Two postdoctoral researcher positions available at Copenhagen Business School Department of Digitalization

Job title	Postdoctoral Researcher
Institution	Copenhagen Business School
Department	Digitalization (DIGI)
Division	Learning in the Platform Economy (LeaP) Research Programme
Location	Howitzvej 60, Frederiksberg 2000, Copenhagen, Denmark
Salary	DKK 36.269 – 43.027 per month depending on experience
Hours & Contract type	Full time (37 hours per week), fixed term for 2 years
Closing date	9 January 2022

The roles

We are seeking two outstanding Postdoctoral Researchers to work with Professor Anoush Margaryan at Copenhagen Business School’s Department of Digitalization on a research programme investigating workplace learning and skill development practices in emergent forms of online and AI-mediated work.

The research programme is titled ‘Learning practices in the platform economy’ (LeaP). It has been funded by the Volkswagen Foundation, Alexander von Humboldt Foundation, Candys Foundation, the European Centre for the Development of Vocational Education (Cedefop) and is led by Professor Margaryan.

LeaP is an interdisciplinary research programme focused on advancing the theory, methodology and policy of learning practices and learning processes in the platform economy. LeaP pursues a dual aim of (i) advancing the understanding of fundamental processes and practices of workplace learning and skill development within new and emergent forms of work in platform and AI-mediated settings; and (ii) developing applications, toolkits and design guidelines to inform and guide policy and practice of workplace learning in the digital economy. LeaP seeks to develop impactful research outcomes that contribute tangible theoretical and methodological advances as well as helping organisations, policymakers and other societal stakeholders nationally and internationally to design workplace and work-related learning environments that can empower individuals to take control of their own learning and development, fostering economic performance, capabilities, skills and well-being in our societies.

LeaP leads research around three interrelated themes: (i) workplace learning practices and processes in new and emergent forms of online platform work; (ii) skill formation and learning in AI-mediated work settings; and (iii) aligning higher education and emergent work practices in the digital economy.

Postdoctoral Researcher 1 will broadly focus on the analysis of workplace learning and skill development practices and processes in online labour platforms (LeaP theme 1) while the second post will examine the nature, practices and processes of skill formation and development in AI-mediated workplaces (LeaP theme 2). Whilst each post will focus on their own theme, both posts will be expected to contribute to LeaP theme 3, by developing ideas on how the outputs from their research could inform teaching practices in education to ensure that students are well-prepared for the future of work.

The Postdoctoral Researchers will be expected to work with Professor Margaryan on ongoing projects within the LeaP programme, whilst developing their own independent research profile within the remit of the LeaP research programme.  They will be expected to publish research of international excellence in peer-reviewed journals (such as those included in FT50 and AJG 3-4* ranking lists and discipline-specific high impact journals).  The Postdoctoral Researchers will be expected to fully engage and participate in the academic life of the research group and the University. 

Both positions are 100% research-focused and do not include teaching duties.

Candidate profile

The successful candidates will hold a PhD (or be very near defending/submitting their PhD) specialising in adult professional learning, workplace learning, education/training, sociology of education, work/educational psychology, human resource development or other related fields that study learning processes and/or learning practices of adults in work settings. It is essential that the candidates have prior experience of research on workplace/adult learning and skill development in the workplace, preferably in digitally-mediated, knowledge-intensive domains.  Candidates should demonstrate interest in grounding their research in fundamental learning sciences theory, in particular theories of adult learning and development, technology-enhanced professional learning, workplace learning and self-regulated learning.  Experience of research on learning practices in online labour platforms and AI-mediated work settings would be a plus. The successful candidates will demonstrate proven ability to write articles in English suitable for publication in high-impact journals. They will have advanced skills in analysing quantitative data (in R or Stata), solid experience of analysing qualitative data (with Nvivo or similar) and proven experience of collecting quantitative and qualitative data. They will be self-regulated and organised, proactive, attentive to detail, and possess effective interpersonal skills.

Main responsibilities

• Collecting and analysing quantitative and qualitative data, including analysing existing survey and questionnaire datasets recently collected within the LeaP research programme  
• Undertaking literature search and reviews and other desk research
• Contributing to and leading journal publications co-authored with other members of LeaP
• Contributing to and leading other types of research dissemination activities such as conference presentations, blogs and project reports
• Engaging with and regularly presenting the progress of their research within internal seminars
• Developing ideas for follow-up research grants and collaborating with Professor Margaryan and other members of the group on grant writing
• Contributing to research programme administration; assisting in grant reporting; maintaining LeaP website and blog; and supporting other members of the group as required
• Helping to develop work plans and monitor progress highlighting issues and risks in a timely manner
• Facilitating day-to-day communication and collaboration between the members of the research programme and the internal and external collaborators
• Representing LeaP at internal and external meetings, seminar and events and presenting papers and talks at conferences, public events and internal and external stakeholder meetings 
• Managing own research and administrative activities in line with agreed deliverables and timeline

Selection criteria

Essential criteria

• A completed PhD (or near completion) in one of the following disciplines/fields: learning sciences, adult and workplace learning, technology-enhanced learning (with grounding in social sciences research), education/training, sociology of education, work/educational psychology, human resource development, or related fields with specialisation in learning processes and/or learning practices of adults in work settings
• Proven ability to write academic articles in English publishable in highly impact-rated journals
• Evidence of advanced skills in analysing quantitative data (R or Stata)
• Evidence of solid experience of analysing qualitative data (Nvivo or similar)
• Proven ability to work both independently and under supervision managing own tasks within agreed deliverables and deadlines
• Evidence of strong interpersonal and communication skills, self-regulation, proactivity, and attention to detail
• Excellent spoken and written English
• Proven skills and positive mindset for effective and efficient remote work

Desirable criteria

• Experience researching online labour platforms, crowdwork and AI-mediated work
• Grant writing experience

How to apply

Applications should include the following documents:

1. Your full CV including a list of your academic publications and grants if any
2. Cover letter, maximum 2 pages long, specifying how your profile aligns with the essential and desirable criteria listed above (please address all 10 criteria).
3. A copy of your sole-authored academic writing in English, such as your PhD thesis, a journal article or a research project report you sole-authored. 
4. Names and contact details of two referees who are closely familiar with your research and your professional performance (do not send reference letters please, names and contact details would be sufficient).

Please email your applications as one single PDF file attachment, putting “LeaP Postdoc application” as the subject line to Anoush Margaryan ama dot digi at cbs dot dk by 9 January 2022.

Fully-funded PhD position available at Copenhagen Business School: Artificial Intelligence, Learning and Skills

Expressions of Interest are invited for a fully-funded PhD position at Copenhagen Business School focused on the following topic: Understanding learning and skill development practices in AI-mediated online platform work

Principal Supervisor: Professor Anoush Margaryan

Description

This PhD opportunity is based within the Learning Practices in the Platform Economy (LeaP) research programme, led by Professor Anoush Margaryan.  LeaP is an interdisciplinary, international and cross-sectoral programme focused on advancing the understanding, conceptualisation, methodology and policy of learning practices in the platform economy, particularly location-independent online platform work and other, emergent forms of work mediated by artificial intelligence (AI) technologies. The aim of the LeAP programme is to identify, collect, analyse and systematise empirical evidence to improve our understanding of workplace learning practices within these emergent and hitherto under-theorised forms of work and to develop new approaches that foster the development of skills, dispositions and mindsets required to function productively in such workplaces. The LeaP research programme is driven by real-world interdisciplinary problems of global importance such as understanding and shaping the impact of digitisation and automation on individual and organisational learning practices; fostering learning, development, productivity, growth and well-being in contemporary workplaces; and empowering individuals to take control of their own learning and development in order to succeed in the future of work.

The PhD position will contribute to the following LeaP research strand: 

Artificial Intelligence, skills and work: The development and embedding of artificial intelligence (AI) in workplaces – across the conventional and the platform economies – is transforming the nature of work and skills. The implications of the emergent AI-mediated work practices for workers’ learning and skill enhancement are not well-understood. This strand of research addresses this gap by analysing the opportunities and challenges of emerging AI systems for work practices and skill requirements for different groups of workers interacting with the AI, such as AI developers, AI trainers, and AI end-users.

Key research questions addressed in this strand are:

• What are the opportunities and challenges of emerging AI systems for learning processes within workplaces?

• What skills are necessitated by the introduction of AI technologies in workplaces

• How do workers presently acquire and could acquire these skills in the future, in particular using what learning activities and behavioural strategies?

• What innovative methodologies can be used to help us surface and analyse workers’ learning behaviour  within AI-based systems in the workplace?

For this PhD position, the focus is on location-independent work in microwork platforms. Microwork platforms are Internet-based online labour marketplaces that bring together a large number of workers from across the world to carry out small tasks (micro-units of work, hence microwork) for pay. The microwork platforms use AI algorithms to disaggregate large datasets submitted by clients into micro-tasks that can be outsourced to microworkers, to quality control the workers’ outputs, to oversee the submission and payment for the work done, and to aggregate the outputs again to be returned to the client. Since their inception over a decade ago, microwork platforms have been used for processing big datasets related to digitalization of archives and marketing, but recently there has been a surge in the use of microwork platforms to process big datasets for training machine learning algorithms underpinning AI applications (Schmidt, 2019; Tubaro and Cassili, 2019). Microworkers engaged in these platforms are preparing, categorising and qualifying data for AI applications, assessing the performance of these algorithms, and making corrections if necessary (Le Ludec et al., 2019; Porter et al., 2017; Schmidt, 2019). Therefore, microworkers represent a unique case in that they are both working in AI-enabled workplaces whilst at the same time participating in the production and training of AI algorithms.  

Combining research methods, frameworks and latest research insights from Learning Sciences, Sociology, Psychology, Platform Studies, Data Science and other relevant disciplines and fields these PhD will provide further understanding of learning and skill development practices in microwork.  The specifics of the project will be further defined in collaboration with the suitable PhD candidate.

Further information and person specification

This is a 3-year PhD fellowship fully funded by Copenhagen Business School.

This is a salaried position (‘Ph.d.-stipendiat’ grades 4-8, DKK 35.565-42.905 gross per annum).

The PhD is interdisciplinary in nature and as such would suit applicants from a range of backgrounds, including, but not limited to, Learning Sciences/Workplace Learning; Psychology; Sociology; Web Science/Data Science; Business and Organisational Studies.

Academic training in social/behavioural sciences is an essential pre-requisite for this position.

Whilst we welcome applicants from a range of disciplines, we expect candidates to have strong interest in research questions focused on uncovering fundamental processes of how individuals learn in the workplace and motivation in developing an academic profile in learning sciences.    

We would particularly welcome applicants who are interested in mixed-method research.  

The full application package including an initial PhD proposal will be developed jointly with the shortlisted candidate.

Expression of Interest/Informal enquiries

Informal enquiries may be addressed to the principal supervisor Professor Anoush Margaryan

Expressions of interest should include:

1. Your full CV including a list of your academic publications if any
2. A max 1 page motivation letter explaining your interest in this post and specifying how your profile aligns with the person specification above
3. A sample of your academic writing in English, sole-authored (e.g. your Master’s thesis) 

Please email your applications as one single PDF file attachment, putting “LeaP PhD Expression of Interest” as the subject line to ama.digi@cbs.dk by 31 March 2021. 

Do not send documents/materials other than those listed in 1-3 above please.

Research Assistant (fixed-term) post available at Copenhagen Business School

Job title: Research Assistant
Institution: Copenhagen Business School
Department: Digitalization (DIGI)
Division: Learning in the Platform Economy (LeaP) Research Programme
Location: The post can be undertaken remotely
Grade and salary: ‘Videnskabelig Assistent’ Grade 4 (Appointment and salary are subject to regulation by the Danish Ministry of Finance)
Hours and contract type: Full time (37.5 hours per week) fixed-term for 4 months preferred; alternatively part time (2 days/15 hours per week) fixed-term for 9 months negotiable
Start date: Negotiable
Reporting to: Professor Anoush Margaryan

Note: A right to work in the EU is necessary to be eligible for this post; we are not able to offer visa sponsorship for this position.

Overview of the role

A Research Assistant is sought to work with Professor Anoush Margaryan at Copenhagen Business School’s Department of Digitalization to provide assistantship on a range of ongoing and planned research projects within the LeaP research programme.

The post-holder’s main responsibilities are: contributing to the writing of journal publications; analysing quantitative and qualitative data (primarily questionnaire surveys and interviews); undertaking literature search/reviews and other desk research; supporting Professor Margaryan in grant writing. Other responsibilities include occasional research admin support and providing support and advice to other members of the group as required.

This position would suit a current PhD fellow, a recent PhD graduate or an advanced graduate student with proven ability to write academic texts in English suitable for publication in peer-reviewed international journals; advanced skills in analysing quantitative data and experience of analysing qualitative data; and training in/proven experience of research in the social sciences.

 

Responsibilities/duties

• Contribute to writing journal publications
• Analyse quantitative and qualitative data (survey and interviews)
• Undertake systematic literature reviews/search and write up the results for publication in peer-reviewed journals and project reports
• Gather and analyse additional quantitative and/or qualitative data as may be required
• Contribute to grant writing
• Contribute to planning and day-to-day administration of the research projects
• Manage own research and administrative activities in line with agreed targets and timelines
• Contribute to discussions and share data and research findings with colleagues in partner institutions and collaborating research groups

  

Selection criteria

Essential criteria:

• A first degree in one of the following disciplines/fields: learning sciences/workplace learning, work/educational psychology, sociology, business and organisation studies, or another relevant social science discipline
• Ability to write academic texts in English suitable for publication in international peer-reviewed journals
• Advanced skills in analysing quantitative data
• Experience of analysing qualitative data
• Academic training in/experience of research in the social sciences
• Proven ability to work both independently and under supervision; in an organised and structured, fast and output-oriented manner; manage own tasks within agreed targets and deadlines
• Strong remote working and communication skills
• Excellent spoken and written English

Desirable criteria:

• Experience researching online platform work, crowdwork and AI-mediated work
• Knowledge of literatures on adult/workplace learning, digital transformation of work and society
• Training in the learning sciences
• Grant writing experience

 

How to apply

Applications should include the following documents:

1. Your full CV including a list of your academic publications and grants if any
2. A max 2 page cover letter explaining your interest in this post and specifying how your profile aligns with the essential and desirable criteria
3. A sample of your sole-authored academic writing in English (e.g. a journal article, PhD proposal/Master’s thesis, or a research report)

Please email your applications as one single PDF file attachment, putting “LeaP RA application” as the subject line to ama.digi@cbs.dk by 31 July 2020.

 

Fully-funded PhD position available at Copenhagen Business School, Department of Digitalisation

Expressions of Interest Invited

Understanding Learning and Skill Development Practices in AI-mediated Workplaces

Principal Supervisor: Professor Anoush Margaryan

 

Description

This PhD opportunity is based within the Learning Practices in the Platform Economy (LeaP) research programme, led by Professor Anoush Margaryan.  LeaP is an interdisciplinary, international and cross-sectoral programme focused on advancing the understanding, conceptualisation, methodology and policy of learning practices in the platform economy, particularly location-independent crowdwork and other forms of AI-mediated work. The aim of the LeAP programme is to identify, collect, analyse and systematise empirical evidence to improve our understanding of workplace learning practices within these emergent and hitherto under-theorised forms of work and to develop new approaches to teaching and learning that foster the skills, dispositions and mindsets required to function productively in such workplaces. Opportunities for workplace learning and continuous professional development are essential to workers’ productivity and well-being. Crowdwork and AI-mediated labour are growing types of work in both developed and developing countries. Therefore, it is important to understand how workers function within these types of work, what the learning potential of these new work forms is, what are the gaps and issues and how these might be addressed.  The LeaP research programme is driven by real-world interdisciplinary problems of global importance such as understanding and shaping the impact of digitisation and automation on individual and organisational learning practices; fostering learning, development, productivity, growth and well-being in contemporary workplaces; and empowering individuals to take control of their own learning and development in order to succeed in the future of work.

The PhD position will contribute to the following LeaP research strand:

Artificial Intelligence, skills and work

The development and embedding of artificial intelligence (AI) in workplaces – across the conventional and the platform economies – is transforming the nature of work and skills. The implications of the emergent AI-based work practices for workers’ learning and skill enhancement are not well-understood. This strand of research addresses this gap by analysing the opportunities and challenges of emerging AI systems for work practices and skill requirements for different groups of workers interacting with the AI, such as AI developers, AI trainers, and AI users.

Key research questions addressed in this strand are:

• What are the opportunities and challenges of emerging AI systems for learning processes within workplaces?
• What skills are necessitated by the introduction of AI technologies in the workplaces and how do workers presently acquire and could acquire these skills in the future?
• What effective and innovative methodologies can be used to help us surface and analyse workers’ learning behaviour – their on-the job learning activities and behavioural and metacognitive learning strategies – within AI-based systems in the workplace?

Of particular interest for this PhD position is location-independent work in microwork platforms. Microwork platforms are Internet-based online labour marketplaces that bring together a large number of workers from across the world to carry out small tasks (micro-units of work, hence microwork) for pay. The microwork platforms use AI algorithms to disaggregate large datasets submitted by clients into micro-tasks that can be outsourced to microworkers, to quality control the workers’ outputs, to oversee the submission and payment for the work done, and to aggregate the outputs again to be returned to the client. Since their inception over a decade ago, microwork platforms have been used for processing big datasets related to digitalization of archives and marketing, but recently there has been a surge in the use of microwork platforms to process big datasets for training machine learning algorithms underpinning AI applications (Schmidt, 2019; Tubaro and Cassili, 2019). Microworkers engaged in these platforms are preparing, categorising and qualifying data for the AI applications, assessing the performance of these algorithms, and making corrections if necessary (Le Ludec et al., 2019; Porter et al., 2017; Schmidt, 2019). Therefore, microworkers are both working in AI-enabled workplaces at the same time participating in the production and training of AI algorithms.

Combining research methods, frameworks and latest research insights from Learning Sciences, Sociology, Psychology, Data Science and other relevant disciplines and fields these PhD will provide further understanding of learning and skill development practices in microwork.  The specifics of the project will be formulated in collaboration with the suitable PhD candidate.

 
Further information and person specification

This is a 3-year PhD fellowship fully funded by Copenhagen Business School.

The PhD is interdisciplinary in nature and as such would suit applicants from a range of backgrounds, including, but not limited to, Learning Sciences/Workplace Learning; Psychology; Sociology; Web Science/Data Science; Business and Organisational Studies.

We would particularly welcome applicants who have strong quantitative skills and are interested in mixed-method research.

The full application package including an initial PhD proposal will be developed jointly with a suitable candidate.

Informal enquiries

Informal enquiries may be addressed to the principal supervisor Professor Anoush Margaryan ama.digi@cbs.dk Please send your full CV alongside your informal enquiry.

Expression of Interest

Expressions of interest should include:

1. Your full CV including academic publications and grants if any
2. A max 1 page motivation letter explaining your interest in this post and specifying how your profile aligns with the post
3. A sample of your academic writing in English, preferably sole-authored

Please email your Expressions of Interest as one single PDF file attachment, putting “LeaP PhD Expression of Interest” as the subject line to ama.digi@cbs.dk by 31 July 2020.

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.

 

Introduction

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, bsp.digi@cbs.dk 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 ama.digi@cbs.dk

 

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.

 

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

Call for expressions of interest for Marie Curie Individual Fellowship in “Implementation of Artificial Intelligence and Digitisation in workplaces in relation to the redesign of jobs and the creation of new job”

University College London, Institute of Education – Department of Education, Practice and Society

Location: London

Salary: basic salary £32,548.00 gross per annum (Grade 7, Spinal point 30), plus London allowance £3,031.00 per annum and top up allowance ranging from £8,750.00-£20,000.00 depending on pension contributions and dependants.

Hours: Full time

Contract type: Fixed term

Closing date for Expressions of Interest: 6 August 2018

Closing date for submission of applications: 12 September 2018

 

 The Fellowship

The Marie Sklodowka Curie Individual Fellowships (MCIF) are prestigious fellowships funded by the European Commission. They offer a generous allowance for 1-3 years 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 the UK for more than 12 months in the 3 years immediately prior to the MCIF deadline on 12 September 2018. The MSCA have a bottom-up approach, i.e. research fields and topics are chosen freely by the applicants.

 

Introduction

The Department of Education, Practice and Society (EPS) at the University College London (UCL) Institute of Education (IoE) welcomes expressions of interest from postdoctoral researchers with an excellent track record of research and publication to apply jointly with a supervisor from EPS/IoE to the European Commission Marie Sklodowska-Curie Individual Fellowship Scheme. Selected candidates will receive dedicated support from two or more IoE Professors as well as from EPS peer-review system to develop their proposal and application for submission to the European Commission by 12 September 2018.

The UCL/IoE lead professor is:

• Professor David Guile, Professor of Education and Work and Head of Department of Education, Practice and Society

and, the co-supervisor is:

• Professor Anoush Margaryan, Professor of Learning Science, University of West London and Visiting Professor, UCL Centre for Engineering and Education

 

Research themes

Expressions of Interest that take the following issues as their starting point – the implementation of Artificial Intelligence and Digitisation in workplaces in relation to the redesign of jobs and the creation of new jobs – and are aligned with one of more of the following research themes are welcome:

1. The impact of the implementation of Artificial Intelligence and Digitisation in workplaces on professional formation, including learning
2. Practices and processes of workplace learning and skill development in emergent forms of digital work such as online labour platforms or gig work
3. Policy and practice implications of digitisation and AI for vocational educational, higher education and learning throughout working life
4. Skill development and skill matching in platform workplaces
5. Practices and processes of worker self-organisation and networking for learning and skill development in platform labour

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

 

How to express your interest

Expressions of interest should include:

1. A copy of your CV (including a full list of your publications and research projects)
2. A 2-3 page Research Proposal Summary, which includes details as to which research area(s) from the list above you are interested in
3. A 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 IOE.recruitment@ucl.ac.uk  by Monday 6 August 2018.  

Expressions of interest will be selected on the basis of the quality of the research idea and the candidate’s track record. Candidates will be invited to make a formal application with their EPS/IoE supervisors. Results will be announced on Monday 13^thAugust.

Please note: UCL Research Finance require the successful proposal, with budget, to be submitted to them 5 days before the EU’s MCIF deadline 12^thSeptember. This means the final version of the successful proposal will have to be submitted to Professor Guile and Professor Margaryan on Monday 3^rdSeptember.

For further information please contact Professor David Guile ( d.guile@ucl.ac.uk ) or Professor Anoush Margaryan ( anoush.margaryan@gmail.com ).

Crowdworkers’ motives to take up crowdwork

One of the issues I explored as part of the survey of crowdworkers was their motives to engage in this form of work.

Specifically, the participants were presented with a list of 16 motives synthesised from crowdwork literature and asked to select all motives that applied in their case.  Participants were also given an opportunity to indicate any other motives not included in the list.

Findings (Figure 1) suggest that the key motives are to earn supplementary or main income, with crowdwork tasks considered fun and a fruitful way of spending one’s time while earning money. Also, being their own boss and having control over their own schedule were indicated relatively frequently as reasons to take up crowdwork. Few crowdworkers appear to engage in this form of work due to inability to find or perform traditional work (10% and 4% respectively).

Figure 1. Crowdworkers’ motives to engage in crowdwork (n=182)

Comparing the responses of microworkers and online freelancers (Fig. 2), more online freelancers report crowdwork as their primary source of income corraborating findings from previous studies of crowdwork.

Also, we observe that considerably fewer online freelancers than microworkers report crowdwork tasks being fun as a key motive, but considerably more online freelancers cite being their own boss, having control over their schedule, following their passion, having more choice of the projects they can do, and earning more through crowdwork than they could through traditional work as key reasons to take up crowdwork.

Figure 2. Online freelancers’, OF (n=15) and microworkers’, MW (n=167) motives to engage in crowdwork 

Other motives indicated by the crowdworkers included:

• “As more people use [crowdwork platform] to find people for project work, the network effect almost requires that I use it; it is an important source of work referrals.”
• “Learning skills and gaining work experience”.
• “I just finished my studies and am currently searching for a traditional (part-time) employment in addition to crowdwork, mostly for insurance reasons.”
• “In [my country] the incomes from traditional work are terrible“.
• “It’s best online earning platform I’ve found so far.”

 

Do crowdworkers self-identify as entrepreneurs?

As part of the survey of crowdworkers’ learning practices, I asked the participants about their self-identity as entrepreneurs.

In particular, I asked the crowdworkers if they considered themselves to be entrepreneurs in line with the following definition: “‘Entrepreneur’ means a person who organises and manages their own business exercising considerable personal initiative and taking on financial risk. Entrepreneurs include people who are self-employed, those who are a sole owner, partner or a majority shareholder of a small, medium, or large company”.

The majority of crowdworkers (52%) reported not identifying as entrepreneurs (Figure 1):

Figure 1. Crowdworkers’ reported self-identity as entrepreneurs (n=182)

More online freelancers than microworkers reported self-identifying as entrepreneurs (Figure 2).  Those who selected ‘other’ stated that they weren’t entrepreneurs yet, but were planning to start a business in the future.

Figure 2. Reported entrepreneurial self-identity among microworkers, MW (n=167) and online freelancers, OF (n=15) 

 

Crowdworkers’ use of self-regulated learning strategies

My previous blogposts in the series on crowdworkers’ learning practices are available here, here, here, and here.

One aspect of the surveys of crowdworkers learning practices I’ve been recently conducting has been focused on scoping the range and frequency of use of of self-regulated learning (SRL) strategies undertaken by crowdworkers.

The questionnaire included a sub-scale of 34 items grounded in Zimmerman’s 3-phase model of self-regulated learning scoping crowdworkers’ strategies of planning, implementing and reflecting on their workplace learning.

The initial results from the sample of 167 microworkers and 15 online freelancers are as follows:

• The possible range of SRL scores based on the questionnaire: 0 – 102
• The actual SRL score ranges in this sample are:
  • microworkers: 4-99
  • online freelancers: 10-76
• The sub-groups by SRL score are:
  • low SRL: 0-34
  • medium SRL: 35-70
  • high SRL: 71-102

1. What is the distribution of high, low and medium SRL scores among this sample?

Figure 1. Distribution of SRL scores among the sample of crowdworkers, percentages (n=182, including microworkers (MW) n=167 and online freelancers (OF) n=15).  

The bell curve distribution of SRL scores is in line with our previous surveys among ‘conventional’ knowledge workers.

 

2. What are the most prevalent SRL strategies among crowdworkers across the three phases of Zimmerman’s model?

By ‘most prevalent’ I mean SRL strategies that crowdworkers reported using ‘most of the time’ and ‘always’ (those who reported using a strategy only ‘sometimes’ are excluded from this analysis).

The initial results are shown in Figures 2-4 below.

Overall, we observe that crowdworkers use a wide range of self-regulated learning strategies across all phases, setting and modifying their own learning goals, strategies and performance standards and reflecting on their learning from crowdwork tasks.

Self-efficacy and intrinsic motivation are prevalent among crowdworkers (determined by responses to statements such as ‘important to learn new things in crowdwork tasks’, ‘confident can handle most demands in crowdwork’, prefers tasks that require to learn something new’, ‘meets learning goals’).

Despite the nature of crowdwork tasks that are designed to be completed individually and autonomously, some crowdworkers apply social learning strategies. Examples of social learning strategies are reaching out to others (36% of microworkers and 33% of online freelancers reported doing this most of the time or always); considering how what they have learned from crowdwork may be of interest to their peers (27% of microworkers and 39% of online freelancers do this most of the time or always); or sharing their learning from crowdwork with others (30% of online freelancers and 13% of microworkers).

The patterns of use of SRL strategies are broadly similar across both groups, but there are some differences, most notably:

• More microworkers report regularly allocating time to work on their learning goals (22% of microworkers vs 7% of online freelancers)
• More microworkers report regularly reflecting on their performance on crowdwork tasks (64% of microworkers vs 13% of online freelancers)
• More microworkers report regularly sharing their reflections on their learning with others (20% of microworkers vs 0% of online freelancers)

Further analysis of the data will help determine if these differences are statistically significant and develop possible explanations for the differences.

Figure 2. SRL Planning strategies among crowdworkers 

 

Figure 3. SRL implementation strategies among crowdworkers

 

Figure 4. SRL reflection strategies among crowdworkers