have already told us that view the network as a talent and innovation pipeline and are keen to provide engagement opportunities for members to learn about corporate matters relevant to learning innovation. This network would advance the the Caledonian Academy's strategy for stratgic change, since engagement of Caledonian Scholars and the university's academic staff involved in Doctoral level study could have a major impact on raising the level of learning innovation across the university.
How do universities prepare students for jobs that don’t yet exist? Harold Jarche recently presented this grand challenge to Education and Industry. This challenge is highly relevant to the development and growth of talent for industry and for the economy.
My colleagues Anoush Margaryan , Colin Milligan and I (Allison Littlejohn ) have been extending our ideas on how we might rise to this challenge. We have been developing the concept of Charting Collective Knowledge by carrying out empirical research and debating ideas with a number of colleagues, including Karen Smith and Isobel Falconer from the Caledonian Academy.
Society, the workplace and knowledge itself is rapidly changing, bringing about the emergence of new economic paradigms. Production is no longer in the hands of organisations. In the information age knowledge generation is an increasingly significant means of production with ownership in the hands of individuals.
It is difficult predict what new roles will emerge over the next decade, never mind by the end of the century. However, individuals will increasingly be expected to be in control of their own knowledge, work and learning.
Collective learning and self-regulated learning (SRL) gaining importance due to global societal transformations which create new demands for learning for work (Jakupec et al, 2000). Education and training has lagged behind socio-economic demands, increasing the gap between education and work (Reynolds et al, 2001). Around the globe governments are trying to ensure that employers have a role in future development of Higher Education and the importance of bringing closer the worlds of work and learning has been emphasised internationally (ETUC, 2006; EU, 2005; EU 2006; EU 2007).
Across Europe there have been initiatives to enhance this transition from education to work. through our “employability skills” or “”graduate attributes” agenda. There has been debate as to how these skills and attributes can be defined, taught and assessed. These debates often overlook one key point: that the development of expertise is not fixed in time, but requires ongoing refinement. Therefore standalone skills development cannot provide a solution. Development of an individual’s expertise involves a change in mindset with commitment to lifelong , self-regulated learning based around self efficacy and motivation. And its essential that individuals can develop skills in networking, and collaboration to help navigate the many transitions they will encounter throughout their career . In a new society where knowledge is generated openly and collaboratively, people require new skills and literacies enabling them to learn as an individual, drawing from collective intelligence. Development of these skills has to be integrated within approaches to learning.
The transition to work from education is problematic partly because although self-regulation is required in both contexts, the nature and goals of learning are very different. In higher education learning is a goal in itself, while in the workplace it is a means to and end and a by-product of carrying out work tasks. Consequently in the workplace the underlying motives, alignment of learning with work goals, assessment and forms of support are not familiar to new graduates. This poses difficulties for graduates as they try to orientate themselves in the workplace and enhance their self-regulating skills (Candy, 1991).
Fig 1: COLLECTIVE LEARNING
Immersing new employees in Collective learning may alieviate these problems. Collective learning processes makes use of collective knowledge and intelligence within and beyond the organisation. In drawing upon such collective knowledge, the individual develops a network of relationships with colleagues, connects with appropriate resources, and actively contributes knowledge and experiences. Through network interactions, knowledge and structures emerge from which the individual, in turn, benefits in his or her learning process. There has to be, therefore, a strong link between the tools supporting individual self-direction and the collective knowledge residing within groups, communities and networks within which collective learning processes emerge.
Collective learning draws from and contributes to collective knowledge. Collective learning is based upon a metaphor of the ‘wisdom of the crowds’ (Surowiecki, 2004), the idea that large groups of connected people are better able than an elite few to produce knowledge to solve problems and foster innovation.
In recent years knowledge networks, based on Web2.0 technologies, have extended groups learning to learning communities. However some learning environments still confine learning groups within ‘walled gardens’ protected by passwords. Collective learning extends beyond the limitations of networks capitalising on all knowledge distributed on the web - in humans, their actions, their networks and their interactions through machines.
In collective learning, individuals consume, connect and contribute knowledge. In consuming knowledge, these individuals need to be able to identify and source knowledge residing within the collective. To enable them to find relevant knowledge, the knowledge base must be transparent and accessible. Connecting knowledge requires that different resources and components (both those residing in systems and in individuals) can be combined efficiently. Contributing knowledge, through creating and sharing, is a vital condition for collective learning. Generating new skills, solutions, processes and feeding these back into the collective is an essential component.
These three components of collective learning represent a set of intertwined activities rather than discrete steps. They are not novel, having been emphasised in many modern pedagogic approaches (Dron, 2007; Siemens, 2006). However, what is missing is, firstly, an understanding of how these components should be linked in a way that supports individuals in accomplishing their work and learning goals in their contexts. Secondly, an understanding and solutions to creating synergies between learning and cognition in humans and machines that allow systems to identify learning requirements, intelligently monitor progress and exploit learners actions to help them learn better.
While navigating collective intelligence the learner needs guidance in how to make sense of the fragments of knowledge she will encounter. This allows her to tap into whatever is important. We propose the concept of ‘charting’ as a mechanism for this integration.
Charting
Charting is an approach (a collection of behaviours) that helps individuals navigate their learning and development goals. Other approaches currently exist such as Personal Development Planning, portfolios and so on. The problem with these approaches is that they are not dynamic and are individually driven rather than tapping into the collective.
Imagine if a new employee setting her learning goals could dynamically look up someone else’s plan and see how they reached their learning goals. Charting allows this. It is both individually focussed AND collaborative allowing individuals use other peoples’ knowledge while setting personal development plans.
Charting is a powerful concept that can support faster acquisition of knowledge, competences and skills thereby accelerating time to competence. Charting is a process whereby an individual determines and executes their individual learning paths. In doing this, individuals assess their current competence and set precise learning and developmental goals. Although this process is individually driven, it is not an individualistic learning process, since it takes place within the socio-cultural context of the workplace. In charting a learning path ideally suited to their needs, learners take advantage of collective knowledge, seeing how others with similar goals achieved them and their reflections on the process. The approach requires learners to both create and share knowledge, to allow others to build on their experience and to contribute to the collective knowledge. Charting also connects learners to others with similar goals and development needs, creating networks of learners who may support each other in learning and work. In doing this they should be able to use their own tools, networks, communities, and resources alongside those of the collective.
Charting can be supported by a ‘toolbox’ to support individuals consuming, connecting and contributing knowledge.
Fig2: charting collective knowledge
Imagine a new employee who sets her own goals and plans the sorts of activities required to achieve these goals. Imagine she is a process chemist tasked with finding a coolant substance for drilling in a new type of substrate. To achieve this goals she will set herself a real life task of testing coolants. To select the right sort of coolant and understand how to proceed she may make use of a variety of sources of information, knowledge and learning such as formal learning resources, stored information, recommended resources, case studies and so on (see Figure 2).
These resources are not always easy to find, since they are distributed. Also they may use language unfamiliar to the employee, leading to organisational and cultural issues. To help the employee overcome these issues she may tap into the expertise of others within her organisation who can guide her, for example her manager, team, peers and so on (Figure 2)
This goal is easiest if its part of the working culture of the organisation and if it is recognised and rewarded. The employee will consume knowledge from these resources and services. She may draw on technology tools to make recommendations as to which resources to select and how to make use of them, based on the actions of others. Connecting with others within and outside the organisation can help her make best use of what’s available to carry out her work and learning tasks and achieve her goal of finding an optimal coolant for drilling. In carrying out these tasks she will, in turn, contribute back to all of these resources and services. She will carry out her work and learning tasks alongside others within her peer group who are setting their own learning and development goals and activities. Not only will this improve her learning productivity, but it will enrich the collective and she will draw upon the knowledge and actions of others as she does so. Consequently all individuals will contribute knowledge, implicitly and explicitly, that can be used by the collective as they move towards achieving their goals. Charting occurs at a level above connection, consumption and contribution. The key to charting is the ability of the employee to define her learning goals.
Goal setting
To maximise the speed with which this employee will learn, the ideal situation is where everything this individual does in her daily working life will contribute towards her learning. In other words, an employee carrying out a job will learn through her normal work tasks. Learning is aligned with her work tasks, knowledge creation and knowledge sharing. This direct route to achieving leaning goals allows for maximum learning productivity.
In reality not everything an employee or learner does will directly contribute to achieving her learning goals, particularly in workplace settings where learning goals are loosely defined and not as linear as in formal education. Learning goals may alter over time. An employee, whether expert or novice, may not be able to predict from the outset where her emerging goals will lead her.
Charting may help the learner relate where she is to where she wants to be and will help her find how to get there by recommending existing trails used by previous learners following a similar route. Charting provides the learner opportunity to dynamically interact with her goals and personal development. Charting allows the learner to make use of people and resources to fine tune her choices at any point. We cannot exactly define charting prior to looking at existing behaviours. And that is what we are currently doing in partnership with Shell.
The Caledonian Academy is offering a 3-year studentship to carry out research leading to a PhD investigating the role of social networks in enhancing learners’ transition from education to the workplace and supporting knowledge work. This PhD studentship is funded, and will be supervised by the Caledonian Academy. The studentship offers a unique opportunity to work with an internationally-renowned research team which has strong links with leading research centres and global corporations.
Research project Although employers demand, and universities aspire to produce, independent learners, the gap between education and work has widened in recent years. This project is based on the premise that understanding the ways individuals operate as independent or self-regulated learners in educational settings and in the workplace is an important component of enhancing transition. Most previous work on these issues has focused on individual learning activities, ignoring the role of the collective in supporting the individual, co-constructing knowledge, and influencing goals and motivations. This project will redress the balance, investigating the networks that learners develop during their study in university, the impact these have, and how they are maintained and extended when new graduates enter the workplace, the resources learners draw on (human and physical, face-to face and online), and the reasons why they choose these resources.
The fellowship is open to candidates from EU countries and the closing date for applications is 17 April 2009.
Further details of the studentship including educational requirements and instructions for applicants are available as a PDF document: learningthroughnetworking.pdf
This week we started a new research study on 'Learning from Incidents' in partnership with Shell, ConocoPhilips and BP. The aim of our study is to develop new approaches to learning that will reduce incidents affecting health and safety in the workplace. This industry-academia partnership involves a 3 year PhD Fellowship funded by the UK Energy Institute.
Allison Littlejohn and Anoush Margaryan of the Caledonian Academy along with John Holmes, Shell Exploration and Production Health and Safety Executive Systems and Planning Leader, based in Houston, Texas and Peter Jefferies from ConocoPhillips Humber Refinery will co-supervise the study. Dane Lukic has joined our team as a PhD Fellow. Dane is originally from Bosnia-Herzegovina.
Learning from Incidents aims to help the industrial partners embed new approaches to learning and reducing critical incidents within the workplace. Adopting a culture of continuous learning employees at all levels will become more self-reliant, scanning their environment, looking for improvements, sharing new ideas and applying safe practices. The study is based on a ‘Change Lab’ methodology which supports participatory redesign of work practices. Researchers will collaborate with workers and managers in Shell, ConnocoPhillips and BP to surface and critically analyze hazardous practices and jointly develop solutions to transform the work practices.
Anoush has been reanalysing the data to find out the nature and extent of students’ use of digital technologies for formal and informal learning and socialisation. We have also been focusing on lecturers’ perceptions of the educational value of these tools and their views on the barriers and enablers for using technologies to support learning.
Our findings suggest that, compared with older students (so called Digital Immigrants) younger students do, indeed, make more recreational use of social technologies such as media sharing tools and social networking sites. However, their use of and familiarity of collaborative knowledge creation tools, virtual worlds, personal web publishing, and other emergent social technologies for learning is fairly limited.
The study has not found evidence to support the claims in relation to students adopting radically different patterns of knowledge creation and sharing. In fact students’ attitudes to learning may be influenced by the teaching approaches adopted by their lecturers.
Far from demanding lecturers change their practice, students appear to conform to fairly traditional pedagogies, albeit with minor uses of technology tools that deliver content. These outcomes suggest that although the calls for radical transformations in educational approaches may be legitimate it would be misleading to ground the arguments for such change solely in students’ shifting expectations and patterns of learning and technology use.
In discussing self-regulated learning with colleagues – focusing on Boekaert’s 2002 paper - I incautiously remarked that the teacher needed somehow to bring the students’ goals in line with academic goals – and was immediately pounced upon for being old-fashioned and teacher-centric in my views. This incident highlights for me one of the fundamental problems with self-regulated learning and the concomitant idea that by developing students as self-regulated learners we improve their employability. The problem is that one can take a very student-centred approach to learning, and be entirely symmetrical in ones view of student-teacher interactions (indeed, this is my preference), and may have highly self-regulated students. However, the definition of “learning” is still asymmetrically in the hands of the institution, as interpreted by the teacher or assessor, just as the definition of “employable” is ultimately in the hands of the employers. Even if student-teacher interactions are symmetric, the contextual definition of learning is not. Highly self-regulated students may have goals that are very different from those the institution or employer would wish them to have - in this case they will not be recognised as self-regulated learners and may appear totally unemployable. Equally, they may adopt the goals of an HE institution and count as very competent self-regulated learners, but never adopt the goals of an employer and remain unemployable (or vice versa). Because of this contextual asymmetry, if the hallmark of a successful teacher is that their students become self-regulated learners, then it still seems to me that this is probably due to something the teacher has done to encourage (somehow) the student to adopt the institution’s or teacher’s goals. A fundamental issue, then, in developing self-regulated learners or employable graduates is the study of how or why students adopt an institution or employer’s goals as their own.
Yesterday we hosted a short event here at the Caledonian Academy centred around our action research partnership with Shell International. Mark Batho, Chief Executive of SFC spoke on the need for universities to supply graduates with appropriate skills, and Dr Sebastian Graeb-Konneker of Shell provided some personal thoughts on making the transition from Academia to the eneterprise. For our presentation, Allison, Anoush and I provided an overview of our work with Shell centred on the ideas of collective learning and charting which have been developed and explored as part of the project.
Our slides from the event are available on slideshare and embedded below:
