Youth digital participation:Measuring social impact

Current scholarly debate around digital participatory youth projects and approaches to their evaluation are examined in this article. The analysis of the literature presented here reveals (1) an over-reliance on traditional evaluation techniques for such initiatives, and (2) a scarcity of models for the assessment of the social impact of digital participatory youth projects. It is concluded that the challenges and limitations of social impact evaluation practice in digital participatory youth projects should be addressed through the adoption of alternative, participant-centred approaches. These issues are discussed in reference to a current ongoing study that seeks to identify solutions for enhancing social impact evaluations of participatory digital initiatives by young people.<br/

Youth digital participation: Measuring social impact

Current scholarly debate around digital participatory youth projects and approaches to their evaluation are examined in this article. The analysis of the literature presented here reveals (1) an over-reliance on traditional evaluation techniques for such initiatives, and (2) a scarcity of models for the assessment of the social impact of digital participatory youth projects. It is concluded that the challenges and limitations of social impact evaluation practice in digital participatory youth projects should be addressed through the adoption of alternative, participant-centred approaches. These issues are discussed in reference to a current ongoing study that seeks to identify solutions for enhancing social impact evaluations of participatory digital initiatives by young people

The Social Impact of Digital Youth Work: What Are We Looking For?

Digital youth work is an emerging field of research and practice which seeks to investigate and support youth-centred digital literacy initiatives. Whilst digital youth work projects have become prominent in Europe in recent years, it has also become increasingly difficult to examine, capture, and understand their social impact. Currently, there is limited understanding of and research on how to measure the social impact of collaborative digital literacy youth projects. This article presents empirical research which explores the ways digital youth workers perceive and evaluate the social impact of their work. Twenty semi-structured interviews were carried out in Scotland, United Kingdom, in 2017. All data were coded in NVivo 10 and analysed using thematic data analysis (Braun & Clarke, 2006). Two problems were identified in this study: (1) limited critical engagement with the social impact evaluation process of digital youth work projects and its outcomes, and (2) lack of consistent definition of the evaluation process to measure the social impact/value of digital youth work. Results of the study are examined within a wider scholarly discourse on the evaluation of youth digital participation, digital literacy, and social impact. It is argued that to progressively work towards a deeper understanding of the social value (positive and negative) of digital youth engagement and their digital literacy needs, further research and youth worker evaluation training are required. Recommendations towards these future changes in practice are also addressed

Young innovators in the digital era. In: The guide to the tools for research of youth in the migrant communities

No abstract available

Me and My Big Data: Understanding Citizens Data Literacies Research Report

No abstract available

Who are the limited users of digital systems and media? An examination of U.K. evidence

This paper presents findings on the correspondence of levels of digital systems and media use with a range of socio-economic and demographic measures in the U.K. Most research on inequalities in regard to digital systems and media has focused on access and skills. Building on prior work (Yates and Lockley, 2018; Yates, et al., 2015) we argue that inequalities in regard to digital systems and media are better understood around types of user and their correspondence to other key social variables — rather than solely individual skills and access. The analysis presented here covers a range of key demographic variables, especially those that are markers of distinct social disadvantage. We find that those not using the Internet have distinct characteristics — predominantly around age, education and deprivation levels. We also find that those undertaking limited uses (overall limited use or a very narrow range of uses) are all predominantly from lower socio-economic status backgrounds with variations due to age and education. The data used for the analysis is the recent U.K. Ofcom 2018–19 (n = 1,882) media literacy survey. The paper uses latent class analysis methods to inductively define user types. Multinomial and binary logistic regression are used to explore the correspondence of latent class group membership to key demographic variables. These insights have direct U.K. and international policy relevance as they are key to the development of strategies to tackle ongoing digital inequalities in U.K. society