We live in an era where digital is the new normal: our devices are quickly becoming part of the internet of things (Wortmann and Flüchter, 2015); our communication has for some time taken place through social media platforms; email, of course, is now ubiquitous; and our data systems and repositories are becoming increasingly interoperable (Shiohira and DaleJones, forthcoming).
Our access to learning opportunities has also been expanding at pace. The open education movement, which has mirrored societal trends towards increased openness in developed countries (Vincent-Lancrin, 2016; Stella and Gnanam, 2004), has impacted hugely on how we think about education in the modern world and also in less developed parts of the globe. Massive open online courses (MOOCs) are now widespread (Music, 2016; Commonwealth of Learning, 2016), so too small private online courses (SPOCs) (De Leeuw, 2017), and in recent years, the more encompassing notion of digital credentials (Keevy and Chakroun, 2018). thumbnail_large.jpg
This is the era in which artificial intelligence (AI) has become more prevalent and is increasingly replacing mid-level skills across both the developed and developing worlds (Majumdar et al., forthcoming). This is also the era in which data privacy is becoming more regulated and the ability of the individual to own his or her own data a reality through technologies such as blockchain (Verbert, Sharples and Klobucar, 2016).
In this new normal, we have to consider how learning, delivered through multiple platforms and modes, can be credible, authentic and transferable. Traditional forms of quality assurance, many of which are closely linked to the pervasive development of national and regional qualifications frameworks across most parts of the globe, have played a key role for the last 30 or more years (Allais, 2010; Allais, 2017; Allais, Raffe and Young, 2009; Allais et al, 2009; Braňka, 2016; International Labour Office, 2017; McGrath, 1997; Raffe, 2009), drawing on many decades of models and systems that preceded qualifications frameworks.
These forms of quality assurance share some common characteristics: a longstanding emphasis on the divide between formal, nonformal and informal learning (OECD, 2016a; 2016b); linked to this, a strong emphasis on the value of formal learning, sometimes at the expense of non-formal and informal learning, further evidenced through the development of recognition of prior learning (RPL) systems internationally (Werqu, 2010); external validation by independent quality assurance bodies; and also strong government control and sanctioning of quality measures in most parts of the world (Keevy and Chakroun, 2018).
This is the conundrum of the new normal. The very nature of learning is changing at a breakneck pace, while the systems we use to quality assure the learning are slow to adapt, slow to provide new proxies for what types of learning has value and even slower in their ability to shift the ownership of data to where it belongs, the individual (Shiohira and DaleJones forthcoming). There are exceptions, notably the move towards a credential framework in the United States (Keevy et al, 2019, Lumina Foundation, 2015 and 2016) and the introduction of more detailed programme monitoring which unlinks the quality assurance of the institution providing the learning from the quality assurance of the curriculum and of the delivery of the learning (Klinkum, 2018).
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