Towards a definition of metaskills
Katherine Stephen, Laura Muir, and Hazel Hall.
Introduction: The term ‘metaskill’ has been used to mean a range of different types of information-based skill. This contribution describes the variation in use across disciplines and industries, and two distinct but related definitions are found.
Method: Two hundred and ten scholarly papers were identified across the fields of psychology, work-based learning, education and information using key word searches. These papers are analysed for inclusion of definitions and examples of ‘metaskills’.
Analysis: Comparisons are made to find similarities and disagreements within both definitions and examples. Excel is used to create word lists, and word clouds used to assess weight and frequency.
Findings: Although some agreement can be found, there is no wide consensus. Two separate but related definitions emerge: that of a shorthand for ‘metacognitive skill’, and a broader ‘higher order’ technical skill type.
Conclusions: Used as a buzzword in work-based learning literature, the idea of ‘metaskills’ seems to be an increasingly important part of lifelong learning. The two definitions that have emerged have some crossover, which may lead to confusion when designing skill development interventions. While formal education environments have traditionally been the source of participants for skill-based research, further work on the development of well-defined metaskills within the workplace is encouraged.
The term metaskill has been used to mean a range of different types of information-based skill. This contribution describes the variation in use across disciplines and industries, and two distinct but related definitions are found. The research questions posed here form the basis of further work on assessing and developing metaskills in the workplace.
- Is there a universal definition of metaskill?
- What are some universally applicable examples of this term?
Significance and relevance of the topic
As our education systems work towards helping people to be ready for the labour market of the future, it is easy to see that key technical skills may be regularly and rapidly superseded by others, thanks to advances in both technology and environmental concerns. Thus, there is importance in understanding the other information-processing skills that tomorrow’s workforce will need to develop. These non-technical abilities have been given many names: generic competences, general skills, soft skills, 21st century skills and metaskills, to name just a few. In order to study the acquisition and development of these non-technical abilities, it is important first to be able to define them and any divisions between them. This definitional work is significant both for the research community and for those people who are building the skills. The study is part of a PhD studentship sponsored by Scotland’s national skills agency, Skills Development Scotland, and so the findings will be relevant to any development frameworks created for workplace learning, as well as having implications for wider education policy.
Introduction: The fourth industrial revolution has increased the likelihood that job tasks will change rapidly, due to factors such as machine automation (Hirschi, 2018). With this rapidity of change comes a need for skills of adaptation, as well as a focus on human capabilities that machines do not currently possess (Autor, 2015). These capabilities are described in various different terms throughout academic literature; one such term is metaskills. This work sets out to investigate current usage of the term metaskills with the aim of defining it for future study.
Methods: Scholarly databases were searched using the keywords metaskills, meta-skills and meta skills. Due to search systems within some databases, this search found results including other terms beginning with meta-. These particular results were discarded if not relevant, but included if judged as similar in meaning, e.g. meta-competences or meta-knowledge. 210 papers published between 1979 and 2019 across domains including psychology, education and information science were found that used one or more of the included terms. A spreadsheet was created to build a list of each paper’s terminology, definitions and examples. Textual analysis was then undertaken to compare usage across papers.
Findings: From the 210 papers, 36 included no definition or example of the term. These included the earliest usage found (Reed and Lave, 1979), as well as papers published as late as 2019 (Yildiz et al., 2019). Of those where explication existed, 103 provided examples. The most common example was learning, with 3 instances; others with more than one instance included communication, creative thinking, innovation and self awareness. 73 papers used a unique example. Of the definitions used, none agreed on phrasing, but broad consensus was found across two levels: papers referred either to competences of general working, such as the ability to communicate knowledge well, to make decisions and to solve problems; or to capacities which enable those competences, such as self-reflection, calibration of one’s own comprehension, and selection of metacognitive strategies. Three papers (Karoly, 1993; Ahonen, 2005; Finch et al., 2013) were referenced in lieu of a rephrased definition.
Conclusions: Without invalidating vast swathes of examples used in existing literature, metaskills can seem to be defined in two primary ways, which are separate but related. First, a shorthand for metacognitive skill – the ability to use introspection to further develop learning, thinking and understanding (cognitive) capabilities. This matches psychological definitions given by Karoly (1993) and Nigg (2017). An example of this might be formulating an appropriate strategy after recognising a context in which one needs to acquire new knowledge. A second definition of metaskills is skills above/beyond skills – higher-order skills that are applicable across domains and disciplines, leading one to improve or accumulate hard skills through having built up a metaskill within one or more other hard skills. For example, information sourcing may be a metaskill using this definition, as it can assist in many work areas beyond where it is first undertaken and can lead to forming new hard skills; oral communication may be another, as it is pertinent in presenting work, asking questions, and working in teams. The most prolific proponents of this definition are Finch et al. (e.g. 2012, 2016).
Next steps: Next steps for the author following this research are empirical work on metaskill measurement and development in the workplace, using the first definition of the term found here. This work will utilise sociological methods such as institutional ethnography, to analyse assessment of these metaskills in Scottish apprenticeship frameworks; intervention studies to investigate conscious metaskill development; and The Imitation Game (Collins et al, 2017) to research newcomer adaptability in workplaces. Additional future research suggestions would centre on workplace development of the second definition of metaskills, as well as further discussion of boundary lines between technical and non-technical skill definitions.
About the authors
Katherine Stephen is a PhD student in the School of Computing at Edinburgh Napier University. She completed a PGDip in Career Guidance and Development at the University of the West of Scotland and an MScRes in Science and Technology Studies at the University of Edinburgh. Her research interests are metaskill development and metacognition within the workplace, tacit knowledge, and lifelong learning. She blogs at www.metaskillsphd.com and she can be contacted at firstname.lastname@example.org.
Dr Laura Muir is an Associate Professor, and Head of the Creative and Social Informatics Subject Group, within the School of Computing at Edinburgh Napier University, Scotland. She completed her PhD (Content prioritised video coding for British Sign Language Communication), and MSc (with Distinction) in Information Systems from Robert Gordon University, Aberdeen. Her research interests include information behaviour and human-centred systems and service. She can be contacted at email@example.com. Her mailing address is School of Computing, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK.
Dr Hazel Hall is Professor of Social Informatics within the School of Computing at Edinburgh Napier University, Scotland and Docent in Information Studies at Åbo Akademi University, Finland. She holds a PhD in Computing from Napier University, an MA in Library and Information Studies from the University of Central England, and a BA (Spec Hons) in French from the University of Birmingham. Her research interests include information sharing in online environments, knowledge management, social computing/media, online communities and collaboration, library and information science research, and research impact. She blogs at http://hazelhall.org and can be contacted at firstname.lastname@example.org. Her mailing address is School of Computing, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK.
- Ahonen, T. (2005). Generic Features of Special Education Need Methodologies. Special Educational Needs in Europe. The Teaching and Learning of Languages. Insights and Innovation. Teaching Languages to Learners with Special Needs. European Commission, 63-75. http://tictc.cti.gr/documents/doc647_en.pdf
- Autor, D.H. (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives, 29(3), 3–30. http://dx.doi.org/10.1257/jep.29.3.3
- Collins, H., Evans, R., Weinel, M., Lyttleton-Smith, J., Bartlett, A., & Hall, M. (2017). The Imitation Game and the Nature of Mixed Methods. Journal of Mixed Methods Research, 11(4), 510–527. https://doi.org/10.1177/1558689815619824
- Finch, D. J., Hamilton, L. K., Baldwin, R., & Zehner, M. (2013). An exploratory study of factors affecting undergraduate employability. Education & Training, 55(7), 681-704. http://dx.doi.org/10.1108/ET-07-2012-0077
- Finch, D., Nadeau, J. & O'Reilly, N. (2012). The future of marketing education: a practitioner’s perspective. Journal of Marketing Education, 35(1), 54-67. http://dx.doi.org/10.1177/0273475312465091
- Finch, D., Peacock, M., Levallet, N. & Foster, W. (2016). A dynamic capabilities view of employability. Education + Training, 58(1), 61-81. http://dx.doi.org/10.1108/ET-02-2015-0013
- Hirschi, A. (2018). The Fourth Industrial Revolution: Issues and Implications for Career Research and Practice. The Career Development Quarterly, 66(3), 192–204. http://dx.doi.org/10.1002/cdq.12142
- Karoly, P. (1993). Mechanisms of self-regulation: a systems view. Annual Review of Psychology, 44(1), 23-52. http://dx.doi.org/10.1146/annurev.ps.44.020193.000323
- Nigg, J. (2017). Annual research review: on the relations among self‐regulation, self‐control, executive functioning, effortful control, cognitive control, impulsivity, risk‐taking, and inhibition for developmental psychopathology. Journal of Child Psychology and Psychiatry, 58(4), 361-383. http://dx.doi.org/10.1111/jcpp.12675
- Reed, H. J., & Lave, J. (1979). Arithmetic as a tool for investigating relations between culture and cognition. American Ethnologist, 6(3), 568-582.
- Yildiz, H. E., Murtic, A., Zander, U., & Richtner, A. (2019). What Fosters Individual-Level Absorptive Capacity in MNCs? An Extended Motivation—Ability—Opportunity Framework. Management International Review, 59(1), 93+. http://dx.doi.org/10.1007/s11575-018-0367-x