Archive for the ‘e-learning 2.0’ Category

Workplace Learning Analytics for Facilitation in European Public Employment Services

February 10th, 2016 by Graham Attwell

Along with colleagues from the EmployID project, I’ve submitted  a paper f to the workshop on Learning Analytics for Workplace and Professional Learning (LA for Work) at Learning Analytics and Knowledge Conference (LAK 2016) in April. Below is the text of teh paper (NB If you are interested, the orgnaisers are still accepting submissions for the workshop.

ABSTRACT

In this paper, we examine issues in introducing Learning Analytics (LA) in the workplace. We describe the aims of the European EmployID research project which aims to use

Image: Educause

technology to facilitate identity transformation and continuing professional development in European Public Employment Services. We describe the pedagogic approach adopted by the project based on social learning in practice, and relate this to the concept of Social Learning Analytics. We outline a series of research questions the project is seeking to explore and explain how these research questions are driving the development of tools for collecting social LA data. At the same time as providing research data, these tools have been developed to provide feedback to participants on their workplace learning.

1. LEARNING ANALYTICS AND WORK BASED LEARNING

Learning Analytics (LA) has been defined as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.” [1]. It can assist in informing decisions in education education system, promote personalized learning and enable adaptive pedagogies and practices [2].

However, whilst there has been considerable research and development in LA in the formal school and higher education sectors, much less attention has been paid to the potential of LA for understanding and improving learning in the workplace. There are a number of possible reasons for this.

Universities and schools have tended to harvest existing data drawn from Virtual Learning Environments (VLEs) and to analyse that data to both predict individual performance and undertake interventions which can for instance reduce drop-out rates. The use of VLEs in the workplace is limited and “collecting traces that learners leave behind” [3] may fail to take cognizance of the multiple modes of formal and informal learning in the workplace and the importance of key indicators such as collaboration. Once more key areas such as collaboration tend to be omitted and in focusing on VLEs, a failure to include all the different modes of learning. Ferguson [4]) says that in LA implementation in formal education: “LA is aligned with clear aims and there are agreed proxies for learning.” Critically, much workplace learning is informal with little agreement of proxies for learning. While Learning Analytics in educational settings very often follow a particular pedagogical design, workplace learning is much more driven by demands of work tasks or intrinsic interests of the learner, by self-directed exploration and social exchange that is tightly connected to processes and the places of work [5].  Learning interactions at the workplace are to a large extent informal and practice based and not embedded into a specific and measurable pedagogical scenario.

Pardo and Siemens [6] point out that “LA is a moral practice and needs to focus on understanding instead of measuring.” In this understanding “learners are central agents and collaborators, learner identity and performance are dynamic variables, learning success and performance is complex and multidimensional, data collection and processing needs to be done with total transparency.” This poses particular issues within the workplace with complex social and work structures, hierarchies and power relations.

Despite these difficulties workplace learners can potentially benefit from being exposed to their own and other’s learning processes and outcomes as this potentially allows for better awareness and tracing of learning, sharing experiences, and scaling informal learning practices [5]. LA can, for instance, allow trainers and L & D professionals to assess the usefulness of learning materials, increase their understanding of the workplace learning environment in order to improve the learning environment and to intervene to advise and assist learners. Perhaps more importantly,  it can assist learners in monitoring and understanding their own activities and interactions and participation in individual and collaborative learning processes and help them in reflecting on their learning.

There have been a number of early attempts to utilise LA in the workplace. Maarten de Laat [7] has developed a system based on Social Network Analysis to show patterns of learning and the impact of informal learning in Communities of Practice for Continuing Professional Development for teachers.

There is a growing interest in the use of MOOCs for professional development and workplace learning. Most (if not all) of the major MOOC platforms have some form of Learning Analytics built in providing both feedback to MOOC designers and to learners about their progress. Given that MOOCs are relatively new and are still rapidly evolving, MOOC developers are keen to use LA as a means of improving MOOC programmes.  Research and development approaches into linking Learning Design with Learning Analytics for developing MOOCs undertaken by Conole [8] and Ferguson [9] amongst others have drawn attention to the importance of pedagogy for LA.

Similarly, there are a number of research and development projects around recommender systems and adaptive learning environments. LA is seen as having strong relations to recommender systems [10], adaptive learning environments and intelligent tutoring systems [11]), and the goals of these research areas. Apart from the idea of using LA for automated customisation and adaptation, feeding back LA results to learners and teachers to foster reflection on learning can support self-regulated learning [12]. In the workplace sphere LA could be used to support the reflective practice of both trainers and learners “taking into account aspects like sentiment, affect, or motivation in LA, for example by exploiting novel multimodal approaches may provide a deeper understanding of learning experiences and the possibility to provide educational interventions in emotionally supportive ways.” [13].

One potential barrier to the use of LA in the workplace is limited data. However, although obviously smaller data sets place limitations on statistical processes, MacNeill [14] stresses the importance of fast data, actionable data, relevant data and smart data, rather than big data. LA, she says, should start from research questions that arise from teaching practice, as opposed to the traditional approach of starting analytics based on already collected and available data. Gasevic, Dawson and Siemens [15]  also draw attention to the importance of information seeking being framed within “robust theoretical models of human behavior” [16]. In the context of workplace learning this implies a focus on individual and collective social practices and to informal learning and facilitation processes rather than formal education. The next section of this paper looks at social learning in Public Employment Services and how this can be linked to an approach to workplace LA.

2. EMPLOYID: ASSISTING IDENTITY TRANSFORMATION THROUGH SOCIAL LEARNING IN EUROPEAN EMPLOYMENT SERVICES

The European EmployID research project aims to support and facilitate the learning process of Public Employment Services (PES) practitioners in their professional identity transformation process. The aims of the project are born out of a recognition that to perform successfully in their job they need to acquire a set of new and transversal skills, develop additional competencies, as well as embed a professional culture of continuous improvement. However, it is unlikely that training programmes will be able to provide sufficient opportunities for all staff in public employment services, particularly in a period of rapid change in the nature and delivery of such services and in a period with intense pressure on public expenditures. Therefore, the EmployID project aims to promote, develop and support the efficient use of technologies to provide advanced coaching, reflection and networking services through social learning. The idea of social learning is that people learn through observing others behaviour, attitudes and outcomes of these behaviours, “Most human behaviour is learned observationally through modelling from observing others, one forms an idea of how new behaviours are performed, and on later occasions this coded information serves as a guide for action” [17]. Facilitation is seen as playing a key role in structuring learning and identity transformation activities and to support networking in personal networks, teams and organisational networks, as well as cross-organisational dialogue.

Social Learning initiatives developed jointly between the EmployID project and PES organisations include the use of MOOCs, access to Labour Market information, the development of a platform to support the emergence of communities of practice and tools to support reflection in practice.

Alongside such a pedagogic approach to social learning based on practice the project is developing a strategy and tools based on Social Learning Analytics. Ferguson and Buckingham Shun [18] say that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social learning, it takes into account both formal and informal educational environments, including networks and communities. “As groups engage in joint activities, their success is related to a combination of individual knowledge and skills, environment, use of tools, and ability to work together. Understanding learning in these settings requires us to pay attention to group processes of knowledge construction – how sets of people learn together using tools in different settings. The focus must be not only on learners, but also on their tools and contexts.”

Viewing learning analytics from a social perspective highlights types of analytic that can be employed to make sense of learner activity in a social setting. They go on to introduce five categories of analytic whose foci are driven by the implications of the changes in which we are using social technology for learning [18]. These include social network analysis focusing on interpersonal relations in social platforms, discourse analytics predicated on the use of language as a tool for knowledge negotiation and construction, content analytics particularly looking at user-generated content and disposition analytics saying intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovation.

The approach to Social Learning Analytics links to the core aims of the EmployID project to support and facilitate the learning process of PES practitioners in their professional identity development by the efficient use of technologies to provide social learning including advanced coaching, reflection, networking and learning support services. The project focuses on technological developments that make facilitation services for professional identity transformation cost-effective and sustainable by empowering individuals and organisations to engage in transformative practices, using a variety of learning and facilitation processes.

3. LEARNING ANALYTICS AND EMPLOYID – WHAT ARE WE TRYING TO FIND OUT?

Clearly there are close links between the development of Learning Analytics and our approach to evaluation within EmployID. In order to design evaluation activities the project has developed a number of overarching research questions around professional development and identity transformations with Public Employment Services. One of these research questions is focused on LA: Which forms of workplace learning analytics can we apply in PES and how do they impact the learner? How can learning analytics contribute to evaluate learning interventions? Other focus on the learning environment and the use of tools for reflection, coaching and creativity as well as the role of the wider environment in facilitating professional identity transformation. A third focus is how practitioners manage better their own learning and gain the necessary skills (e.g. self-directed learning skills, career adaptability skills, transversal skills etc.) to support identity transformation processes as well as facilitating the learning of others linking individual, community and organizational learning.

These research questions also provide a high level framework for the development of Learning Analytics, embedded within the project activities and tools. And indeed much of the data collected for evaluation purposes also can inform Learning Analytics and vice versa. However, whilst the main aim of the evaluation work is measure the impact of the EmployID project and for providing useful formative feedback for development of the project’s tools and overarching blended learning approach, the Learning Analytics focus is understanding and optimizing learning and the environments in which it occurs.

4. FROM A THEORETICAL APPROACH TO DEVELOPING TOOLS FOR LA IN PUBLIC EMPLOYMENT SERVICES

Whilst the more practical work is in an initial phase, linked to the roll out of tools and platforms to support learning, a number of tools are under development and will be tested in 2016. Since this work is placed in the particular working environment of public administration, the initial contextual exploration led to a series of design considerations for the suggested LA approaches presented below. The access to fast, actionable, relevant and smart data is most importantly regulated by strict data protection and privacy aspects, that are crucial and clearly play a critical role in any workplace LA. As mentioned above power relations and hierarchies come into play and the full transparency to be aspired with LA might either be hindered by existing structures or raise expectations that are not covered by existing organisations structures and process. If efficient learning at the workplace becomes transparent and visible through intelligent LA, what does this mean with regard to career development and promotion? Who has access to the data, how are they linked to existing appraisal systems or is it perceived as sufficient to use the analytics for individual reflection only? For the following LA tools a trade-off needs to be negotiated and their practicality in workplace setting can only be assessed when fully implemented. Clear rules about who has access to the insight gained from LA have to be defined. The current approach in EmployID is thus to focus on the individual learner as the main recipient of LA.   

4.1 Self-assessment questionnaire

The project has developed a self-assessment questionnaire as an instrument to collect data from EmployID interventions in different PES organisations to support reflection on personal development. It contains a core set of questions for cross-case evaluation and LA on a project level as well as intervention-specific questions that can be selected to fit the context. The self-assessment approach should provide evidence for the impact of EmployID interventions whilst addressing the EmployID research questions, e.g. the effectiveness of a learning environment in the specific workplace context. Questions are related to professional identity transformation, including individual, emotional, relational and practical development. For the individual learner the questionnaire aims to foster their self-reflection process. It supports them in observing their ‘distance travelled’ in key aspects of their professional identity development. Whilst using EmployID platforms and tools, participants will be invited to fill in the questionnaire upon registration and then at periodic intervals. Questions and ways of presenting the questionnaire questions are adapted to the respective tool or platform, such as social learning programmes, reflective community, or peer coaching.

The individual results and distance travelled over the different time points will be visualised and presented to individual participants in the form of development curves based on summary categories to stimulate self-reflection on learning. These development curves show the individual learners’ changes in their attitudes and behaviour related to learning and adaptation  in the job, the facilitation of colleagues and clients, as well as the personal development related to reflexivity, stress management and emotional awareness.

4.2 Learning Analytics and Reflective Communities

The EmployID project is launching a platform to support the development of a Reflective in the Slovenian PES in February, 2016. The platform is based on the WordPress Content Management System and the project has developed a number of plug ins to support social learning analytics and reflection analytics. The data from these plugins can serve as the basis for a dashboard for learners providing visualisations of different metrics

4.2.1 Network Maps

This plugin visualizes user interactions in social networks including individual contacts, activities, and topics. The data is visualised through a series of maps and is localised through different offices within the PES. The interface shows how interaction with other users has changed during the last 30 days. This way users can visually “see” how often they interact with others and possibly find other users with whom they wish to interact.

The view can be filtered by different job roles and is designed to help users find topics they may be interested in.

4.2.2 Karma Points

The Karma Points plugin allows users to give each other ‘Karma points’ and ‘reputation points’. It is based both on rankings of posts and of authors. Karma points are temporary and expire after a week but are also refreshed each week. This way users can only donate karma points to a few selected posts in each week. The user who receives a karma point gets the point added to her permanent reputation points.

4.2.3 Reflection Analytics

The Reflection Analytics plugin collects platform usage data and shows it in an actionable way to users. The purpose of this is to show people information in order to let them reflect about their behaviour in the platform and then possibly to give them enough information to show them how they could learn more effectively. The plugin will use a number of different charts, each wrapped in a widget in order to retain customizability.

One chart being considered would visualise the role of the user’s interaction in the current month in terms of how many posts she wrote, how many topics she commented on and how many topics she read compared to the average of the group.  This way, users can easily identify whether they are writing a similar number of topics as their colleagues. It shows change over time and provides suggestions for new activities. However, we also recognise that comparisons with group averages can be demotivating for some people.

4.3 Content Coding and Analysis

The analysis of comments and content shared within the EmployID tools can provide data addressing a number of the research questions outlined above.

A first trial of content coding used to analyse inputs into a pilot MOOC held in early 2015 using the FutureLearn platform resulted in rich insights about aspects of identity transformation and learning from and with others. The codes for this analysis were created inductively based on [19] and then analysed according to success factors for identity transformation. Given that identity transformation in PES organisations is a new field of research we expect new categories to evolve over time.

In addition to the inductive coding the EmployID project will apply deductive analysis to investigate the reflection in content of the Reflective Community Platform following a fixed coding scheme for reflection [20].

Similar to the coding approach applied for reflective actions we are currently working on a new coding scheme for learning facilitation in EmployID. Based on existing models of facilitation (e.g. [21]) and facilitation requirements identified within the PES organisations, a fixed scheme for coding will be developed and applied the first time for the analysis of content shared in the Reflective Community platform.

An important future aspect of content coding is going one step further and exploring innovative methodological approaches, trialing with a machine learning approach based on (semi-) automatic detection of reflection and facilitation in text. This semi-automatic content analysis is a prerequisite for reflecting analysis back to learners as part of learning analytics, as it allows the analysis of large amounts of shared content, in different languages and not only ex-post, but continually in real time.

4.4 Dynamic Social Network Analysis

Conceptual work being currently undertaken aims to bring together Social Network Analysis and Content Analysis in an evolving environment in order to analyze the changing nature and discontinuities in a knowledge development and usage over time. Such a perspective would not only enable a greater understanding of knowledge development and maturing within communities of practice and other collaborative learning teams, but would allow further development and improvements to the (online) working and learning environment.

The methodology is based on various Machine Learning approaches including content analysis, classification and clustering [22], and statistical modelling of graphs and networks with a main focus on sequential and temporal non-stationary environments [23].

To illustrate changes of nature and discontinuities at the level of social network connectivity and content of communications in a knowledge maturing process “based on the assumption that learning is an inherently social and collaborative activity in which individual learning processes are interdependent and dynamically interlinked with each other: the output of one learning process is input to the next. If we have a look at this phenomenon from a distance, we can observe a knowledge flow across different interlinked individual learning processes. Knowledge becomes less contextualized, more explicitly linked, easier to communicate, in short: it matures.” [24]

5. NEXT STEPS

In this paper we have examined current approaches to Learning Analytics and have considered some of the issues in developing approaches to LA for workplace learning, notably that learning interactions at the workplace are to a large extent informal and practice based and not embedded into a specific and measurable pedagogical scenario. Despite that, we foresee considerable benefits through developing Workplace Learning Analytics in terms of better awareness and tracing of learning, sharing experiences, and scaling informal learning practices.

We have outlined a pedagogic approach to learning in European Public Employment Services based on social learning and have outlined a parallel approach to LA based on Social Learning Analytics. We have described a number of different tools for workplace Learning Analytics aiming at providing data to assist answering a series of research questions developed through the EmployID project. At the same time as providing research data, these tools have been developed to provide feedback to participants on their workplace learning.

The tools are at various stages of development. In the next phase of development, during 2016, we will implement and evaluate the use of these tools, whilst continuing to develop our conceptual approach to Workplace Learning Analytics.

One essential part of this conceptual approach is that supporting learning of individuals with learning analytics is not just as designers of learning solutions how to present dashboards, visualizations and other forms of data representation. The biggest challenge of workplace learning analytics (but also learning analytics in general) is to support learners in making sense of the data analysis:

  1. What does an indicator or a visualization tell about how to improve learning?
  2. What are the limitations of such indicators?
  3. How can we move more towards evidence-based interventions

And this is not just a individual task; it requires collaborative reflection and learning processes. The knowledge of how to use learning analytics results for improving learning also needs to evolve through a knowledge maturing process. This corresponds to Argyris & Schön’s double loop learning [25]. Otherwise, if learning analytics is perceived as a top-down approach pushed towards the learner, it will suffer from the same problems as performance management. These pre-defined indicators (through their selection, computation, and visualization) implement a certain preconception which is not evaluated on a continuous basis by those involved in the process. Misinterpretations and a misled confidence in numbers can disempower learners and lead to an overall rejection of analytics-driven approaches.

ACKNOWLEDGEMENTS

EmployID – “Scalable & cost-effective facilitation of professional identity transformation in public employment services” – is a research project supported by the European Commission under the 7th Framework Program (project no. 619619).

REFERENCES

[1] SoLAR(2011).Open Learning Analytics: An Integrated & Modularized Platform. WhitePaper.Society for Learning Analytics Research. Retrieved from http://solaresearch.org/OpenLearningAnalytics.pdf

[2] Johnson, L. Adams Becker, S., Estrada, V., Freeman, A. (2014). NMC Horizon Report: 2014 Higher Education Edition. Austin, Texas: The New Media Consortium

[3] Duval E. (2012) Learning Analytics and Educational Data Mining, Erik Duval’s Weblog, 30 January 2012,  https://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/

[4] Ferguson, R. (2012) Learning analytics: drivers, developments and challenges. In: International Journal of Technology Enhanced Learning, 4(5/6), 2012, pp. 304-317.

[5] Ley T. Lindstaedt S., Klamma R. and Wild S. (2015) Learning Analytics for Workplace and Professional Learning, http://learning-layers.eu/laforwork/

[6] Pardo A. and Siemens G. (2014) Ethical and privacy principles for learning analytics in British Journal of Educational Technology Volume 45, Issue 3, pages 438–450, May 2014

[7] de Laat M. & Schreurs (2013) Visualizing Informal Professional Development Networks: Building a Case for Learning Analytics in the Workplace, In American Bahavioral Scientist http://abs.sagepub.com/content/early/2013/03/11/0002764213479364.abstract

[8] Conole G. (2014) The implciations of open practice, presentation, Slideshare, http://www.slideshare.net/GrainneConole/conole-hea-seminar

[9] Ferguson (2015) Learning Design and Learning Analytics, Presentation, Slideshare http://www.slideshare.net/R3beccaF/learning-design-and-learning-analytics-50180031

[10] Adomavicius, G. and Tuzhilin, A. (2005) Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering, 17, 734-749. http://dx.doi.org/10.1109/TKDE.2005.99

[11] Brusilovsky, P. and Peylo, C. (2003) Adaptive and intelligent Web-based educational systems. In P. Brusilovsky and C. Peylo (eds.), International Journal of Artificial Intelligence in Education 13 (2-4), Special Issue on Adaptive and Intelligent Web-based Educational Systems, 159-172.

[12] Zimmerman B. J, (2002) Becoming a self-regulated learner: An overview, in Theory into Practice, Volume: 41 Issue: 2 Pages: 64-70

[13] Bahreini K, Nadolski & Westera W. (2014) Towards multimodal emotion recognition in e-learning environments, Interactive Learning environments, Routledge, http://www.tandfonline.com/doi/abs/10.1080/10494820.2014.908927

[14] MacNeill, S. (2015) The sound of learning analytics, presentation, Slideshare, http://www.slideshare.net/sheilamac/the-sound-of-learning-analytics

[15] Gašević, D., Dawson, S., Siemens, G. (2015) Let’s not forget: Learning Analytics are about learning. TechTrends

[16] Wilson, T. D. (1999). Models in information behaviour research. Journal of Documentation, 55 (3), pp 249-70

[17] Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.

[18] Buckingham Shum, S., & Ferguson, R. (2012). Social Learning Analytics. Educational Technology & Society, 15 (3), 3–26

[19] Mayring, P. (2000). Qualitative Content Analysis. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 1(2). Retrieved from http://nbn-resolving.de/urn:nbn:de:0114-fqs0002204

[20] Prilla M, Nolte A, Blunk O, et al (2015) Analyzing Collaborative Reflection Support: A Content Analysis Approach. In: Proceedings of the European Conference on Computer Supported Cooperative Work (ECSCW 2015).   

[21] Hyland, N., Grant, J. M., Craig, A. C., Hudon, M., & Nethery, C. (2012). Exploring Facilitation Stages and Facilitator Actions in an Online/Blended Community of Practice of Elementary Teachers: Reflections on Practice (ROP) Anne Rodrigue Elementary Teachers Federation of Ontario. Copyright© 2012 Shirley Van Nuland and Jim Greenlaw, 71.   

[22] Yeung, K. Y. and Ruzzo W.L. (2000). An empirical study on principal component analysis for clustering gene expression data. Technical report, Department of Computer Science and Engineering, University of Washington.http://bio.cs.washington.edu/supplements/kayee/pca.pdf

[23] Mc Culloh, I. and Carley, K. M. (2008). Social Network Change Detection. Institute for Software Research. School of Computer Science. Carnegie Mellon University. Pittsburgh, PA 15213. CMU-CS-08116.

http://www.casos.cs.cmu.edu/publications/papers/CMU-CS-08-116.pdf

[24] R. Maier, A. Schmidt. Characterizing Knowledge Maturing: A Conceptual Process Model for Integrating E-Learning and Knowledge Management In: Gronau, Norbert (eds.): 4th Conference Professional Knowledge Management – Experiences and Visions (WM ’07), Potsdam, GITO, 2007, pp. 325-334.

http://knowledge-maturing.com/concept/knowledge-maturing-phase-model

[25] Argyris, C./ Schön, D. (1978): Organizational Learning: A theory of action perspective. Reading.

What is the political and social habit(u)s of present day universities?

January 18th, 2016 by Graham Attwell

I like Cristina Costa’s blog, “Is technology changing learning habit(u)s?” (and not only because she cited me). Cristina says how her study on students’ digital practices shows how students’ learning habitus (their histories/experiences with education) have not changed that much in the formal setting, even when they are presented with new pedagogical approaches. It is not so much an issue of their digital competence but an issue that the informal uses of technology do not simply transfer into formal contexts.

Students, she says, “have a feeling for the ‘academic game’ and do their best to adjust to the field’s rules in order to succeed in it.” It seems to me their was always something of a game in academia and especially in undergraduate education. Even in the early 1970s we had well developed strategies for getting through exams (for instance I undertook a rather more in depth study of past exam questions than I did of the overall curriculum and it worked well for me).

But there are more profound contradictions in today’s higher education system. On the one hand universities are supposed to be about education and learning – as expressed through Humboldt’s idea of Allgemeine Bildung—or well-rounded education—to ensure that each person might seek to realize the human potentialities that he possessed as a unique individual or more modern appeals for a broad liberal education (unless such an education can be seen as improving their employability). On the other hand in the UK students are paying substantial fees for a system designed to provide them with a qualification to realise the so called graduate wage premium in the world of work. In such a situation it is little wonder that students are reluctant to participate in the innovative pedagogies – described by Cristina as  Freirean and Deweyan type of pedagogical approaches – designed for them to explore ideas and knowledge – quite simply they want the knowledge and skills they need to pass the exams and thus justify the expenditure. In this situation students will readily adopt productivity apps – office tools, citation databases, revision apps etc – and of course will use technology for social purposes and entertainment. But I am afraid asking them to use social software for learning within the political and social habit(u)s of present day universities may be going to far.

Stagnation or innovation in Technology Enhanced Learning?

January 12th, 2016 by Graham Attwell

Just a quick note following up on my blog of yesterday noting the lack of new ideas in the exhibition at Online Educa Berlin. Today I read an interesting article entitled “Caputalism: Will Capitalism Die?” by Robert Misik on the Social Europe blog. Most of the article, as the title implies is given over to an analysis of the lack of growth and “secular stagnation” in western economies.

Misik says that “despite superficial impressions, the past 15 years may have produced practically no more genuinely productive innovations.” He quotes the economist Robert J Gordon who says:“Invention since 2000 has centered on entertainment and communication devices that are smaller, smarter, and more capable, but do not fundamentally change labour productivity or the standard of living in the way that electric light, motor cars, or indoor plumbing changed it.”

And that seems to sum up much of the developments in Technology Enhanced Learning. Whilst in the 1990s and the first years of this century there was something of an explosion in innovative uses of technology for learning through mainly the development of Virtual Learning Environments, since then genuine innovation has stalled, as least through the ed tech industry. Games based learning, Learning Analytics, mobile learning, MOOCs are all interesting but they do not, to paraphrase Gordon, fundamentally change education and learning, still less pedagogy. As Phil Hill says: “Didn’t we have bigger dreams for instructional technology?”

Misik speculates on the slow emergence of a new economy in which “more decentralized, self-managed firms, co-operatives and initiatives play a gradually more important role – so that, in the end, a mixed economy emerges composed of private companies, state enterprises and co-operatives and alternative economic bodies.” And that may be the way forward to for Technology Enhanced Learning, where the behemoths of the Ed Tech world play a lesser role, where governments continue to invest in innovation in teaching and learning with technology in education, where the importance of state involvement in education is recognised and where smaller more agile private sector enterprises become partners in developing new initiatives and pedagogic approaches to learning. Its nice to be optimistic!

A blog is just a blog

January 11th, 2016 by Graham Attwell

2016 and it is time to return to the blog after a crazy December of meetings, conferences, travel and exhaustion.

First a quick catch up from Online Educa Berlin. Online Educa is always enjoyable if only because so many friends and colleagues attend it. I am also always interested in the very large exhibition which provides a quick overview of market and to a lesser extent pedagogic trends in technology supported learning. Decembers exhibition was strange, though. Firstly there were no big stands. Go back five or six years and the big stands were from the public organisations supporting the adoption of technology in universities and education in general. The UK Jisc always had a big presence, so too did the Netherlands SURF network. When they dropped away – probably as a result of funding cuts, The Middle East countries took over with colourful booths, even if somewhat lacking in content. And of course there were the VLE suppliers – Blackboard (later to become Pearsons) could always be relied on for a free glass of wine at the end of a busy conference day. At Online Educa 2015 they were all missing. The largest stand was Egypt Arising. However – whether because of their materials not arriving or for some other reason- they has no content and seemingly no representatives on what remained an empty stand. Instead the exhibition was dominated by the cheaper to rent small stands, some from projects but mainly it appeared from start up companies.

It was hard too to discern any particular trends. A few years ago the exhibition was dominated by virtual world type apps. Another year it was all about interactive whiteboards. And the next year it was video apps that were dominating the scene. In 2015 it seemed to be a bit of everything and a bit of nothing.

It left be wondering if the days of educational technology are numbered. Yes we are moving to software as a service and this will impact of education. And of course data (sometimes big data) is making an impact in the form of Learning analytics. Learning management Systems or VLEs stubbornly refuse to go away although all the suppliers seem to stress how their platforms support personal learning pathways. But in truth much of the technology used for learning is little different from the productivity apps and social software being used in everyday business and living. Will 2016 be the year when – depending on how you look at it – educational technology becomes part of the mainstream or the mainstream is just technology used for learning. After all a blog is just a blog.

Live internet Radio this week from Online Educa Berlin

November 29th, 2015 by Graham Attwell

In what by now has become an annual event, we will be presenting Sounds of the Bazaar, the official online radio from Online Educa Berlin, on Thursday 3 and Friday 4 of December this week. The broadcasts will be from 11:00 to 11:45 CET. If you are a regular, we have a new venue this year –  in the area of the Internet Café. If you are lucky enough to be at the conference and  are willing to come on the programme could you email Graham Attwell – graham10 [at] mac [dot] com – saying which day is most convenient for you and what time in the programme suits you best. In general each slot lasts around 5 minutes.

And if you would like to catch up in person we will be preparing the shows in the Marlene Bar from about 1500 onwards tomorrow afternoon.

If you can’t make to to Online Educa in person, don’t despair. You can listen to all the best of the conference in our live radio shows. Just tune in at 11:00 CET on Thursday and Friday by pointing your internet browser to SoB Online EDUCA 2015 LIVE Radio  and the live stream will open up in the MP3 player of your choice. Or go here to our new stream webpage.

This years The OEB Debate, provides discussion on one of the hottest topics for learners with the motion: ’This House believes 21st Century skills aren’t being taught – and they should be´.

Keynotes this year include Prof Ian Goldin, Chair at Oxford’s Martin Institute and former Vice President of the World Bank; Cory Doctorow, activist, author and journalist; David Price, learning futurist and the author of OPEN: How We’ll Work, Live and Learn In The Future'; Anka Mulder, Vice President for Education of the Delft University of Technology; Toby Walsh, Professor of Artificial Intelligence at the University of New South Wales; John Higgins, Director General of DIGITALEUROPE and Lia Commissar, leader of the ‘Education and Neuroscience Initiative’ at the Wellcome Trust.

The future of libraries

August 19th, 2015 by Graham Attwell

The NMC Horizon Project, an ongoing research project designed to identify and describe emerging technologies likely to have an impact on teaching, learning, and creative inquiry has released its library edition. Six key trends, six significant challenges, and six important developments in technology are identified across three adoption horizons over the next one to five years, giving library leaders and staff, they say, a valuable guide for strategic technology planning.

The NMC Horizon Report > 2015 Library Edition identifies “Increasing Value of the User Experience” and “Prioritization of Mobile Content and Delivery” as short-term impact trends driving changes in academic and research libraries over the next one to two years. The “Evolving Nature of the Scholarly Record” and “Increasing Focus on Research Data Management” are mid-term impact trends expected to accelerate technology use in the next three to five years; and “Increasing Accessibility of Research Content” and “Rethinking Library Spaces” are long-term impact trends, anticipated to impact libraries for the next five years or more.

Golden Oldie

August 19th, 2015 by Graham Attwell

Thanks to a Tweet by @francesbell I picked up this olden but still golden video (around discussions in the first ever MOOC). As the Youtube blurb says “WARNING : This is not a real conversation. It is intended as a good-humoured parody of conversations about Groups and Networks that took place on CCK08 and elsewhere. This video is a mashup of the words of Bob Bell, Lisa Lane, Ariel Lion, Frances Bell, Stephen Downes, Ailsa Haxell, Roy Williams and possibly others, with a few extra words thrown to glue the conversation. You will have been quoted out of context, and otherwise had your words twisted but I hope you take this in good spirit.”

Does technology destroy jobs

May 18th, 2015 by Graham Attwell

Infoposter_V1The argument over whether technology creates or destroys jobs has been going on for as long as I can remember.

Only yesterday John Naughton, in an article entitled “We are ignoring the new machine age at our peril“, worried about the impact of self driving cars and other technology on the future of employment. Naughton argued that there are “radical discontinuities that nobody could have anticipated”, driven by “combinatorial” effects of different technology trends coming together. These, he siad, include: “the near-infinite computing power provided by Moore’s law; precise digital mapping; GPS; developments in laser and infrared sensor technology; and machine-learning algorithms plus the availability of massive data-sets on which to train them.”

He warned the outcome could be “that vast swaths of human activity – and employment – which were hitherto regarded as beyond the reach of “intelligent” machines may now be susceptible to automation.” he went on to quote a studyby  Dr Carl Benedikt Frey and Michael Osborne, two researchers at the Martin School in Oxford,T heir report, The Future of Employment: How Susceptible Are Jobs to Computerisation?,  estimates the probability of computerisation for 702 detailed occupations, based on US government classifications of those occupations.  About 47% of total US employment, they conclude, is at risk from technologies now operational in laboratories and in the field.

However a study entitled ‘Are ICT Displacing Workers? Evidence from Seven European Countries‘ by Smaranda Pantea, Federico Biagi and Anna Sabadash from the Institute of Prospective Technologies in Seville comes up with a different answer. Looking at micro data ins even European countries for companies in the manufacturing, ICT producing and service sector the study found “a non-significant relationship between employment growth and ICT intensity among ICT-using firms.: The authors say: “Since our estimates mainly capture the “substitution” effects of ICT on employment (i.e. those due to ICT substituting for some type of labour and to ICT increasing productivity and hence reducing demand for inputs, for constant values of output), our results indicate that these effects are statistically insignificant.”

Of course this study and the American study are not directly comparable. They looked at different things and used different methodologies. One conclusion might be that whilst technology is not being directly substituted for overall employment, it is changing the nature of jobs available. Some labour market studies (for instance based on the US O*Net surveys) have suggested that what is happening is a bifurcation of labour, with an increasing number of high qualified jobs and of low skilled (and consequently low paid) service sector jobs. And of course another impact may be on the ;content’ and different skills required in different jobs. For instance our work in the construction industry through the Learning layers project suggests increasing adoption of technology is leading to the need for new (and higher) skills levels within what was traditionally seen as a lower skills sector. This has considerable implications for vocational education and training. ather than training for presents skills demands VET systems need to be looking at future skills. And by providing those future orein3eteds kills this could provide a workforce and society with the abilities and motivation to shape our use of technology in society, rather than as John Naughton fears that “we’re bound to lose this race against the machine” and in the course “enrich the corporations that own it.”

Designing Applications To Support Mobile Work Based Learning In The Construction Industry

April 28th, 2015 by Graham Attwell

Along with Joanna Burchert, Gilbert Peffer and Raymond Elferink, I am presenting a paper at the EDEN conference on Expanding Learning Scenarios in Barcelona in June. the paper is based on work undertaken as part of the Learning Layers project. Below is the abstract. And if you would like to read the full paper you can download it from the link at the bottom of this page.

This paper focuses on the use of technology for (mainly informal) learning in Small and Medium Enterprises (SMEs) in the construction sector. It is based on work being undertaken by the EU funded Learning Layers project. The project is aiming to develop large scale take up of technology for informal learning in two sectors, health and construction.

The project includes both research and development strands, aiming to facilitate and support the development, testing and deployment of systems and tools for learning. The wider goals of the project are to develop sustainable models and tools for supporting learning in other countries and sectors. The paper describes the outcomes of empirical research undertaken in the construction sector as well as the co-design process contributing to the development of the Learning Toolbox, a mobile application for apprentices. The empirical research has been undertaken with a wide range of stakeholders in the construction industry, including surveys of apprentices whilst the co-design process has focused on trainers and apprentices.

Any use of mobile technology in and for work depends on the very specific situation and general conditions within a business sector. Hence research and development for mobile digital media includes both peoples’ needs and practices as workers and learners as well as specific business challenges, directions of development and needs concerning knowledge, skills and competencies. Testing and guiding the introduction of such solutions in enterprises and organisations could be understood as one kind of action research. Thus in researching and developing mobile learning applications and digital media for use in SMEs it is important to examine the possible impacts on employees and work processes as well as just the impact or potential for learning. The research in enterprises differentiated four lines of argumentation around the use of digital media: a) anxious-avoiding, b) critical, c) optimistic and d) pragmatically oriented,

Our interviews confirmed that technology is fast changing the world of construction, with increased work pressure and the demand to document work. It was noted that mobile devices are increasingly being used to produce a photographic record of construction work, as part of quality assurance processes. However, there was pronounced scepticism towards what was termed as “VET researcher fantasies” for instance in developing knowledge exchange networks. Companies were not prepared to share knowledge which was seen as giving them a competitive advantage over others.

The initial interviews were followed up with a survey of over 700 first, second and third year apprentices. The survey confirmed the desire for more use of mobile learning and a frustration with the limitations of existing commercial applications. Whilst only a limited number of companies permitted the use of mobile devices in the workplace, 53% of apprentices said they used them for learning or for obtaining work related information, explaining this was in their own time in breaks or after work.

The project is developing a ‘Learning Toolbox’, designed as a comprehensive architecture and framework for apprentice training and continuing training as well as for other services for the building and construction sector. Rather than training the main interest craft trade companies in web tools and mobile technologies is related to real-time, knowledge sharing, communication and problem-solving. Experience with earlier web tools has shown that they do not necessarily contribute to optimisation of work and business processes. However, flexible framework solutions like Learning Toolbox can be customised to their needs. Supplier companies (e.g. vendors of machinery, equipment and materials) want to customise user guidelines, maintenance manuals and instructional media for different users. They also need to develop real-time feedback mechanisms to improve error control mechanisms.

The implementation of Technology Enhanced Learning in SMEs will require capacity building in organisations, networks and sectors. This includes the capacity of trainers to support pedagogically the implementation of technology for learning, the development of technical infrastructure and the capacity of organisations and managements to support the use of technologies.

Finally is the importance of context in work based learning. Mobile learning applications need to be able to adapt to different contexts. These include, but are not limited to, the context of what kind of work is being undertaken, different forms of work organisation and different locations and forms of learning. The Learning Toolbox application is particularly designed to bridge formal and informal learning and to take account of the different contexts of learning in the vocational schools, learning in the industry training centre and learning on the construction site.

Download full paper (Word format) – mobileLearningEDENFIN

Researching MOOCs

April 24th, 2015 by Graham Attwell

In February we held the first annual review meeting for the EmployID project, which is focused on identity transformation and continuing professional development in European Public Employment Services. As part of the review process we have to deliver a series of (substantial) reports detailing the work we have done in different work packages in the project. Pontydysgu are involved in a range of work across the project and additionally coordinate work on Networking, Structuring and Coordination Tools. Having authored the report on this area I am now checking back through it to make sure there is nothing confidential before we publish the reports. And at the same time I thought I would publish selected highlights on this blog.

One focus for our work is around MOOCs. The following section summarises our background research into MOOCs. A future post will outline how we are taking this forward.

MOOCs continue to feature highly at conferences, seminars and events in the Technology Enhanced Learning community and are a subject of some debate and contention. Given the fast moving discussions, this section can only aim to summarise some of the subjects of debate.

There are now hundreds of open online courses available through branded MOOC platforms such as Coursera, Udemy, FutureLearn and Iversity along with self‐hosted courses direct from Universities and even individual lecturers offering open courses outside of their institutions. The vision of the MOOC is exactly that, Massive ‐ anyone can join in, Open ‐ materials available free of charge for all to use and repurpose, Online Course. The extent of the openness of many courses branded as MOOC is questionable, most materials are locked behind logins, passwords and time limits. Some courses come with a fee. As described above, a MOOC is not always a MOOC.

Research by the UK Department for Business Innovation and Skills (BIS) in 2013 highlighted two conflicting strands of thought amongst MOOC professionals.

A strand of enthusiasts welcomes the shake‐up and energy MOOCs bring to learning, teaching and assessment. They report positively on learning experiences and innovative formats of pedagogy, and spotlight themes such as access, empowerment, relationship building and community. This strand is particularly prevalent in the general press. Examples include Shirky and Legon.A strand of sceptics tempers the general enthusiasm along two themes. The supposed benefits of MOOCs were already realised in previous generations of Open and Distance Learning (ODL) innovation – and the innovations of MOOCs are the victory of packaging over content. The MOOC format itself suffers from weaknesses around access, content, quality of learning, accreditation, pedagogy, poor engagement of weaker learners, exclusion of learners without specific networking skills.

The themes emerging from both sides of the argument are those of access and inclusion of learners, quality of content, teaching and learning, networks and communities, and accreditation.

A recent study of MOOCs run by MIT showed that the most typical registrant in the courses were males aged 26 or older with a Bachelor’s degree. However, when the data is viewed in context it is notable that this demographic accounts for less than one in three registrants. Other statistics collected from 17 courses comprising over 600,000 registrants showed that 33% had high school or lower levels of education, 6.3% were over 50, and 2.7% had IP or mailing addresses from countries on the United Nations’ list of least‐developed countries (Rutter, 2014, Ho et.al., 2014, DeBoer et.al., 2014).

The formulaic structure of the branded courses such as Coursera make it easy for a course provider to quickly create an attractive looking sequence of lessons with video, text and assignments. One downside to this method is that there are now hundreds of identical looking courses consisting of video lectures, further reading and the occasional multiple choice quiz. The format has been referred to by critics as “The sage on a stage” and pedagogically reflects the paradigm that teaching is a one‐way process of giving knowledge to another. It is of course possible to use such a platform without being a slave to the formula, but more interaction with students requires more input and more time on the part of the course providers. The issue for the course facilitator is that online courses take time; a survey of professors running MOOCs recently reported that over 100 hours of work occurs before the course has started with a further 8 to 10 hours a week on upkeep (Kolowich, 2013). Factor in that the number of enrolled students on a MOOC can be as high as 160,000 (Rodriguez, 2012) and it becomes evident that dealing with individuals can be an almost impossible task.

Research carried out by MIT into 17 courses on the edX platform suggests that course completion may not be a valid success criteria for online courses or learners. “Course completion rates, often seen as a bellwether for MOOCs, can be misleading and may at times be counterproductive indicators of the impact and potential of open online courses.”

The researchers found evidence of large numbers of registrants who may not have completed a course but still accessed substantial amounts of course content.” (Rutter, 2014)

One of the most contentious debates has been dropout and completion rates. MOOCs in general have a very high dropout rate when compared to conventional courses (both face to face and online). Critics have pointed to this as evidence of the poor quality of courses and the lack of support for learning. Proponents of MOOCs have countered by pointing out how easy it is to sign up for free and open courses and that many learners join only wishing to undertake part of a programme. Openness, they say, is allowing more learners to embark on courses and that conventional measurements of quality such as completion rates are inappropriate for MOOCs.

The openness and availability of the resources will have some impact on the uptake of an online course by students. Participants can be put off by long registration processes or constant requests for login information. It is interesting to note that when materials are easy to access a number of students continue to access, study and participate in online courses beyond the official synchronous running times. Campbell (2014) describes these participants as “archived‐learners”;

“Despite the lack of a defined cohort, deadlines, strong instructor‐ presence, and the ability to earn a Statement of Accomplishment, archived‐learners indicate similar intent and exhibit similarbehavior to live‐learners. And this behavior extends beyond watching videos to completion of assessments and interaction on the discussion forums.” (Campbell, 2014)

The way in which students interact with online course content can be compared to the way in which people interact with other Web‐based media such as video or social network sites. (Rutter, 2014).

Research shows that students tend to navigate a non‐linear pattern through course content with students deemed successful (in that they achieved the certification available for the course) skipping around 20% of the content (Guo & Reinecke, 2014).

BIS (2013) summarises that “Learners who have completed MOOCs emerge from the literature as relatively enthusiastic about the MOOC format. Different kinds of learner experience have been identified, and passive consumption or lurking in a MOOC is a common pattern. The consensus is growing that lurking and auditing have validity as a learning activity within MOOCs, and that non‐completion is not a significant problem in this learning format.”

The early cMoocs were developed using a mixture of Open Source and homegrown software and some providers continue to follow such an approach. The last two years have seen the rapid emergence of MOOC platforms, driven in part by the need to ensure scalability and in part by attempting to standardise and facilitate MOOC design. Most, although not all, of these platforms have been developed by private organisations, often backed by venture capital funding and working in partnership with academic organisations for providing content. There have been some innovations, for instance in allowing designers to annotate video.

There has been some criticism by course developers of the limitations of platforms, particularly the xMooc platforms.

It is likely that more platforms will be released over the next two years and that some will be available as Open Source Software

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    Sounds of the Bazaar LIVE from the OEB 2015

    We will broadcast from Berlin on the 3rd and the 4th of December. Both times it will start at 11.00 CET and will go on for about 45 minutes.

    Go here to listen to the radio stream: SoB Online EDUCA 2015 LIVE Radio.

    Or go to our new stream webpage: Sounds of the Bazaar Radio Stream Page

    News Bites

    Teachers and overtime

    According to the TES teachers in the UK “are more likely to work unpaid overtime than staff in any other industry, with some working almost 13 extra hours per week, according to research.

    A study of official figures from the Trades Union Congress (TUC) found that 61.4 per cent of primary school teachers worked unpaid overtime in 2014, equating to 12.9 additional hours a week.

    Among secondary teachers, 57.5 per cent worked unpaid overtime, with an average of 12.5 extra hours.

    Across all education staff, including teachers, teaching assistants, playground staff, cleaners and caretakers, 37.6 per cent worked unpaid overtime – a figure higher than that for any other sector.”


    The future of English Further Education

    The UK Parliament Public Accounts Committee has warned  the declining financial health of many FE colleges has “potentially serious consequences for learners and local economies”.

    It finds funding and oversight bodies have been slow to address emerging financial and educational risks, with current oversight arrangements leading to confusion over who should intervene and when.

    The Report says the Department for Business, Innovation & Skills and the Skills Funding Agency “are not doing enough to help colleges address risks at an early stage”.


    Skills in Europe

    Cedefop is launching a new SKILLS PANORAMA website, online on 1 December at 11.00 (CET).

    Skills Panorama, they say,  turns labour market data and information into useful, accurate and timely intelligence that helps policy-makers decide on skills and jobs in Europe.

    The new website will provide with a more comprehensive and user-friendly central access point for information and intelligence on skill needs in occupations and sectors across Europe. You can register for the launch at Register now at http://skillspanorama.cedefop.europa.eu/launch/.


    Talking about ‘European’ MOOCs

    The European EMMA project is launching a  webinar series. The first is on Tuesday 17 November 2015 from 14:00 – 15:00 CET.

    They say: “In this first webinar we will explore new trends in European MOOCs. Rosanna de Rosa, from UNINA, will present the philosophy and challenges behind the EMMA EU project and MOOC platform developed with the idea of accommodating diversity through multilingualism. Darco Jansen, from EADTU (European Association of Distance Teaching Universities), will talk about Europe’s response to MOOC opportunities. His presentation will highlight the main difference with the U.S. and discuss the consequences for didactical and pedagogical approaches regarding the different contexts.


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