Call for Expressions of Interest for postdoctoral Marie Curie Incoming Fellowship at Copenhagen Business School

Marie Sklodowska-Curie Individual Fellowships – Call for Expressions of Interest

Copenhagen Business School – Department of Digitalisation

Location: Copenhagen, Denmark

Salary:  The salary range for the fellowship will fall within the range of € 66 000 -€70 000 per annum (salary levels 6-8), subject to negotiation in accordance with the Danish Ministry of Finance guidelines. The grant includes a family allowance of € 500/month for eligible researchers.

Hours: Full time

Contract type: Fixed term

Closing date for Expressions of Interest: 30 June 2019

Closing date for submission of applications: 11 September 2019


The Fellowship

The Marie Sklodowka Curie Individual Fellowships (MCIFs) are prestigious fellowships funded by the European Commission. They offer a generous allowance for 12-24 months including mobility, family and research allowance. Applicants can be from any country, must hold a PhD (or equivalent), and must not have resided or carried out their main activity in Denmark for more than 12 months in the 3 years immediately prior to the MCIF deadline on 11 September 2019. MCIFs follow a bottom-up approach, that is research fields and topics are chosen freely by the applicants, in collaboration with their prospective hosts.



The Department of Digitalization (DIGI) at Copenhagen Business School (CBS) welcomes expressions of interest from postdoctoral researchers with an excellent track record of research and publication to apply jointly with a supervisor from DIGI/CBS to Marie Sklodowska-Curie Individual Fellowship Scheme. Selected candidates will receive dedicated support from a DIGI Senior Professor, as well as CBS’s Research Support Office to develop their proposal and application for submission to the European Commission by 11 September 2019.  The successful candidates will benefit from travel funding provided by CBS to visit the host professor for 1-2 days in July/August 2019 to discuss and plan the full proposal for submission to the European Commission. The host at CBS is Professor Anoush Margaryan.


Research themes

Expressions of Interest that are aligned with one of more of the following research themes are welcome:

  1. Workplace learning and skill development practices in emergent forms of digital work such as crowdwork in online labour platforms
  2. Policy and practice implications of crowdwork and other emergent forms of digital work for pedagogy in higher education settings
  3. Practices and processes of worker self-organisation and networking for learning, knowledge sharing and skill development in crowdwork

Candidates with a (interdisciplinary) background in, including but not limited to, Learning Sciences, Workplace Learning, Education, Sociology, Psychology, Communication Studies, Information Science, Business and Organisational Studies/Human Resource Development and a strong interest in workplace learning research are welcome to apply.


How to express your interest

Expressions of interest should include:

  1. Your CV including a full list of your publications, research grants and projects
  2. A max 2-3 page Research Proposal Summary aligned with one or more of the above themes
  3. A max 1-2 page motivation letter identifying synergies with key research areas listed above

Please email your EoI pack as one single PDF file attachment, putting ‘MCIF Expression of Interest’ as your email subject to Bodil Sponholtz, by Sunday 30 June 2019. 

Expressions of interest will be selected on the basis of the quality of the research idea and the candidate’s track record. Successful candidates will be informed by Monday 8 July 2019 when they will be invited to make a formal application to the European Commission with their CBS host Professor Anoush Margaryan.

To allow sufficient time for institutional approvals, the final draft of the full proposal is expected to be ready for review by the host by Tuesday 3 September 2019.

For further information and to arrange an informal discussion please contact Professor Anoush Margaryan


New paper on learning practices in crowdwork

My paper “Workplace learning in crowdwork: Comparing microworkers’ and online freelancers’ practices” has been accepted for publication in the Journal of Workplace Learning.  Here is the abstract:

Purpose: This paper explores workplace learning practices within two types of crowdwork– microwork and online freelancing. Specifically, the paper scopes and compares the use of workplace learning activities (WLAs) and self-regulatory learning strategies (SRL strategies) undertaken by microworkers and online freelancers. We hypothesised that there may be quantitative differences in the use of WLAs and SRL strategies within these two types of crowdwork, because of the underpinning differences in the complexity of tasks and skill requirements.

Methodology: To test this hypothesis, a questionnaire survey was carried out among crowdworkers from two crowdwork platforms – Figure Eight (microwork) and Upwork (online freelancing). Chi-square test was used to compare WLAs and SRL strategies among online freelancers and microworkers.

Findings: Both groups use many WLAs and SRL strategies. Several significant differences were identified between the groups. In particular, moderate and moderately strong associations were uncovered, whereby OFs were more likely to report (i) undertaking free online courses/tutorials; and (ii) learning by receiving feedback. In addition, significant but weak or very weak associations were identified, namely OFs were more likely to learn by (i) collaborating with others; (ii) self-study of literature; and (iii) making notes when learning. In contrast, MWs were more likely to write reflective notes on learning after the completion of work tasks, although this association was very weak.

Contribution: The paper contributes empirical evidence in an under-researched area – workplace learning practices in crowdwork. Crowdwork is increasingly taken up across developed and developing countries. Therefore, it is important to understand the learning potential of this form of work and where the gaps and issues might be. Better understanding of crowdworkers’ learning practices could help platform providers and policymakers to shape the design of crowdwork in ways that could be beneficial to all stakeholders. The paper outlines several implications for the design of crowdwork.


RWL09 Conference: paper, presentation, etc.

I am at present in Copenhagen to participate in the 2009 Researching Work and Learning (RWL) Conference.  The conference kicks off tomorrow (Sunday July 28) with an opening reception, keynote and dinner at the Workers Museum in Copenhagen.  The rest of the conference will take place at Roskilde University.

I have decided to stay in Roskilde rather than Copenhagen in order to avoid the daily 25-30 minute journey to the conference – in retrospect this was not a very smart decision.  The hotel which was booked for me turned out to be approx 25 minutes away from the university anyway (10 min walk to the station+5 min train+10 min walk to the university).   On the positive side – the weather is great (sunny, +25C) and forecasts indicate it will stay so in the next 5 days.

I am looking forward to the conference.  I am planning to live-blog the interesting presentations, of which I hope there will be many.  The programme looks promising.

I am presenting a paper titled “Self-regulated learning and knowledge sharing in the workplace: Similarities and differences between novices and experts” co-authored with Colin Milligan and Allison Littlejohn.  The paper is part of a symposium on Integrating Workplace Learning and Institutional Learning. I don’t think our paper fits the theme of the symposium very well, but I am hoping the discussion will be useful anyway.  The presentations is now on the slideshare.

Developmental level of self-regulatory skills in the workplace

Barry Zimmerman in his article Attaining self-regulation: A social congintive perspective argues that most skills (congnitive and motoric) are initially acquired by observing, reading, or hearing about the performance of skilled social models (teachers, experts, experienced peers, etc). He argues that the socially-conveyed skills become self-regulated through a series of levels. These developmental levels of regulatory skills are:

Level 1- Observation-Vicarious induction of a skill from a proficient model

Level 2 – Emulation-Imitative performance of the general pattern/style of a model’s skill with social assistance

Level 3-Self-control-Independent display of the model’s skill under sturctured conditions

Level 4 -Self-regulation-Adaptive use of skill across changing personal and environmental conditions

Zimmerman says that there is evidence that the speed and quality of the development of self-regulatory skills “can be enhanced significantly if learners proceed according to a multilevel developmental hierarchy” (p. 31). He then describes an unpublished study by Kistantas, Zimmerman and Cleary* who compared the development of dart skill by novices who learned initially from modelling (a skilled dart player demonstrated dart throwing strategies and provided feedback on a selective basis) with that of learners who initally learned from enactment.  The study found that learners who had the benefit of modelling “significantly surpassed the dart skill of those who attempted to learn from performance outcomes only” (p. 31). And “learners who received feedback learned better than those who practiced on their own, but the feedback was insufficient to make up for the absence of vicarious experience” (p.31). Learners exposed to strategic modelling “showed higher levels of self-motivation according to an array of measures such as self-efficacy and intrinsic interest than students who realied on discovery and social feedback” (p.32).

It would be interesting to conduct a similar study in the context of self-regulated learning in the workplace (non-instructional, non-formal learning), in addition to extending it to cognitive rather than only motoric skills.  It would also be interesting to study to what extent exerienced peers can facilitate development of self-regulatory skills in the workplace during levels 1-4.

* Kistantas, A., Zimmerman, B., & Cleary, T. (1999). Observation and imitation phases in the development of motoric self-regulation. Unpublished manuscript. Graduate School of the City University of New York.

Self-organisation, evolution of social systems and learning

In the past few months, together with some colleagues in the caledonian academy, Iw have been working on self-regulation, mainly in the context of knowledge work and non-formal learning in the workplace, and particulalry the role of emergent technologies in enhancing self-regulation.  Most of this work is in early conceptualisation stage (including in the form of a couple of EU research grant proposals being submitted) and has not been published yet, apart from some deliberations by various colleagues in our group blog and a presentation at the last EDMEDIA conference.

There are various notions related to self-regulation, such as self-direction and self-organisation, and we are thinking about which of these may best descibe learning in the context of both formal and non-formal learning.  Isobel Falconer reviews what some of the psychology literatue has to say on this.   

I have come across interesting work by Charlotte Hemelrijk and colleagues looking at self-organisation from the perspective of complexity science and particularly in the context of evolution of social systems of animals (including humans).  They are exploring self-organisation within social systems ranging from single-celled organisms to humans; within groups of various sizes ranging from small (eg primates) to very large (eg social insects); and are dealing with various aspects of organistion such as group formation, task-division, dominance interactions, language and voting.

This work offers very interesting insights, although many of the findings and concepts being discussed, I think, cannot be directly extrapolated to (informal) learning in the workplace and have to be used metaphorically in this context.  Some relevant points are summarised below:

1. Self-organisation is defined as “the emergence of order on a global scale through interactions on a local scale” (de Boer, p.123).  This is predicated on the following assumption:

2. The system within which self-organisation occurs has two components: actors and interactions. Actors do not have to be able to determine their own actions and can behave in a completely reactive way (eg they can be molecules or neurons).

3. “There is a population of actors and the interactions always entail a number of actors that is considerably smaller than the total number of actors in the population. This is what is meant by interaction on a local scale” (de Boer, p. 124).

4. “Behaviour that cannot be predicted directly from the behaviours of indvidual actors in a system, but is caused by interaction between actors and/or their environment, is referred to as emergent behaviour or emergence” (ibid).

5. “When emergent behaviour involves many indviduals and results in regulat collective behaviour, then it is referred to as self-organising” (ibid)

6. “For self-organising to happen, there must be positive feedback between the behaviour of individuals. Small fluctuations in individuals must be amplified and adopted by other individuals for a pattern to spread through the population” (ibid).

7. “Emergent phenomena arise in social systems as a consequence of self-reinforcing effects, which imply that if an event takes place it increases the likelihood that it will happen again” (Hemelrijk, p.1). For example Deneuborg et al show how in the context of foraging for food in ant colonies, when there are two food sources of identical quality and size, by accident one path may be marked (by pheromons) more strongly than another; as a consequence, ants will be attracted to that path and so it will be marked more strongly again. In human societies more complex set of variables may be at play, but can this example tell us anything about the underlying mechanisms of how deas get spread and adopted among humans? (memetics, diffusion of innovation, learning).

8. “In animal societies, collective decisions and patterns emerge thorugh self-organised processes, from a variety of interactions among indviduals.  The rules specifying these interactions are executed using only local information, without reference to the global pattern. Therefore collective decisions can be made that at the individual level require omnly limited cognitive abilities and partial knowledge of the environment” (Deneubourg et al, p. 25)

9. “Most self-organised decisions and patterns arise as a result of a competition between different sources of information that are amplified trhough positive feedback.” (ibid)

Reference: Hemelrijk, C. (2005) (Ed.). Self-organisation and evolution of social systems. Cambridge: Camrbidge University Press.

Process-oriented teaching for self-directed lifelong learning

This morning I read a paper on this subject by Sanneke Bolhuis (Bolhuis, S. (2003) Towards process-oriented teaching for self-directed lifelong learning: A multidimensional perspective. Learning and Instruction, 13, 327-347. )

Recently I have been reading and thinking quite a lot about self-directed learning in relation to a research proposal on charting my Caledonian Academy colleagues and I are developing with our partners in a European consortium, and also in relation to our project with Shell Learning.

As evident from the title, the main focus on the paper is self-directed learning within formal instructional settings where learning is the aim (schools, higher education). Our interest in contrast is primarily in self-direction in the workplace, where learning is only a by-product of carrying out work tasks (thus not formal learning in the workplace, eg in-house training, various forms of formalised coaching and mentoring and so on).  The paper, however, raises a number of issues that are important regardless of the context.

Bolhuis grounds self-directed learning in the lifelong learning agenda, and outlines four groups arguments in support of teaching for self-directed learning (quoted almost verbatim from pp 328-329):

1. Argument from education – learners in lower educational levels (school) should be prepared for the next educational level (higher or vocational education), where they are required to study more independently.  So the focus is on acquiring skills in self-direction in order to be able to succeed in higher levels of education.

2.  Argument from economy – knowledge productivity as a key economic motor.  Here skills in self-direction are seen critical in ensuring that enough people are able to create new knowledge and others are at least able to catch up with the changes that are brought about by changes in knowledge.

3. Argument from society – effects of globalisation (multiculturalism, mobility, media), which bring about situations where people are increasingly confronted with others who have a different view of the world, different knowledge, different beliefs, and different habits.   Self-direction here is linked to learning how to deal with these other “truths”. Self-directed learning in this context is also linked to elimination of inequalities in socio-economic position, ethnicity and gender and cultural struggles against the negative effects of globalisation.

4. Argument from democracy – teaching individuals to become self-directed learners contributes to a truly democratic society. Democracy can only function if people have equal possibilities to inform themselves, solve problems, make well-considered choices, and take part in society.

Bolhuis then discusses how recent theories of learning broaden the concept of learning as an aspect of all activity (thus also work activity, which is my primary interest).   In discussing the experiential and social context of learning, Bolhuis suggests that school activity (arguably also education), in contrast with practice, is mainly concerned with manipulation of symbolic information.  Some other authors have argued that this is one of the main differences between the world of education and the world of work (eg Candy and Crebert, 1996). However, I am wondering if this is entirely true in the context of knowledge work, where a large part work is concerned with manipulation of symbolic information, albeit at higher levels of analysis and synthesis than is the case in education.

Bolhuis emphasises the domain-specific nature and socio-material contextuality of the capacity for self-directed learning and that a lot of knowledge is encoded within “networks of meaning” – problem statements, concepts, rules, expressed in a partly domain specific language.  Bolhuis argues that the access to this knowledge is the main difference between experts and novices in a knowledge domain.

An individual’s learning potential depends on expertise in the learning domain (but Bolhuis doesn’t mention any productive action in work domain):

  1. knowing what and how to learn in the domain
  2. having access to a relevant knowledge base to build on
  3. being motivated to learn in the domain (motivation is domain specific)

Bolhuis argues that the development from novice to expert includes the development of these three interacting aspects.  Experts are expected not only to possess vast knowledge, but to contribute knowledge to the domain. Moreover, Bolhuis seems to imply that, the sources of novices’ and experts’ motivation-formation are different – experts’ motivation comes from strong internal goals.  In our work on charting where we are trying to develop tools and approaches to increase productivity and decrease time to competence during transition from education to workplace, we are trying to understand the different factors impacting formation of goals in these different contexts.

Bolhuis suggests that learning in a social context refers to model-learning, whereby individuals internalise the interpretations of “significant others”. I try to avoid the word “internalise” because of the connotations of passivity in taking something in, however overall this notion of significant others is especially important in the workplace, where so many aspect of productivity and performance are interrelated with others, and where even expertise (recognition of)  depends on and takes place in relation to others. 

Bolhuis also responds to those who criticise self-directed learning as an individual learning process and emphasises that it cannot be free from socio-economic and political context.  “Self-direction refers to being in command of oneself, moving towards one’s own goals” (p. 335).  I think that while self-directed learning doesn’t imply individual learning, self-direction is a largely individual action, albeit shaped by the socio-cultural, organisational, economic and political context. 

Emotional aspects of self-directed learning are discussed.  Motivation in educational settings, argues Bolhuis, is often problematic, because students are not involved in goal setting. Rewards in educational settings are extrinsic, which leads students away from goal-oriented motivation.  While in general I agree, I think that this happens in workplace setting as well (depending on organisational culture, management style, nature of job, indviduals’ position within an organisational hierarchy, etc), that’s why organisational dimension is important, ie that organisations and jobs allow self-direction.

Bolhuis proposes a conceptual model outlining the main components of learning in life.  It consists of goal setting, orientation and mobilising prior knowledge, executing learning activities, and evaluating processes and results and each of these 4 components is related to social context.  Each of these components are treated in detail (pp 335-338):

  1. Setting goals – learning in life follows from life goals not from setting learning goals
  2. Orientation – mobilising prior knowledge and investigating possible routes to move towards the goal (searching for information, social and material resources, action opportunities and planning).
  3. Executing a variety of learning activities – learning is not separated from other life activities, it rather flows from a variety of activities. Mental activities by which we learn are 1)social interaction, 2) processing verbal and other symbolic information, 3) direct experience, and 4) reflection. [Beginnings of a typology for charting activities, actions and operations?]
  4. Evaluating process and results – doesn’t take place in the end but is often diagnostic and leads to renewed orientation, other learning activities or a change in goal.
  5. Regulating – monitoring progress and decision making

Further reading:

Kessles, J (1996). Het Corporate Curriculum. Leiden: University of Leiden.