Get in touch if you’d like a pre-print copy.
Abstract: This paper outlines a research and development agenda for the nascent field of Learning from Incidents (LFI). Effective, deep and lasting learning from incidents is critical for the safety of employees, the general public and environmental protection. The paper is an output of an international seminar series ‘Interdisciplinary Perspectives on Learning from Incidents’ funded by the UK Economic and Social Research Council (ESRC) in 2013-2016 http://lfiseminars.ning.com/ The seminar series brought together academics, practitioners and policymakers from a range of disciplines and sectors to advance the theory, methodology, organisational practice and policy in LFI. Drawing on a range of disciplinary and sectoral perspectives, as well as on input from practitioners and policymakers, this paper lays out four key research and development challenges: defining LFI; measuring LFI; levels and factors of LFI; and strengthening research-practice nexus in LFI.
Reference (incomplete): Margaryan, A., Littlejohn, A., & Stanton, N. (in press). Research and development agenda for Learning from Incidents. Safety Science.
My paper on crowdworkers’ learning within microwork and online freelancing platforms has been accepted at Internet, Policy and Politics 2016 Conference organised by Oxford Internet Institute. I’m very much looking forward to the conference.
This paper reports findings of a survey exploring how crowdworkers develop their knowledge and skills in the course of their work on digital platforms. The focus is on informal learning initiated and self-regulated by crowdworkers: engaging in challenging tasks; studying professional literature/online resources; sharing knowledge and collaborating with others. The survey was run within two platforms representing two types of crowdwork – microwork (CrowdFlower) and online freelancing (Upwork). The survey uncovered evidence for considerable individual and social learning activity within both types of crowdwork. Findings suggest that both microwork and online freelancing are learning-intensive and both groups of workers are learning-oriented and self-regulated. Crowdwork is a growing form of employment in developed and developing countries. Improved understanding of learning practices within crowdwork would inform the design of crowdwork platforms; empower crowdworkers to direct their own learning and work; and help platforms, employers, and policymakers enhance the learning potential of crowdwork.
Reference: Margaryan, A. (22 September, 2016). Understanding crowdworkers’ learning practices. Paper presented at Internet, Policy and Politics 2016 Conference, Oxford Internet Institute, University of Oxford, UK. [Online] http://ipp.oii.ox.ac.uk/sites/ipp/files/documents/FullPaper-CrowdworkerLearning-MargaryanForIPP-100816%281%29.pdf
I admire Marissa Mayer and always enjoy hearing her interviews and talks. I admire her for her brightness, work ethic, the combination of shyness and confidence, of geekiness and femininity, and for her professional achievements.
I listened to an interview she gave at Cleveland Clinic Ideas for Tomorrow event earlier this year. In this interview she talks about her work at Yahoo and Google, her career choices and the rationale underpinning these. She concludes by outlining the lessons she has learned. Here is a summary of career lessons from Marissa Mayer:
- Often there is not a good or a right choice, but there are many good choices – it’s about picking well and then committing to it.
- Surround yourself with the smartest people you can to challenge you and push you to the next level.
- Go for things you are not yet ready to do – you will either learn that you are better than you thought or that you fall short of where you want to be – both outcomes are a huge learning opportunity.
- When choosing a job, go for an environment you’re comfortable in – you want to be somewhere where you are surrounded by like-minded people, where you can realise your full potential, where you can have your voice, where you can influence. It may seem that this point contradicts 2 and 3 above but it doesn’t – what Mayer is talking about here is not seeking a non-challenging environment but one where there is a mutual cultural and value fit between you and the organisation. The metaphor she used to explain this is: ‘when doing sports you should really push yourself, but wear comfortable clothes’.
- And the most important advice in my view – Work somewhere where there is someone in the leadership who will believe in you and who will invest in you so that you can take your work to the next level and learn something new constantly.
Updated on 5 January 2016:
The timeline for our Safety Science special issue on Learning from Incidents has been extended as follows:
Papers are due by 31 March 2016. Further details and instructions are below.
Do let us know if you are interested in submitting a paper. Help in circulating this call would be much appreciated. We look forward to receiving submissions.
Call for papers: Special issue of Safety Science on Learning from Incidents
The ability to learn from incidents it essential for safety in all organisations, industries, regulatory bodies and policy makers. Safety Science has a long history of innovations in theory, methodology, science and application. For example, accident causation models that first emerged in the early 1900s have since evolved to consider entire systems and emergent properties (e.g. Heinrich, 1931; Leveson, 2004; Perrow, 1984; Rasmussen, 1997; Reason, 1990). Similarly, methodologies have moved from focussing on tasks (Taylor, 1911) to entire systems and the constraints shaping behaviour (e.g. Vicente, 1999). However Learning from Incidents is yet to embrace theories and methods from the learning sciences. A new repertoire of theories, methods and instruments evolved from interdisciplinary perspectives is needed to learn from incidents effectively.
The aim of this special issue is to provide researchers and practitioners with an opportunity to present and discuss contemporary, forecasted, and required paradigm shifts to learn from incidents. We welcome submissions from all disciplines, including, but not restricted to: Adult and Organisational Learning, Computer Science, Engineering, Sociology, Industrial Psychology, Human Factors Engineering.
Manuscripts from any domain are welcomed on:
- Reviews of state of the art of LfI;
- Whole of systems approaches to LfI;
- New methodologies for researching LfI;
- New instruments for measuring LfI;
- Inter-disciplinary insights into LfI;
- Case studies involving new concepts to LfI;
- Commentaries on LfI and the future for the Safety Science discipline
- Reports on intervention studies into improving LfI
- Approaches to facilitating and enhancing interactions between researchers, practitioners and policymakers in LfI
Timeline (updated on 5 January 2016)
Instructions for authors
The deadline for receipt of papers is 1st February 2016, with a projected publication date of mid 2017. All papers will be subjected to the standard peer-review procedures of the journal. Potential authors are requested to submit their paper for consideration to Professor Neville Stanton (firstname.lastname@example.org), Dr Anoush Margaryan (email@example.com), Professor Allison Littlejohn (Allison.firstname.lastname@example.org) prior to electronic submission so that the Guest Editors can ensure its scope and quality is suitable for the special issue.
Following approval, papers should be submitted online via the Elsevier Safety Science manuscript submission site . When specifying ‘Article Type’ authors should select ‘SI: Learning from Incidents”. Failure to do so will cause the papers to go unrecognised as belonging to the special issue.
Guidelines for authors can also be found on the Safety Science website.
I was pleased to find out this morning that several papers I have co-authored achieved high ranking in the recent update of Google Scholar citation metrics:
- The most cited paper in the journal Computers and Education (the top journal in Google Scholar Educational Technology category) in the last 5 years: Margaryan, A., Littlejohn, A., & Vojt. G. (2011). Are digital natives a myth or reality? University students’ use of digital technologies. Computers and Education, 56(2), 429-440.
- The second most cited paper in the Journal of Online Teaching and Learning (no 20 in Educational Technology category) in the past 5 years: Milligan, C., Littlejohn, A., & Margaryan, A. (2013). Patterns of engagement in connectivist MOOCs. Journal of Online Learning and Teaching, 9(2).
- The fifth most cited paper in the Journal of Workplace Learning (no 17 in Google Scholar) in the past 5 years: Littlejohn, A., Milligan, C., & Margaryan, A. (2012). Collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24(3), 226-238.
Thanks to Colin Milligan for pointing this out to me.
Pleased to find out that my abstract ‘Reconceptualising professional learning within emergent digitally-mediated work practices’ has been accepted for the forthcoming symposium of the Dynamics of Virtual Work research network.
Abstract: In many domains work has become increasingly complex, reliant on expertise distributed across a range of specialisms and involving novel problems at the boundaries of human knowledge (Boisot et al, 2011). In parallel, the unfolding digital transformation of work is catalysing new formations and constellations in the workplace that challenge traditional patterns of individual agency, organisation, power, responsibility and learning (Littlejohn and Margaryan, 2013). New forms of organisation mediated by digital technology include crowdwork, networked science, nomadic work and other types of distributed work (Bietz, 2013; Nickerson, 2013; Nielsen, 2012). These developments are having a profound effect on society and work, but are yet to have a significant effect on how professional learning is conceptualised and organised. Contemporary work practices require new forms of professional learning that align with the new spatial and temporal reconfigurations of workplaces, new work cultures, new networks of knowledge, and new requirements pertaining to the development and use of digital technologies. Conventional forms of professional learning such as formal training enable large numbers of people to reach a specific level of competency; however these forms of learning are unlikely to meet the learning needs of people in these new work contexts. Established forms of professional learning have largely not taken advantages of the opportunities around how people collaborate to learn, emergent knowledge networks, multiple ways in which people and knowledge resources can be brought together to enhance learning, and how digital technologies can extend access to these learning opportunities and resources. A fundamental rethink of how professional learning aligns with current trends in work, technology and society is required. In this presentation, I will discuss key implications of digital reinstrumentation and the emergent work practices for professional learning. Drawing on four concepts from learning sciences, sociology of work and technology-enhanced learning – self-regulation (Zimmerman, 2006), objectual practice (Knorr-Cetina, 2001), networked learning (Milligan, Littlejohn and Margaryan, 2014) and charting (Littlejohn, Milligan, and Margaryan, 2012) – I will outline some ways in which learning within emergent digitally-mediated work practices may be reconceptualised and fostered.
Bietz, M. (2013). Distributed work: Working and learning at a distance. In Littlejohn, A., & Margaryan, A. (Eds.). Technology-enhanced professional learning: Processes, practices and tools (pp. 28-38). London: Routledge.
Boisot, M., Norberg, M., Yami, S., & Nicquevert, B. (2011) (Eds.) Collisions and collaboration: The organisation of learning in the Atlas Experiment at the LHC. Oxford: Oxford University Press.
Knorr-Cetina, K. (2001). Objectual practice. In Schatzki, T., Knorr-Cetina, K., & Savigny, E. (Eds), The practice turn in contemporary theory (pp. 175-188). London: Routledge.
Littlejohn, A., & Margaryan, A. (2013) (Eds.). Technology-enhanced professional learning: Processes, practices and tools. London: Routledge.
Littlejohn, A., Milligan, C., & Margaryan, A. (2012). Collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24(3), 226-238.
Milligan, C., Margaryan, A., & Littlejohn, A. (2014). Workplace learning in informal networks. Journal of Interactive Media Environments, special issue ‘Reusing Resources – Open for Learning. [Online] file:///Users/ama11/Downloads/325-2585-1-PB%20(2).pdf
Nickerson, J. (2013). Crowd work and collective learning. In Littlejohn, A., & Margaryan, A. (Eds.). Technology-enhanced professional learning: Processes, practices and tools (pp. 39-49). London: Routledge.
Nielsen, M. (2012). Reinventing discovery: The new era of networked science. Princeton: Princeton University Press.
Zimmerman, B. (2006). Development and adaptation of expertise: The role of self-regulatory processes and beliefs. In Ericsson, A., Charness, N., Feltovich, P., & Hoffman, R. (Eds.), The Cambridge handbook of expertise and expert performance (pp. 705-722). New York: Cambridge University Press.
Our paper (with Allison Littlejohn and Dane Lukic ) ‘Comparing safety culture and learning culture‘ has been accepted for publication in Risk Management journal (Risk Management (2015) doi:10.1057/rm.2015.2).
Extended abstract: This article examines the alignment of learning and safety culture in organisations. It tests the hypothesis that factors that indicate a good learning culture might also signify good safety and vice versa. The hypothesis was tested through an extensive literature review. Areas of alignment of learning culture and safety culture were identified. Six components of learning culture and safety culture can be measured by the same instrument. These components form guiding principles for measurement of safety culture and learning culture: open communication; employee empowerment; collaboration; alignment of espoused and enacted priorities; internal systemic alignment; management. Another eight component areas were identified where learning culture and safety culture partially align: motivation; recognition and rewards; competence; commitment; workplace condition; risk; opportunities for learning; and policy and procedures. Four further components were found to be relevant to either safety culture or learning culture and do not align: social regulation; safety versus productivity; equipment; and innovation. Overall, there is a relationship between learning culture and safety culture, but gauging one does not provide a reliable measure of the other.