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.
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 was pleased to hear that our paper on the quality of instructional design of massive open online courses (MOOCs) has been accepted for publication in Computers and Education.
Abstract: We present an analysis of instructional design quality of 76 randomly selected Massive Open Online Courses (MOOCs). The quality of MOOCs was determined from first principles of instruction, using a course survey instrument. Two types of MOOCs – xMOOCs and cMOOCs – were analysed and their instructional design quality was assessed and compared. We found that the majority of MOOCs scored poorly on most instructional design principles. However, most MOOCs scored highly on organisation and presentation of course material. The results indicate that although most MOOCs are well-packaged, their instructional design quality is low. We outline implications for practice and ideas for future research.
It took 18 months to get to this stage from the conception of the study:
conception of the project idea and securing internal funding for a research assistant – Feb 2013;
search and recruitment of a research assistant – Feb-Jul 2013 (6 months);
data collection – Sep-Dec 2013 (4 months);
data analysis – Jan 2014;
publication – Feb-Aug 2014 (7 months), including: (i)submission of the first draft of the article – Feb 2014; (ii) review received – Apr 2014; (iii) resubmission of 2nd draft – May 2014; (iv)second review received – Jul 2014; (v) resubmission and acceptance of the final draft – Aug 2014.
So the actual conception and execution of the study took just 6/18 months…
Citation: Margaryan, A., Bianco, M., & Littlejohn, A. (in press). Instructional quality of Massive Open Online Courses (MOOCs). Computers and Education.
This paper outlines the findings of a study investigating the extent and nature of use of digital technologies by undergraduate students in Social Work and Engineering, in two British universities.The study involved a questionnaire survey of students (n=160) followed by in-depth interviews with students, lecturers and support staff in both institutions. Firstly, the findings suggest that students use a limited range of technologies for both learning and socialisation. For learning, mainly established ICTs are used- institutional VLE, Google and Wikipedia and mobile phones. Students make limited, recreational use of social technologies such as media sharing tools and social networking sites.Secondly, the findings point to a low level of use of and familiarity with collaborative knowledge creation tools, virtual worlds, personal web publishing, and other emergent social technologies. Thirdly, the study did not find evidence to support the claims regarding students adopting radically different patterns of knowledge creation and sharing suggested by some previous studies. The study shows that students’ attitudes to learning appear to be influenced by the teaching approaches adopted by their lecturers. Far from demanding lecturers change their practice, students appear to conform to fairly traditional pedagogies, albeit with minor uses of technology tools that deliver content.Despite both groups clearly using a rather limited range of technologies for learning, the results point to some age differences, with younger, engineering students making somewhat more active, albeit limited, use of tools than the older ones. The outcomes suggest that although the calls for radical transformations in educational approaches may be legitimate it would be misleading to ground the arguments for such change solely in students’ shifting expectations and patterns of learning and technology use.