Edtech and sustainability

Last September, Cambridge published a ‘Sustainability Framework for ELT’, which attempts to bring together environmental, social and economic sustainability. It’s a kind of 21^st century skills framework and is designed to help teachers ‘to integrate sustainability skills development’ into their lessons. Among the sub-skills that are listed, a handful grabbed my attention:

• Identifying and understanding obstacles to sustainability
• Broadening discussion and including underrepresented voices
• Understanding observable and hidden consequences
• Critically evaluating sustainability claims
• Understanding the bigger picture

Hoping to brush up my skills in these areas, I decided to take a look at the upcoming BETT show in London, which describes itself as ‘the biggest Education Technology exhibition in the world’. BETT and its parent company, Hyve, ‘are committed to redefining sustainability within the event industry and within education’. They are doing this by reducing their ‘onsite printing and collateral’. (‘Event collateral’ is an interesting event-industry term that refers to all the crap that is put into delegate bags, intended to ‘enhance their experience of the event’.) BETT and Hyve are encouraging all sponsors to go paperless, too, ‘switching from seat-drop collateral to QR codes’, and delegate bags will no longer be offered. They are partnering with various charities to donate ‘surplus food and furniture’ to local community projects, they are donating to other food charities that support families in need, and they are recycling all of the aisle banners into tote bags. Keynote speakers will include people like Sally Uren, CEO of ‘Forum for the Future’, who will talk about ‘Transforming carbon neutral education for a just and regenerative future’.

BETT and Hyve want us to take their corporate and social responsibility very seriously. All of these initiatives are very commendable, even though I wouldn’t go so far as to say that they will redefine sustainability within the event industry and education. But there is a problem – and it’s not that the world is already over-saturated with recycled tote bags. As the biggest jamboree of this kind in the world, the show attracts over 600 vendors and over 30,000 visitors, with over 120 countries represented. Quite apart from all the collateral and surplus furniture, the carbon and material footprint of the event cannot be negligible. Think of all those start-up solution-providers flying and driving into town, AirB’n’B-ing for the duration, and Ubering around town after hours, for a start.

But this is not really the problem, either. Much as the event likes to talk about ‘driving impact and improving outcomes for teachers and learners’, the clear and only purpose of the event is to sell stuff. It is to enable the investors in the 600+ edtech solution-providers in the exhibition area to move towards making a return on their investment. If we wanted to talk seriously about sustainability, the question that needs to be asked is: to what extent does all the hardware and software on sale contribute in any positive and sustainable way to education? Is there any meaningful social benefit to be derived from all this hardware and software, or is it all primarily just a part of a speculative, financial game? Is the corporate social responsibility of BETT / Hyve a form of green-washing to disguise the stimulation of more production and consumption? Is it all just a kind of environmentalism of the rich’ (Dauvergne, 2016).

Edtech is not the most pressing of environmental problems – indeed, there are examples of edtech that are likely more sustainable than the non-tech alternatives – but the sustainability question remains. There are at least four environmental costs to edtech:

• The energy-greedy data infrastructures that lie behind digital transactions
• The raw ingredients of digital devices
• The environmentally destructive manufacture and production of digital devices
• The environmental cost of dismantling and disposing digital hardware (Selwyn, 2018)

Some forms of edtech are more environmentally costly than others. First, we might consider the material costs. Going back to pre-internet days, think of the countless tonnes of audio cassettes, VCR tapes, DVDs and CD-ROMs. Think of the discarded playback devices, language laboratories and IWBs. None of these are easily recyclable and most have ended up in landfill, mostly in countries that never used these products. These days the hardware that is used for edtech is more often a device that serves other non-educational purposes, but the planned obsolescence of our phones, tablets and laptops is a huge problem for sustainability.

More important now are probably the energy costs of edtech. Audio and video streaming might seem more environmentally friendly than CDs and DVDs, but, depending on how often the CD or DVD is used, the energy cost of streaming (especially high quality video) can be much higher than using the physical format. AI ups the ante significantly (Brevini, 2022). Five years ago, a standard ‘AI training model in linguistics emit more than 284 tonnes of carbon dioxide equivalent’ (Strubell et al., 2019). With exponentially greater volumes of data now being used, the environmental cost is much, much higher. Whilst VR vendors will tout the environmental benefits of cutting down on travel, getting learners together in a physical room may well have a much lower carbon footprint than meeting in the Metaverse.

When doing the calculus of edtech, we need to evaluate the use-value of the technology. Does the tech actually have any clear educational (or other social) benefit, or is its value primarily in terms of its exchange-value?

To illustrate the difference between use-value and exchange-value, I’d like to return again to the beginnings of modern edtech in ELT. As the global market for ELT materials mushroomed in the 1990s, coursebook publishers realised that, for a relatively small investment, they could boost their sales by bringing out ‘new editions’ of best-selling titles. This meant a new cover, replacing a few texts and topics, making minor modifications to other content, and, crucially, adding extra features. As the years went by, these extra features became digital: CD-ROMs, DVDs, online workbooks and downloadables of various kinds. The publishers knew that sales depended on the existence of these shiny new things, even if many buyers made minimal use or zero use of them. But they gave the marketing departments and sales reps a pitch, and justified an increase in unit price. Did these enhanced coursebooks actually represent any increase in use-value? Did learners make better or faster progress in English as a result? On the whole, the answer has to be an unsurprising and resounding no. We should not be surprised if hundreds of megabytes of drag-and-drop grammar practice fail to have much positive impact on learning outcomes. From the start, it was the impact on the exchange-value (sales and profits) of these products that was the driving force.

Edtech vendors have always wanted to position themselves to potential buyers as ‘solution providers’, trumpeting the use-value of what they are selling. When it comes to attracting investors, it’s a different story, one that is all about minimum viable products, scalability and return on investment.

There are plenty of technologies that have undisputed educational use-value in language learning and teaching. Google Docs, Word, Zoom and YouTube come immediately to mind. Not coincidentally, they are not technologies that were designed for educational purposes. But when you look at specifically educational technology, It becomes much harder (though not impossible) to identify unambiguous gains in use-value. Most commonly, the technology holds out the promise of improved learning, but evidence that it has actually achieved this is extremely rare. Sure, a bells-and-whistles LMS offers exciting possibilities for flipped or blended learning, but research that demonstrates the effectiveness of these approaches in the real world is sadly lacking. Sure, VR might seem to offer a glimpse of motivated learners interacting meaningfully in the Metaverse, but I wouldn’t advise you to bet on it.

And betting is what most edtech is all about. An eye-watering $16.1 billion of venture capital was invested in global edtech in 2020. What matters is not that any of these products or services have any use-value, but that they are perceived to have a use-value. Central to this investment is the further commercialisation and privatisation of education (William & Hogan 2020). BETT is a part of this.

Returning to the development of my sustainability skills, I still need to consider the bigger picture. I’ve suggested that it is difficult to separate edtech from a consideration of capitalism, a system that needs to manufacture consumption, to expand production and markets in order to survive (Dauvergne, 2016: 48). Economic growth is the sine qua non of this system, and it is this that makes the British government (and others) so keen on BETT. Education and edtech in particular are rapidly growing markets. But growth is only sustainable, in environmental terms, if it is premised on things that we actually need, rather than things which are less necessary and ecologically destructive (Hickel, 2020). At the very least, as Selwyn (2021) noted, we need more diverse thinking: ‘What if environmental instability cannot be ‘solved’ simply through the expanded application of digital technologies but is actually exacerbated through increased technology use?’

References

Brevini, B. (2022) Is AI Good for the Planet? Cambridge: Polity Press

Dauvergne, P. (2016) Environmentalism of the Rich. Cambridge, Mass.: MIT Press

Hickel, J. (2020) Less Is More. London: William Heinemann

Selwyn, N. (2018) EdTech is killing us all: facing up to the environmental consequences of digital education. EduResearch Matters 22 October, 2018. https://www.aare.edu.au/blog/?p=3293

Selwyn, N. (2021) Ed-Tech Within Limits: Anticipating educational technology in times of environmental crisis. E-Learning and Digital Media, 18 (5): 496 – 510. https://journals.sagepub.com/doi/pdf/10.1177/20427530211022951

Strubell, E., Ganesh, A. & McCallum, A. (2019) Energy and Policy Considerations for Deep Learning in NLP. Cornell University: https://arxiv.org/pdf/1906.02243.pdf

Williamson, B. & Hogan, A. (2020) Commercialisation and privatisation in / of education in the context of Covid-19. Education International

Learning and earning

In the campaign for leadership of the British Conservative party, prime ministerial wannabe, Rishi Sunak, announced that he wanted to phase out all university degrees with low ‘earning potential’. This would mean the end of undergraduate courses in fashion, film, philosophy, English language and media studies. And linguistics. More of an attention-grabbing soundbite than anything else, it reflects a view of education that is shared by his competitor, Liz Truss, who ‘is passionate about giving every child basic maths and science skills’ as a way of driving the contribution of education to the economy.

It’s a view that is shared these days by practically everyone with any power and influence, from national governments to organisations like the EU and the OECD (Schuller, 2000). It is rooted in the belief that what matters most in education are the teachable knowledges, skills and competences that are relevant to economic activity (as the OECD puts it). These competences are seen to be essential to economic growth and competitivity, and essential to individuals to enhance their employment potential. Learning equals earning. The way for societies to push this orientation to education is to allow market forces to respond to the presumed demands of the consumers of education (students and their sponsors), as they seek to obtain the best possible return on their investment in education. Market forces are given more power when education is privatized and uncoupled from the state. For this to happen, the market may need a little help in the form of policies from the likes of Sunak and Truss.

This set of beliefs has a name: human capital theory (Becker, 1993). Human capital refers both to the skills that individuals ‘bring to bear in the economy and the need for capital investment in these’ (Holborow, 2012). It is impossible to overstate just how pervasive this theory in contemporary approaches to education is. See, for example, this selection of articles from Science Direct. It is also very easy to forget how recently the lens of human capital has become practically the only lens through which education is viewed.

Contemporary language teaching is perhaps best understood as a series of initiatives that have been driven by human capital theory. First and foremost, there is the global ‘frenzied rush towards acquiring English’ (Holborow, 2018), driven both by governments and by individuals who see that foreign language competence (especially English) ‘might […]open up new opportunities for students [and] assist them in breaking social barriers’ (Kormos & Kiddle, 2013). Children, at ever younger ages (even pre-school), are pushed towards getting a headstart in the race to acquire human capital, whilst there has been an explosive growth in EMI courses (Lasagabaster, 2022). At the same time, there has been mushrooming interest in so-called 21^st century skills (or ‘life skills’ / ‘global skills’) in the English language curriculum. These skills have been identified by asking employers what skills matter most to them when recruiting staff. Critical and creative thinking skills may be seen as having pre-Human Capital, intrinsic educational worth, but it is their potential contribution to economic productivity that explains their general current acceptance.

Investments in human capital need to be measured and measurable. Language teaching needs to be made accountable. Our preoccupation with learning outcomes is seen in the endless number of competency frameworks, and with new tools for quantifying language proficiency. Technology facilitates this evaluation, promises to deliver language teaching more efficiently, and technological skills are, after English language skills themselves, seen to be the most bankable of 21^st century skills. Current interest in social-emotional learning – growth mindsets, grit, resilience and so on – is also driven by a concern to make learning more efficient.

In all of these aspects of language teaching / learning, the private sector (often in private-public partnerships) is very visible. This is by design. Supported by the state, the market economy of education grows in tandem with the rising influence of the private sector on national educational policy. When education ministers lose their job, they can easily find well-paid consultancies in the private sector (as in the case of Sunak and Truss’s colleague, Gavin Williamson).

One of the powers of market-economy ideologies is that it often seems that ‘there is no alternative’ (TINA). There are, however, good reasons to try to think in alternative terms. To begin with, and limiting ourselves for the moment to language teaching, there is a desperate lack of evidence that starting English language learning at very young ages (in the way that is most typically done) will lead to any appreciable gains in the human capital race. It is generally recognised that EMI is highly problematic in a variety of ways (Lasagabaster, 2022). The focus on 21^st century skills has not led to any significant growth in learning outcomes when these skills are measured. There is a worrying lack of evidence that interventions in schools to promote improvements in critical or creative thinking have had much, if any, impact at all. Similarly, there is a worrying lack of evidence that attention to growth mindsets or grit has led to very much at all. Personalized learning, facilitated by technology, likewise has a dismal track record. At the same time, there is no evidence that the interest in measuring learning outcomes has led to any improvement in those outcomes. For all the millions and millions that have been invested in all these trends, the returns have been very slim. Perhaps we would have done better to look for solutions to those aspects of language teaching which we know to be problematic. The obsession with synthetic syllabuses delivered by coursebooks (or their online equivalents) comes to mind.

But beyond the failure of all these things to deliver on their promises, there are broader issues. Although language skills (usually English) have the potential to enhance employment prospects, Holborow (2018) has noted that they do not necessarily do so (see, for example, Yeung & Gray, 2022). Precisely how important language skills are is very hard to determine. A 2016 survey by Cambridge English found that ‘approximately half of all employers offer a better starting package to applicants with good English language skills’ and a similar number indicate that these skills result in faster career progression. But these numbers need to be treated with caution, not least because Cambridge English is in the business of selling English. More importantly, it seems highly unlikely that the figures that are reported reflect the reality of job markets around the world. The survey observes that banking, finance and law are the sectors with the greatest need for such skills, but these are all usually graduate posts. An average of 39% of the population in OECD countries has tertiary education; the percentage is much lower elsewhere. How many students of a given age cohort will actually work in these sectors? Even in rich countries, like Germany and the Netherlands, between 40 and 60% of workers are employed in what is termed ‘nonstandard forms of work’ (OECD, 2015) where language skills will count for little or nothing. These numbers are growing. Language skills are of most value to those students who are already relatively advantaged. That is not to say that there are no potential benefits to everyone in learning English, but these benefits will not be found in better jobs and wages for the majority. One interesting case study describes how a Swiss airport company exploits the language skills of migrant workers, without any benefits (salary or mobility) accruing to the workers themselves (Duchêne, 2011).

The relationship between learning English and earning more is a lot more complex than is usually presented. The same holds true for learning more generally. In the US, ‘nearly two-thirds of job openings in 2020 required no more than a high school diploma’ (Brown et al., 2022: 222). Earnings for graduates in real terms are in decline, except for those at the very top. For the rest, over $1.3 trillion in student loan debt remains unpaid. Elsewhere in the world, the picture is more mixed, but it is clear that learning does not equal earning in the global gig economy.

This evident uncoupling of learning from earning has led some to conclude that education is ‘a waste of time and money’ (Caplan, 2018), a view that has been gaining traction in the US. It’s not an entirely unreasonable view, if the only reason for education is seen to be its contribution to the economy. More commonly, the reaction has been to double-down on human capital theory. In Spain, for example, with its high levels of youth unemployment, there are calls for closer links between educational institutions, and graduates themselves are blamed for failing to take ‘advantage of the upgrading in the demand for skills’ (Bentolilla et al., 2022). This seems almost wilfully cruel, especially since the authors note that there is global trend in falling economic returns in tertiary education (ILO, 2020).

But, rather than doubling-down on human capital theory (e.g. more vocational training, more efficient delivery of the training), it might be a good idea to question human capital theory itself. Both early and more recent critics have tended to accept without hesitation that education can enhance worker productivity, but argue that, as a theory, it is too simplistic to have much explanatory power, and that the supporting evidence is weak, vague or untestable (Bowles & Gintis, 1975; Fix, 2018). Language skills, like education more generally, do not always lead to better employment prospects and salaries, because ‘wider, systemic social inequalities come into play’ (Holborow, 2018). It is not because black women need to brush up on their 21^st century skills that they earn less than white men.

Until recently, critics of human capital theory have been a minority, and largely unheard, voice. But this appear to be changing. The World Bank, more guilty than anyone for pushing human capital theory on the global stage (see here), has recognised that hoped-for job outcomes do not always materialize after massive investments in training systems (World Bank, 2013). Mainstream critics include the Nobel prize winners Joseph Stiglitz and Amartya Sen, and the recent OUP title, ‘The Death of Human Capital?’ (Brown et al., 2020) is likely to spur debate further. The assumption that human capital theory holds water no longer holds water.

When we turn back to English language teaching, we might benefit from some new thinking. For sure, there will be large numbers of English language learners whose only purpose in studying is utilitarian, whose primary desire is to enhance their human capital. But there are also millions, especially children studying in public schools, for whom things are rather different. A major change in thinking involves a reconceptualization of the point of all this English study. If learning English is not, for the majority, seen primarily as a preparation for the workplace, but as compensation for the realities of (un)employment (Brown et al., 2020: 13), most of the recent innovations in ELT would become highly suspect. We would have a much less impoverished view of ‘the complex and multifaceted nature of language’ (Holborow, 2018) and we would find more space for plurilingual practices. A brake on relentless Englishization might be no bad thing (Wilkinson & Gabriëls, 2021). We might be able to explore more fully artistic and creative uses of language. Who knows? We might finally get round to wider implementation of language teaching approaches that we know have a decent chance of success.

References

Becker, G. S. (1993). Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education (3^rd ed.). University of Chicago Press.

Bentolila, S., Felgueroso, F., Jansen, M. et al. (2022). Lost in recessions: youth employment and earnings in Spain. SERIEs 13: 11–49. https://doi.org/10.1007/s13209-021-00244-6

Bowles, S. & Gintis, H. (1975). The Problem with Human Capital Theory – a Marxian critique. The American Economic Review, 65 (2): 74 – 83

Brown, S., Lauder, H. & Cheung, S. Y. (2020). The Death of Human Capital? New York: Oxford University Press

Caplan, B. (2018). The Case against Education: Why the Education System is a Waste of Time and Money. Princeton, NJ: Princeton University Press

Duchêne, A. (2011). Neoliberalism, Social Inequalities, and Multilingualism: The Exploitation of Linguistic Resources and Speakers. Langage et Société, 136 (2): 81 – 108

Fix, B. (2018). The Trouble with Human Capital Theory. Working Papers on Capital as Power, No. 2018/7

Holborow, M. (2012). Neoliberal keywords and the contradictions of an ideology. In Block, D., Gray, J. & Holborow, M. Neoliberalism and Applied Linguistics. Abingdon: Routledge: 33 – 55

Holborow, M. (2018). Language skills as human capital? Challenging the neoliberal frame. Language and Intercultural Communication, 18: (5): 520-532

ILO (2020). Global employment trends for youth, 2020. Geneva: International Labour Organization

Kormos, J., & Kiddle, T. (2013). The role of socio-economic factors in motivation to learn English as a foreign language: the case of Chile. System, 41(2): 399-412

Lasagabaster, D. (2022). English-Medium Instruction in Higher Education. Cambridge: Cambridge University Press

OECD (2015). In It Together, Why Less Inequality Benefits All. Paris: OECD

Schuller, T. (2000). Social and Human Capital: The Search for Appropriate Technomethodology. Policy Studies, 21 (1): 25 – 35

Wilkinson, R., & Gabriëls, R. (Eds.) (2021). The Englishization of Higher Education in Europe. Amsterdam: Amsterdam University Press.

World Bank (2012). World Development Report 2013: Jobs. Washington, DC: World Bank

Yeung, S. & Gray, J. (2022). Neoliberalism, English, and spoiled identity: The case of a high-achieving university graduate in Hong Kong. Language in Society, First View, pp. 1 – 22

Social robots for English language teaching

In May of last year, EL Gazette had a story entitled ‘Your new English language teacher is a robot’ that was accompanied by a stock photo of a humanoid robot, Pepper (built by SoftBank Robotics). The story was pure clickbait and the picture had nothing to do with it. The article actually concerned a chatbot (EAP Talk) to practise EAP currently under development at a Chinese university. There’s nothing especially new about chatbots: I last blogged about them in 2016 and interest in them, both research and practical, dates back to the 1970s (Lee et al., 2020). There’s nothing, as far as I can see, especially new about the Chinese EAP chatbot project either. The article concludes by saying that the academic behind the project ‘does not believe that AI can ever replace a human teacher’, but that chatbots might offer some useful benefits.

The benefits are, however, limited – a point that is acknowledged even by chatbot enthusiasts like Lee et al (2020). We are some way from having chatbots that we can actually have meaningful conversations with, but they do appear to have some potential as ‘intelligent tutoring systems’ to provide practice of and feedback on pre-designated bits of language (especially vocabulary and phrases). The main benefit that is usually given, as in the EL Gazette article, is that they are non-judgemental and may, therefore, be appropriate for shy or insecure learners.

Social robots, of the kind used in the illustration for the EL Gazette story, are, of course, not the same as chatbots. Chatbots, like EAP Talk, can be incorporated into all sorts of devices (notably phones, tablets and laptops) and all sorts of applications. If social robots are to be used for language learning, they will clearly need to incorporate chatbots, but in what ways could the other features of robots facilitate language acquisition? Pepper (the robot in the picture) has ‘touch sensors, LEDs and microphones for multimodal interactions’, along with ‘infrared sensors, bumpers, an inertial unit, 2D and 3D cameras, and sonars for omnidirectional and autonomous navigation’. How could these features help language acquisition?

Lee and Lee (2022) attempt to provide an answer to this question. Here’s what they have come up with:

By virtue of their physical embodiment, social robots have been suggested to provide language learners with direct and physical interactions, which is considered one of the basic ingredients for language learning. In addition, as social robots are generally humanoids or anthropomorphized animal shapes, they have been valued for their ability to serve as familiar conversational partners, having potential to lower the affective filter of language learners.

Is there any research evidence to back up these claims? The short answer is no. Motivation and engagement may sometimes be positively impacted, but we can’t say any more than that. As far as learning is concerned, Lee and Lee (2022: 121) write: involving social robots led to statistically similar or even higher [English language learning] outcomes compared with traditional ELT contexts (i.e. no social robot). In other words, social robots did not, on the whole, have a negative impact on learning outcomes. Hardly grounds for wild enthusiasm … Still, Lee and Lee, in the next line, refer to the ‘positive effectiveness of social robots in English teaching’ before proceeding to enumerate the ways in which these robots could be used in English language learning. Doesn’t ELT Journal have editors to pick up on this kind of thing?

So, how could these robots be used? Lee and Lee suggest (for younger learners) one-on-one vocabulary tutoring, dialogue practice, more vocabulary teaching, and personalized feedback. That’s it. It’s worth noting that all of these functions could equally well be carried out by chatbots as by social robots.

Lee and Lee discuss and describe the social robot, NAO6, also built by SoftBank Robotics. It’s a smaller and cheaper cousin of the Pepper robot that illustrates the EL Gazette article. Among Lee and Lee’s reasons for using social robots is that they ‘have become more accessible due to ever-lower costs’: NAO6 costs around £350 a month to rent. Buying it outright is also an option. Eduporium (‘Empowering the future with technology’) has one on offer for $12,990.00. According to the blurb, it helps ‘teach coding, brings literature to life, enhances special education, and allows for training simulations. Plus, its educational solutions include an intuitive interface, remote learning, and various applications for accessibility!’

It’s easy enough to understand why EL Gazette uses clickbait from time to time. I’m less clear about why ELT Journal would print this kind of nonsense. According to Lee and Lee, further research into social robots ‘would initiate a new era of language learning’ in which the robots will become ‘an important addition to the ELT arsenal’. Yeah, right …

References

Lee, H. & Lee, J. H. (2022) Social robots for English language teaching. ELT Journal 76 (1): 119 – 124

Lee, J. H., Yang, H., Shin D. & Kim, H. (2020) Chatbots. ELT Journal 74 (3): 338 – 3444

The Long Covid of Education

The pandemic has affected all learners, but the more vulnerable the learner, the harder they have been hit. The evidence is very clear that Covid and the response of authorities to it has, in the words of UNESCO , ‘increased inequalities and exacerbated a pre-existing education crisis’. Learning poverty (a term coined by UNESCO and the World Bank), which refers to the ability to read and understand a simple text by the age of 10, is just one way of looking at these inequalities. Before the pandemic, 53% of children in low and middle income countries (and 9% in high income countries) were living in learning poverty. According to the World Bank (Azevedo et al., 2021), the pandemic will amplify this crisis with the figure rising to somewhere between 63% and 70%. The fear is that the recovery from Covid may be ‘similarly inequitable and that the effects of COVID-19 will be long-lasting’ (ibid.).

Inequity was not, of course, the only problem that educational systems faced before the pandemic. Since the turn of the millennium, it has been common to talk about ‘reimagining education’, and use of this phrase peaked in the summer of 2020. Leading the discoursal charge was Andreas Schleicher, head of education at the OECD, who saw the pandemic as ‘a great moment’ for education, since ‘the current wave of school closures offers an opportunity for experimentation and for envisioning new models of education’. Schleicher’s reimagining involves a closely intertwined privatization (by ending state monopolies) and digitalization of education (see this post for more details). Other reimaginings are usually very similar. Yong Zhao, for example, does not share Schleicher’s enthusiasm for standardized tests, but he sees an entrepreneurial, technology-driven, market-oriented approach as the way forward. He outlined this, pre-pandemic, in his book An Education Crisis is a Terrible Thing to Waste (Zhao et al., 2019), and then picked up on the pandemic (Zhao, 2020) to reiterate his ideas and, no doubt, to sell his book – all ‘in the spirit’, he writes, ‘of never wasting a good crisis’.

It was Churchill who first said ‘Never let a good crisis go to waste’, but it is often attributed to Emanuel Rahm, Obama’s Chief of Staff, who said the same thing in reference to the financial crisis of 2009. As we have seen in the last two years, crises can be good opportunities to push through policy changes. Viktor Orbán provides a good example. Crises can also be a way to make a financial killing, a practice known as ‘disaster capitalism’ (Loewenstein, 2017). Sometimes, it’s possible to change policy and turn a tidy profit at the same time. One example from the recent past shows us the way.

Following Hurricane Katrina in 2005, education was massively disrupted in New Orleans and the surrounding areas. Arne Duncan, who became Obama’s Secretary for Education a few years after Katrina, had this to say about the disaster: “Let me be really honest. I think the best thing that happened to the education system in New Orleans was Hurricane Katrina. That education system was a disaster, and it took Hurricane Katrina to wake up the community to say that ‘We have to do better.’” The reform that followed, inspired by Milton Friedman, involved replacing New Orleans’ public school system with privately run charter schools. The change took place with ‘military speed and precision’, compared to the ‘glacial pace’ with which levees and the electricity grid were repaired (Klein, 2007: 5). Nearly 5000 unionized teachers were fired, although some of the younger ones were rehired on reduced salaries. Most of the city’s poorer residents were still in exile when the changes took place: the impact on the most vulnerable students was entirely predictable. ‘The social and economic situation always bleeds into the school, said one researcher into the impact of the catastrophe.

Disaster capitalism may, then, be a useful lens through which to view the current situation (Moore et al., 2021). Betsy DeVos, Trump’s Secretary for Education, stated that the pandemic was an opportunity to ‘look very seriously at the fact that K-12 education for too long has been very static and very stuck in one method of delivering and making instruction available’ (Ferrari, 2020). What DeVos, who was famous for having described public education as a ‘dead end’, meant by this was privatization and digitalization, and privatization through digitalization. Although the pandemic is far from over, we can already begin to ask: has the crisis been wasted?

Turning from the US to Europe, a fascinating report by Zancajo et al (2022) examines the educational policy responses to Covid in a number of European countries. The first point to note is that the recovery plans of these countries is not fundamentally any different from pre-pandemic educational policy. The Covid-19 pandemic has simply ‘served as a catalyst to accelerate preexisting digitization policies in education systems’. Individual states are supported by the European Commission’s Digital Education Action Plan 2021–2027 (European Commission, 2021) which lists three main priorities: making use of technology, the development of digital skills for teachers and learners, and the increased use of data to improve education. The focus of attention of education policy in the national recovery plans of individual EU countries is almost completely monopolized by digitalization. Covid has not led to any reimagining of education: it has simple been ‘a path accelerator contributing to strengthening policy instruments and solutions that were already on the agenda (Zancajo et al., 2022). Less overtly obvious than digitalization has been the creeping privatization that occurs when a greater proportion of national education budgets is spent on technology provided by private companies.

Creeping privatization has been especially noticeable in British universities, which, for years, have been focusing on the most profitable ‘revenue streams’ and on cutting the costs of academic labour. The pandemic has been used by some (Leicester and Manchester, for example) as a justification for further restructuring, cost-cutting and the development of new digitally-driven business models (Nehring, 2021). In schools, the private technology providers were able to jump in quickly because the public sector was unprepared, and, in so doing, position themselves as essential services. The lack of preparedness of the public sector is not, of course, unsurprising, since it has been underfunded for so long. Underfund – create a crisis – privatize the solution: such has long been the ‘Shock Doctrine’ game plan of disaster capitalists. Naomi Klein has observed that where we have ended up in post-Covid education is probably where we would have ended up anyway: Covid accelerated the process by ten years.

Williamson and Hogan (2020) describe the current situation in the following terms:

The pivot to online learning and ‘emergency remote teaching’ has positioned educational technology (edtech) as an integral component of education globally, bringing private sector and commercial organisations into the centre of essential educational services. […] A global education industry of private and commercial organisations has played a significant role in educational provision during the Covid-19 crisis, working at local, national and international scales to insert edtech into educational systems and practices. It has often set the agenda, offered technical solutions for government departments of education to follow, and is actively pursuing long-term reforms whereby private technology companies would be embedded in public education systems during the recovery from the Covid-19 crisis and beyond it in new models of hybrid teaching and learning. […] Supported by multilateral policy influencing organisations and national government departments, these companies have integrated schools, teachers and students into their global cloud systems and online education platforms, raising the prospect of longterm dependencies of public education institutions on private technology infrastructures.

And where is educational equity in all this? Even the OECD is worried – more assessment is needed to identify learning losses, they say! A pandemic tale from California will give us a clue. When schools shut down, 50% of low-income California students lacked the necessary technology to access distance learning (Gutentag, 2020). Big Tech came riding to the rescue: donations from companies like HP, Amazon, Apple, Microsoft and Google made it possible for chromebooks and wifi hotspots to be made available for every student, and California legislators and corporations could congratulate themselves on closing the ‘digital divide’ (ibid.). To compensate for increased problems of homelessness, poverty, hunger, and discrimination, the most vulnerable students now have a laptop or tablet, with which they can generate data to be monetized by the tech vendors (Feathers, 2022).

References

Azevedo, J. P. W., Rogers, F. H., Ahlgren, S. E., Cloutier, M-H., Chakroun, B., Chang, G-C., Mizunoya, S., Reuge,N. J., Brossard, M., & Bergmann, J. L. (2021) The State of the Global Education Crisis : A Path to Recovery (English). Washington, D.C. : World Bank Group. https://documents1.worldbank.org/curated/en/416991638768297704/pdf/The-State-of-the-Global-Education-Crisis-A-Path-to-Recovery.pdf

European Commission. (2021) Digital education action plan 2021-2027. Resetting Education, Brussels

Feathers, T. (2022) This Private Equity Firm Is Amassing Companies That Collect Data on America’s Children. January 11th, 2022 The Markup https://themarkup.org/machine-learning/2022/01/11/this-private-equity-firm-is-amassing-companies-that-collect-data-on-americas-children

Ferrari, K. (2020) Disaster Capitalism Is Coming for Public Education. Jacobin 14 May 2020 https://jacobinmag.com/2020/05/public-education-schools-covid-coronavirus-charter-teachers

Gutentag, A. (2020) The Virtual Education Shock Doctrine. The Bellows https://www.thebellows.org/the-virtual-education-shock-doctrine/

Klein, N. (2007) The Shock Doctrine. New York: Metropolitan Books

Loewenstein, A. (2017) Disaster Capitalism. London: Verso Books

Moore, S. D. M., Jayme, B. D., Black, J. (2021) Disaster capitalism, rampant edtech opportunism, and the advancement of online learning in the era of COVID19. Critical Education, 12(2), 1-21.

Nehring, D. (2021) Is COVID-19 Enabling Academic Disaster Capitalism? Social Science Space 21 July 2021 https://www.socialsciencespace.com/2021/07/is-covid-19-enabling-academic-disaster-capitalism/

Williamson, B., & Hogan, A. (2020). Commercialisation and privatisation in/of education in the context of Covid-19. Education International, Brussels.

Zancajo, A., Verger, A. & Bolea, P. (2022) Digitalization and beyond: the effects of Covid-19 on post-pandemic educational policy and delivery in Europe, Policy and Society, puab016, https://doi.org/10.1093/polsoc/puab016

Zhao, Y. (2020) COVID-19 as a catalyst for educational change. Prospects 49: 29–33. https://doi.org/10.1007/s11125-020-09477-y

Zhao, Y., Emler, T. E., Snethen, A. & Yin, D. (2019) An Education Crisis is a Terrible Thing to Waste. New York: Teachers College Press

The digital future of education (according to the OECD)

On 21 January, I attended the launch webinar of DEFI (the Digital Education Futures Initiative), an initiative of the University of Cambridge, which seeks to work ‘with partners in industry, policy and practice to explore the field of possibilities that digital technology opens up for education’. The opening keynote speaker was Andrea Schleicher, head of education at the OECD. The OECD’s vision of the future of education is outlined in Schleicher’s book, ‘World Class: How to Build a 21st-Century School System’, freely available from the OECD, but his presentation for DEFI offers a relatively short summary. A recording is available here, and this post will take a closer look at some of the things he had to say.

Schleicher is a statistician and the coordinator of the OECD’s PISA programme. Along with other international organisations, such as the World Economic Forum and the World Bank (see my post here), the OECD promotes the global economization and corporatization of education, ‘based on the [human capital] view that developing work skills is the primary purpose of schooling’ (Spring, 2015: 14). In other words, the main proper function of education is seen to be meeting the needs of global corporate interests. In the early days of the COVID-19 pandemic, with the impact of school closures becoming very visible, Schleicher expressed concern about the disruption to human capital development, but thought it was ‘a great moment’: ‘the current wave of school closures offers an opportunity for experimentation and for envisioning new models of education’. Every cloud has a silver lining, and the pandemic has been a godsend for private companies selling digital learning (see my post about this here) and for those who want to reimagine education in a more corporate way.

Schleicher’s presentation for DEFI was a good opportunity to look again at the way in which organisations like the OECD are shaping educational discourse (see my post about the EdTech imaginary and ELT).

He begins by suggesting that, as a result of the development of digital technology (Google, YouTube, etc.) literacy is ‘no longer just about extracting knowledge’. PISA reading scores, he points out, have remained more or less static since 2000, despite the fact that we have invested (globally) more than 15% extra per student in this time. Only 9% of all 15-year-old students in the industrialised world can distinguish between fact and opinion.

To begin with, one might argue about the reliability and validity of the PISA reading scores (Berliner, 2020). One might also argue, as did a collection of 80 education experts in a letter to the Guardian, that the scores themselves are responsible for damaging global education, raising further questions about their validity. One might argue that the increased investment was spent in the wrong way (e.g. on hardware and software, rather than teacher training, for example), because the advice of organisations like OECD has been uncritically followed. And the statistic about critical reading skills is fairly meaningless unless it is compared to comparable metrics over a long time span: there is no reason to believe that susceptibility to fake news is any more of a problem now than it was, say, one hundred years ago. Nor is there any reason to believe that education can solve the fake-news problem (see my post about fake news and critical thinking here). These are more than just quibbles, but the main point that Schleicher is making is that education needs to change.

Schleicher next presents a graph which is designed to show that the amount of time that students spend studying correlates poorly with the amount they learn. His interest is in the (lack of) productivity of educational activities in some contexts. He goes on to argue that there is greater productivity in educational activities when learners have a growth mindset, implying (but not stating) that mindset interventions in schools would lead to a more productive educational environment.

Schleicher appears to confuse what students learn with the things they have learnt that have been measured by PISA. The two are obviously rather different, since PISA is only interested in a relatively small subset of the possible learning outcomes of schooling. His argument for growth mindset interventions hinges on the assumption that such interventions will lead to gains in reading scores. However, his graph demonstrates a correlation between growth mindset and reading scores, not a causal relationship. A causal relationship has not been clearly and empirically demonstrated (see my post about growth mindsets here) and recent work by Carol Dweck and her associates (e.g. Yeager et al., 2016), as well as other researchers (e.g. McPartlan et al, 2020), indicates that the relationship between gains in learning outcomes and mindset interventions is extremely complex.

Schleicher then turns to digitalisation and briefly discusses the positive and negative affordances of technology. He eulogizes platform companies before showing a slide designed to demonstrate that (in the workplace) there is a strong correlation between ICT use and learning. He concludes: ‘the digital world of learning is a hugely empowering world of learning’.

A brief paraphrase of this very disingenuous part of the presentation would be: technology can be good and bad, but I’ll only focus on the former. The discourse appears balanced, but it is anything but.

During the segment, Schleicher argues that technology is empowering, and gives the examples of ‘the most successful companies these days, they’re not created by a big industry, they’re created by a big idea’. This is plainly counterfactual. In the case of Alphabet and Facebook, profits did not follow from a ‘big idea’: the ideas changed as the companies evolved.

Schleicher then sketches a picture of an unpredictable future (pandemics, climate change, AI, cyber wars, etc.) as a way of framing the importance of being open (and resilient) to different futures and how we respond to them. He offers two different kinds of response: maintenance of the status quo, or ‘outsourcing’ of education. The pandemic, he suggests, has made more countries aware that the latter is the way forward.

In his discussion of the maintenance of the status quo, Schleicher talks about the maintenance of educational monopolies. By this, he must be referring to state monopolies on education: this is a favoured way of neoliberals of referring to state-sponsored education. But the extent to which, in 2021 in many OECD countries, the state has any kind of monopoly of education, is very open to debate. Privatization is advancing fast. Even in 2015, the World Education Forum’s ‘Final Report’ wrote that ‘the scale of engagement of nonstate actors at all levels of education is growing and becoming more diversified’. Schleicher goes on to talk about ‘large, bureaucratic school systems’, suggesting that such systems cannot be sufficiently agile, adaptive or responsive. ‘We should ask this question,’ he says, but his own answer to it is totally transparent: ‘changing education can be like moving graveyards’ is the title of the next slide. Education needs to be more like the health sector, he claims, which has been able to develop a COVID vaccine in such a short period of time. We need an education industry that underpins change in the same way as the health industry underpins vaccine development. In case his message isn’t yet clear enough, I’ll spell it out: education needs to be privatized still further.

Schleicher then turns to the ways in which he feels that digital technology can enhance learning. These include the use of AR, VR and AI. Technology, he says, can make learning so much more personalized: ‘the computer can study how you study, and then adapt learning so that it is much more granular, so much more adaptive, so much more responsive to your learning style’. He moves on to the field of assessment, again singing the praises of technology in the ways that it can offer new modes of assessment and ‘increase the reliability of machine rating for essays’. Through technology, we can ‘reunite learning and assessment’. Moving on to learning analytics, he briefly mentions privacy issues, before enthusing at greater length about the benefits of analytics.

Learning styles? Really? The reliability of machine scoring of essays? How reliable exactly? Data privacy as an area worth only a passing mention? The use of sensors to measure learners’ responses to learning experiences? Any pretence of balance appears now to have been shed. This is in-your-face sales talk.

Next up is a graph which purports to show the number of teachers in OECD countries who use technology for learners’ project work. This is followed by another graph showing the number of teachers who have participated in face-to-face and online CPD. The point of this is to argue that online CPD needs to become more common.

I couldn’t understand what point he was trying to make with the first graph. For the second, it is surely the quality of the CPD, rather than the channel, that matters.

Schleicher then turns to two further possible responses of education to unpredictable futures: ‘schools as learning hubs’ and ‘learn-as-you-go’. In the latter, digital infrastructure replaces physical infrastructure. Neither is explored in any detail. The main point appears to be that we should consider these possibilities, weighing up as we do so the risks and the opportunities (see slide below).

Useful ways to frame questions about the future of education, no doubt, but Schleicher is operating with a set of assumptions about the purpose of education, which he chooses not to explore. His fundamental assumption – that the primary purpose of education is to develop human capital in and for the global economy – is not one that I would share. However, if you do take that view, then privatization, economization, digitalization and the training of social-emotional competences are all reasonable corollaries, and the big question about the future concerns how to go about this in a more efficient way.

Schleicher’s (and the OECD’s) views are very much in accord with the libertarian values of the right-wing philanthro-capitalist foundations of the United States (the Gates Foundation, the Broad Foundation and so on), funded by Silicon Valley and hedge-fund managers. It is to the US that we can trace the spread and promotion of these ideas, but it is also, perhaps, to the US that we can now turn in search of hope for an alternative educational future. The privatization / disruption / reform movement in the US has stalled in recent years, as it has become clear that it failed to deliver on its promise of improved learning. The resistance to privatized and digitalized education is chronicled in Diane Ravitch’s latest book, ‘Slaying Goliath’ (2020). School closures during the pandemic may have been ‘a great moment’ for Schleicher, but for most of us, they have underscored the importance of face-to-face free public schooling. Now, with the electoral victory of Joe Biden and the appointment of a new US Secretary for Education (still to be confirmed), we are likely to see, for the first time in decades, an education policy that is firmly committed to public schools. The US is by far the largest contributor to the budget of the OECD – more than twice any other nation. Perhaps a rethink of the OECD’s educational policies will soon be in order?

References

Berliner D.C. (2020) The Implications of Understanding That PISA Is Simply Another Standardized Achievement Test. In Fan G., Popkewitz T. (Eds.) Handbook of Education Policy Studies. Springer, Singapore. https://doi.org/10.1007/978-981-13-8343-4_13

McPartlan, P., Solanki, S., Xu, D. & Sato, B. (2020) Testing Basic Assumptions Reveals When (Not) to Expect Mindset and Belonging Interventions to Succeed. AERA Open, 6 (4): 1 – 16 https://journals.sagepub.com/doi/pdf/10.1177/2332858420966994

Ravitch, D. (2020) Slaying Goliath: The Passionate Resistance to Privatization and the Fight to Save America’s Public School. New York: Vintage Books

Schleicher, A. (2018) World Class: How to Build a 21^st-Century School System. Paris: OECD Publishing https://www.oecd.org/education/world-class-9789264300002-en.htm

Spring, J. (2015) Globalization of Education 2nd Edition. New York: Routledge

Yeager, D. S., et al. (2016) Using design thinking to improve psychological interventions: The case of the growth mindset during the transition to high school. Journal of Educational Psychology, 108(3), 374–391. https://doi.org/10.1037/edu0000098

VR – the next big thing in ELT

The VR experience is nothing if it is not immersive, and in language learning, the value of immersion in VR is seen to be the way in which it can lead to what we might call ‘engagement’ or ‘flow’. Fully immersed in a VR world, learning can be maximized, or so the thinking goes (Lan, 2020; Chen & Hsu, 2020). ‘By blocking out visual and auditory distractions in the classroom, VR has the potential to help students deeply connect with the material’ (Gadelha, 2018). ‘There are no distracting classroom windows to stare out of when students are directly immersed into the topic they are investigating’ (Bonner & Reinders, 2018: 36). Such is the allure of immersion that it is no surprise to find the word in the names of VR language learning products like Immerse and ImmerseMe (although the nod to bilingual immersion progammes (such as those in Canada) is an added bonus).

There is, however, immersion and immersion. A common categorisation of VR is into:

• non-immersive (e.g. a desktop game with a 2D screen and avatars)
• semi-immersive (e.g. high-end arcade games and flight simulators with large projections)
• fully immersive (e.g. with a head-mounted display, headphones, body sensors)

Taking things a little further is the possibility of directly inducing responses in the nervous system with molecular nanotechnology. We’re some way off that, but, fear not, people are working on it. At this point, it’s worth noting that this hierarchy of immersivity is driven by technological considerations: more tech = more immersion.

In ELT, the most common VR applications are currently at the low end of this scale. Probably the most talked about currently is the use of 360⁰ photography and a very simple headset like Google Cardboard, along with headphones, to take students on virtual field trips – anywhere from a museum or a Disney castle to a coral reef or outer space. See Raquel Ribeiro’s blog post for CUP for more ideas. Then, there are self-study packages, like Velawoods, which is a sort of combination of the SIMS with interaction made possible through speech recognition. The syllabus will be familiar to anyone used to using a contemporary coursebooks.

And, now, up a technological notch or two, is Immerse, which requires an Oculus headset. It appears to be a sort of Second Life where language learners can interact with each other and a trainer in a number of role plays, set in, for example, a garden barbecue, a pool bar, a conference or a deserted island. In addition to interacting with each other, students can interact with virtual objects, picking up darts and throw them at questions they want to focus on, for example. ‘Total physical engagement with the environment’ is how this is described by Immerse’s Chief Product Office. You can find out more in this promotional video.

Paul Driver has suggested that the evolution of VR can be ‘traced back through time as a constant struggle to create more immersive experiences. From the intricate scrolls of twelfth-century China, the huge panoramic paintings of the nineteenth century and early experiments in stereoscopic photography, to the promising but over-hyped 1990s arcade machines (which raised hopes and then dashed expectations for a whole generation), the history of virtual reality has been a meandering march forward, punctuated with long periods of stagnation’. Immerse may be fairly sophisticated as a VR language learning platform, but it has a long way to go as an immersive environment in comparison to games like Meeting Rembrandt: Master of Reality or Project VR Fishing. Its animations are crude and clunky, its scenarios short of detail.

But however ‘lifelike’ games like these are, their immersive potential is extremely limited if you have no interest in Rembrandt or fishing. VR is only as immersive as the intrinsic interest of (1) the ‘real world’ it is attempting to replicate, and (2) what you can do in it. The novelty factor may hold attention for a while, but not for long.

With simpler 360⁰ Google Cardboard versions of VR, you can’t actually do anything in the VR world besides watch, listen and marvel, so the intrinsic interest of the content is even more important. I quite like exploring the Okavango Delta, but I have no interest in rollercoasters or parachute jumps. But, to be immersed, I don’t actually need the 360⁰ experience at all, if the quality of the video is good enough. In many ways, I prefer an old-fashioned screen where my hands are not tied up with holding the phone into the Cardboard and the Cardboard to my nose.

360⁰ videos are usually short, and I can see how they can be used in a language class as a springboard for other work. But as a language learning tool, old-fashioned screens (with good content) may offer more potential than headsets (whether Cardboard or Oculus) because we can do other things (like communicate with other people, use a dictionary or take notes) at the same time.

VR technology in language learning cannot, therefore, (whatever its claims) generate immersion or engagement on its own. For the time being, it can, for some, captivate initial curiosity. For others, already used to high-end Oculus games, programmes like Immerse are more likely to generate a resounding ‘meh’. Engagement in learning is a highly complex phenomenon. Mercer and Dörnyei (2020: 102 ff.) argue that engaging learning materials must be designed for particular groups of learners (in terms of level and interests, for example) and they must get learners emotionally invested. Improvements in VR technology won’t really change anything.

VR is already well established and successful in some forms of education: military, healthcare and engineering, especially. Virtual reality is obviously a good place to learn how to defuse a bomb or carry out keyhole surgery. In other areas, such as soft skills training in corporate contexts, its use is growing, but its effectiveness is much less clear. In language learning, the purported advantages of VR (see, for example, Alizadeh, 2019, which has a useful bibliography, or Lloyd et al., 2017) are not convincing. There is no problem in language learning for which VR is the solution. This doesn’t mean that VR does not have a place in language learning / teaching. VR field trips may offer occasional moments of variety. Conversation in VR worlds like Facebook Spaces may be welcomed by some. And there will be markets for dedicated platforms like Velawoods, Mondly or Immerse.

Predictions about edtech are often thinly disguised attempts to accelerate a predicted future. Four years ago I went to a conference presentation by Saul Nassé, Chief Executive of Cambridge Assessment. All the participants were given a Cambridge branded Google Cardboard. At the time, Nassé wrote the following:

‘The technology is only going to get better and cheaper. In two or three years it will be wireless and cost less than a smart phone. That’s the point when you’ll see whole classrooms equipped with VR. And I like to think we’ll find a way of Cambridge English content being used in those classrooms, with people learning English in a whole new way. It may have been a long time coming, but I think the VR revolution is now truly here to stay’.

The message was echoed in Lloyd et al (2017), all three of whom worked for Cambridge Assessment, and amplified in a series of blog posts and conference presentations around that time. Since then, it has all gone rather quiet. There are still people out there (including the investors who have just pumped $1.5 million into Immerse in Series A funding), who believe that VR will be the next big thing in language learning. But edtech investors have a long track record of turning a blind eye to history. VR, as Saul Nassé observed, ‘has been the next big thing for thirty years’. And maybe for the next thirty years, too.

REFERENCES

Alizadeh, M. (2019). Augmented/virtual reality promises for ELT practitioners. In Clements, P., Krause, A. & Bennett, P. (Eds.), Diversity and inclusion. Tokyo: JALT. https://jalt-publications.org/sites/default/files/pdf-article/jalt2018-pcp-048.pdf

Bonner, E., & Reinders, H. (2018). Augmented and virtual reality in the language classroom: Practical ideas. Teaching English with Technology, 18 (3), pp. 33-53. Retrieved from https://files.eric.ed.gov/fulltext/EJ1186392.pdf

Chen, Y. L. & Hsu, C. C. (2020). Self-regulated mobile game-based English learning in a virtual reality environment. Computers and Education, 154 https://www.sciencedirect.com/science/article/abs/pii/S0360131520301093?dgcid=rss_sd_all

Gadelha, R. (2018). Revolutionizing Education: The promise of virtual reality. Childhood Education, 94 (1), pp. 40-43. doi:10.1080/00094056.2018.1420362

Lan, Y. J. (2020). Immersion, interaction and experience-oriented learning: Bringing virtual reality into FL learning. Language Learning & Technology, 24(1), pp. 1–15. http://hdl.handle.net/10125/44704

Lloyd, A., Rogerson, S. & Stead, G. (2017). Imagining the potential for using Virtual Reality technologies in language learning. In Carrier, M., Damerow, R. M. & Bailey, K. M. (Eds.) Digital Language Learning and Teaching. New York: Routledge. pp. 222 – 234

Mercer, S. & Dörnyei, Z. (2020). Engaging Language Learners in Contemporary Classrooms. Cambridge: Cambridge University Press

Critical data literacy #1: our data and ELT websites

Take the Cambridge Assessment English website, for example. When you connect to the site, you will see, at the bottom of the screen, a familiar (to people in Europe, at least) notification about the site’s use of cookies: the cookies consent.

You probably trust the site, so ignore the notification and quickly move on to find the resource you are looking for. But if you did click on hyperlinked ‘set cookies’, what would you find? The first link takes you to the ‘Cookie policy’ where you will be told that ‘We use cookies principally because we want to make our websites and mobile applications user-friendly, and we are interested in anonymous user behaviour. Generally our cookies don’t store sensitive or personally identifiable information such as your name and address or credit card details’. Scroll down, and you will find out more about the kind of cookies that are used. Besides the cookies that are necessary to the functioning of the site, you will see that there are also ‘third party cookies’. These are explained as follows: ‘Cambridge Assessment works with third parties who serve advertisements or present offers on our behalf and personalise the content that you see. Cookies may be used by those third parties to build a profile of your interests and show you relevant adverts on other sites. They do not store personal information directly but use a unique identifier in your browser or internet device. If you do not allow these cookies, you will experience less targeted content’.

This is not factually inaccurate: personal information is not stored directly. However, it is extremely easy for this information to be triangulated with other information to identify you personally. In addition to the data that you generate by having cookies on your device, Cambridge Assessment will also directly collect data about you. Depending on your interactions with Cambridge Assessment, this will include ‘your name, date of birth, gender, contact data including your home/work postal address, email address and phone number, transaction data including your credit card number when you make a payment to us, technical data including internet protocol (IP) address, login data, browser type and technology used to access this website’. They say they may share this data ‘with other people and/or businesses who provide services on our behalf or at our request’ and ‘with social media platforms, including but not limited to Facebook, Google, Google Analytics, LinkedIn, in pseudonymised or anonymised forms’.

In short, Cambridge Assessment may hold a huge amount of data about you and they can, basically, do what they like with it.

The cookie and privacy policies are fairly standard, as is the lack of transparency in the phrasing of them. Rather more transparency would include, for example, information about which particular ad trackers you are giving your consent to. This information can be found with a browser extension tool like Ghostery, and these trackers can be blocked. As you’ll see below, there are 5 ad trackers on this site. This is rather more than other sites that English language teachers are likely to go to. ETS-TOEFL has 4, Macmillan English and Pearson have 3, CUP ELT and the British Council Teaching English have 1, OUP ELT, IATEFL, BBC Learning English and Trinity College have none. I could only find TESOL, with 6 ad trackers, which has more. The blogs for all these organisations invariably have more trackers than their websites.

The use of numerous ad trackers is probably a reflection of the importance that Cambridge Assessment gives to social media marketing. There is a research paper, produced by Cambridge Assessment, which outlines the significance of big data and social media analytics. They have far more Facebook followers (and nearly 6 million likes) than any other ELT page, and they are proud of their #1 ranking in the education category of social media. The amount of data that can be collected here is enormous and it can be analysed in myriad ways using tools like Ubervu, Yomego and Hootsuite.

A little more transparency, however, would not go amiss. According to a report in Vox, Apple has announced that some time next year ‘iPhone users will start seeing a new question when they use many of the apps on their devices: Do they want the app to follow them around the internet, tracking their behavior?’ Obviously, Google and Facebook are none too pleased about this and will be fighting back. The implications for ad trackers and online advertising, more generally, are potentially huge. I wrote to Cambridge Assessment about this and was pleased to hear that ‘Cambridge Assessment are currently reviewing the process by which we obtain users consent for the use of cookies with the intention of moving to a much more transparent model in the future’. Let’s hope that other ELT organisations are doing the same.

You may be less bothered than I am by the thought of dozens of ad trackers following you around the net so that you can be served with more personalized ads. But the digital profile about you, to which these cookies contribute, may include information about your ethnicity, disabilities and sexual orientation. This profile is auctioned to advertisers when you visit some sites, allowing them to show you ‘personalized’ adverts based on the categories in your digital profile. Contrary to EU regulations, these categories may include whether you have cancer, a substance-abuse problem, your politics and religion (as reported in Fortune https://fortune.com/2019/01/28/google-iab-sensitive-profiles/ ).

But it’s not these cookies that are the most worrying aspect about our lack of digital privacy. It’s the sheer quantity of personal data that is stored about us. Every time we ask our students to use an app or a platform, we are asking them to divulge huge amounts of data. With ClassDojo, for example, this includes names, usernames, passwords, age, addresses, photographs, videos, documents, drawings, or audio files, IP addresses and browser details, clicks, referring URL’s, time spent on site, and page views (Manolev et al., 2019; see also Williamson, 2019).

It is now widely recognized that the ‘consent’ that is obtained through cookie policies and other end-user agreements is largely spurious. These consent agreements, as Sadowski (2019) observes, are non-negotiated, and non-negotiable; you either agree or you are denied access. What’s more, he adds, citing one study, it would take 76 days, working for 8 hours a day, to read the privacy policies a person typically encounters in a year. As a result, most of us choose not to choose when we accept online services (Cobo, 2019: 25). We have little, if any, control over how the data that is collected is used (Birch et al., 2020). More importantly, perhaps, when we ask our students to sign up to an educational app, we are asking / telling them to give away their personal data, not just ours. They are unlikely to fully understand the consequences of doing so.

The extent of this ignorance is also now widely recognized. In the UK, for example, two reports (cited by Sander, 2020) indicate that ‘only a third of people know that data they have not actively chosen to share has been collected’ (Doteveryone, 2018: 5), and that ‘less than half of British adult internet users are aware that apps collect their location and information on their personal preferences’ (Ofcom, 2019: 14).

The main problem with this has been expressed by programmer and activist, Richard Stallman, in an interview with New York magazine (Kulwin, 2018): Companies are collecting data about people. The data that is collected will be abused. That’s not an absolute certainty, but it’s a practical, extreme likelihood, which is enough to make collection a problem.

The abuse that Smallman is referring to can come in a variety of forms. At the relatively trivial end is the personalized advertising. Much more serious is the way that data aggregation companies will scrape data from a variety of sources, building up individual data profiles which can be used to make significant life-impacting decisions, such as final academic grades or whether one is offered a job, insurance or credit (Manolev et al., 2019). Cathy O’Neil’s (2016) best-selling ‘Weapons of Math Destruction’ spells out in detail how this abuse of data increases racial, gender and class inequalities. And after the revelations of Edward Snowden, we all know about the routine collection by states of huge amounts of data about, well, everyone. Whether it’s used for predictive policing or straightforward repression or something else, it is simply not possible for younger people, our students, to know what personal data they may regret divulging at a later date.

Digital educational providers may try to reassure us that they will keep data private, and not use it for advertising purposes, but the reassurances are hollow. These companies may change their terms and conditions further down the line, and examples exist of when this has happened (Moore, 2018: 210). But even if this does not happen, the data can never be secure. Illegal data breaches and cyber attacks are relentless, and education ranked worst at cybersecurity out of 17 major industries in one recent analysis (Foresman, 2018). One report suggests that one in five US schools and colleges have fallen victim to cyber-crime. Two weeks ago, I learnt (by chance, as I happened to be looking at my security settings on Chrome) that my passwords for Quizlet, Future Learn, Elsevier and Science Direct had been compromised by a data breach. To get a better understanding of the scale of data breaches, you might like to look at the UK’s IT Governance site, which lists detected and publicly disclosed data breaches and cyber attacks each month (36.6 million records breached in August 2020). If you scroll through the list, you’ll see how many of them are educational sites. You’ll also see a comment about how leaky organisations have been throughout lockdown … because they weren’t prepared for the sudden shift online.

Recent years have seen a growing consensus that ‘it is crucial for language teaching to […] encompass the digital literacies which are increasingly central to learners’ […] lives’ (Dudeney et al., 2013). Most of the focus has been on the skills that are needed to use digital media. There also appears to be growing interest in developing critical thinking skills in the context of digital media (e.g. Peachey, 2016) – identifying fake news and so on. To a much lesser extent, there has been some focus on ‘issues of digital identity, responsibility, safety and ethics when students use these technologies’ (Mavridi, 2020a: 172). Mavridi (2020b: 91) also briefly discusses the personal risks of digital footprints, but she does not have the space to explore more fully the notion of critical data literacy. This literacy involves an understanding of not just the personal risks of using ‘free’ educational apps and platforms, but of why they are ‘free’ in the first place. Sander (2020b) suggests that this literacy entails ‘an understanding of datafication, recognizing the risks and benefits of the growing prevalence of data collection, analytics, automation, and predictive systems, as well as being able to critically reflect upon these developments. This includes, but goes beyond the skills of, for example, changing one’s social media settings, and rather constitutes an altered view on the pervasive, structural, and systemic levels of changing big data systems in our datafied societies’.

In my next two posts, I will, first of all, explore in more detail the idea of critical data literacy, before suggesting a range of classroom resources.

(I posted about privacy in March 2014, when I looked at the connections between big data and personalized / adaptive learning. In another post, September 2014, I looked at the claims of the CEO of Knewton who bragged that his company had five orders of magnitude more data about you than Google has. … We literally have more data about our students than any company has about anybody else about anything, and it’s not even close. You might find both of these posts interesting.)

References

Birch, K., Chiappetta, M. & Artyushina, A. (2020). ‘The problem of innovation in technoscientific capitalism: data rentiership and the policy implications of turning personal digital data into a private asset’ Policy Studies, 41:5, 468-487, DOI: 10.1080/01442872.2020.1748264

Cobo, C. (2019). I Accept the Terms and Conditions. https://adaptivelearninginelt.files.wordpress.com/2020/01/41acf-cd84b5_7a6e74f4592c460b8f34d1f69f2d5068.pdf

Doteveryone. (2018). People, Power and Technology: The 2018 Digital Attitudes Report. https://attitudes.doteveryone.org.uk

Dudeney, G., Hockly, N. & Pegrum, M. (2013). Digital Literacies. Harlow: Pearson Education

Foresman, B. (2018). Education ranked worst at cybersecurity out of 17 major industries. Edscoop, December 17, 2018. https://edscoop.com/education-ranked-worst-at-cybersecurity-out-of-17-major-industries/

Kulwin, K. (2018). F*ck Them. We Need a Law’: A Legendary Programmer Takes on Silicon Valley, New York Intelligencer, 2018, https://nymag.com/intelligencer/2018/04/richard-stallman-rms-on-privacy-data-and-free-software.html

Manolev, J., Sullivan, A. & Slee, R. (2019). ‘Vast amounts of data about our children are being harvested and stored via apps used by schools’ EduReseach Matters, February 18, 2019. https://www.aare.edu.au/blog/?p=3712

Mavridi, S. (2020a). Fostering Students’ Digital Responsibility, Ethics and Safety Skills (Dress). In Mavridi, S. & Saumell, V. (Eds.) Digital Innovations and Research in Language Learning. Faversham, Kent: IATEFL. pp. 170 – 196

Mavridi, S. (2020b). Digital literacies and the new digital divide. In Mavridi, S. & Xerri, D. (Eds.) English for 21^st Century Skills. Newbury, Berks.: Express Publishing. pp. 90 – 98

Moore, M. (2018). Democracy Hacked. London: Oneworld

Ofcom. (2019). Adults: Media use and attitudes report [Report]. https://www.ofcom.org.uk/__data/assets/pdf_file/0021/149124/adults-media-use-and-attitudes-report.pdf

O’Neil, C. (2016). Weapons of Math Destruction. London: Allen Lane

Peachey, N. (2016). Thinking Critically through Digital Media. http://peacheypublications.com/

Sadowski, J. (2019). ‘When data is capital: Datafication, accumulation, and extraction’ Big Data and Society 6 (1) https://doi.org/10.1177%2F2053951718820549

Sander, I. (2020a). What is critical big data literacy and how can it be implemented? Internet Policy Review, 9 (2). DOI: 10.14763/2020.2.1479 https://www.econstor.eu/bitstream/10419/218936/1/2020-2-1479.pdf

Sander, I. (2020b). Critical big data literacy tools—Engaging citizens and promoting empowered internet usage. Data & Policy, 2: e5 doi:10.1017/dap.2020.5

Williamson, B. (2019). ‘Killer Apps for the Classroom? Developing Critical Perspectives on ClassDojo and the ‘Ed-tech’ Industry’ Journal of Professional Learning, 2019 (Semester 2) https://cpl.asn.au/journal/semester-2-2019/killer-apps-for-the-classroom-developing-critical-perspectives-on-classdojo

Grit: I can do nothing for you, son

from Quartz at Work magazine

 

Grit is on the up. You may have come across articles like ‘How to Be Gritty in the Time of COVID-19’ or ‘Rediscovering the meaning of grit during COVID-19’ . If you still want more, there are new videos from Angela Duckworth herself where we can learn how to find our grit in the face of the pandemic.

Schools and educational authorities love grit. Its simple, upbeat message (‘Yes, you can’) has won over hearts and minds. Back in 2014, the British minister for education announced a £5million plan to encourage teaching ‘character and resilience’ in schools – specifically looking at making Britain’s pupils ‘grittier’. The spending on grit hasn’t stopped since.

The publishers of Duckworth’s book paid a seven-figure sum to acquire the US rights, and sales have proved the wisdom of the investment. Her TED talk has had over 6.5 million views on YouTube, although it’s worth looking at the comments to see why many people have been watching it.

The world of English language teaching, always on the lookout for a new bandwagon to jump onto, is starting to catch up with the wider world of education. Luke Plonsky, an eminent SLA scholar, specialist in meta-analyses and grit enthusiast, has a bibliography of grit studies related to L2 learning, that he deems worthy of consideration. Here’s a summary, by year, of those publications. More details will follow in the next section.

We can expect interest in ‘grit’ to continue growing, and this may be accelerated by the publication this year of Engaging Language Learners in Contemporary Classrooms by Sarah Mercer and Zoltán Dörnyei. In this book, the authors argue that a ‘facilitative mindset’ is required for learner engagement. They enumerate five interrelated principles for developing a ‘facilitative mindset’: promote a sense of competence, foster a growth mindset, promote learners’ sense of ownership and control, develop proactive learners and, develop gritty learners. After a brief discussion of grit, they write: ‘Thankfully, grit can be learnt and developed’ (p.38).

Unfortunately, they don’t provide any evidence at all for this. Unfortunately, too, this oversight is easy to explain. Such evidence as there is does not lend unequivocal support to the claim. Two studies that should have been mentioned in this book are ‘Much ado about grit: A meta-analytic synthesis of the grit literature’ (Credé et al, 2017) and ‘What shall we do about grit? A critical review of what we know and what we don’t know’ (Credé, 2018). The authors found that ‘grit as it is currently measured does not appear to be particularly predictive of success and performance’ (Credé et al, 2017) and that there is no support for the claim that ‘grit is likely to be responsive to interventions’ (Credé, 2018). In the L2 learning context, Teimouri et al (2020) concluded that more research in SLA substantiating the role of grit in L2 contexts was needed before any grit interventions can be recommended.

It has to be said that such results are hardly surprising. If, as Duckworth claims, ‘grit’ is a combination of passion and persistence, how on earth can the passion part of it be susceptible to educational interventions? ‘If there is one thing that cannot be learned, it’s passion. A person can have it and develop it, but learn it? Sadly, not’. (De Bruyckere et al., 2020: 83)

Even Duckworth herself is not convinced. In an interview on a Freakonomics podcast, she states that she hopes it’s something people can learn, but also admits not having enough proof to confirm that they can (Kirschner & Neelen, 2016)!

Is ‘grit’ a thing?

Marc Jones, in a 2016 blog post entitled ‘Gritty Politti: Grit, Growth Mindset and Neoliberal Language Teaching’, writes that ‘Grit is so difficult to define that it takes Duckworth (2016) the best part of a book to describe it adequately’. Yes, ‘grit’ is passion and persistence (or perseverance), but it’s also conscientiousness, practice and hope. Credé et al (2017) found that ‘grit is very strongly correlated with conscientiousness’ (which has already been widely studied in the educational literature). Why lump this together with passion? Another study (Muenks et al., 2017) found that ‘Students’ grit overlapped empirically with their concurrently reported self-control, self-regulation, and engagement. Students’ perseverance of effort (but not their consistency of interests) predicted their later grades, although other self-regulation and engagement variables were stronger predictors of students’ grades than was grit’. Credé (2018) concluded that ‘there appears to be no reason to accept the combination of perseverance and passion for long-term goals into a single grit construct’.

The L2 learning research listed in Plonsky’s bibliography does not offer much in support of ‘grit’, either. Many of the studies identified problems with ‘grit’ as a construct, but, even when accepting it, did not find it to be of much value. Wei et al. (2019) found a positive but weak correlation between grit and English language course grades. Yamashita (2018) found no relationship between learners’ grit and their course grades. Taşpinar & Külekçi (2018) found that students’ grit levels and academic achievement scores did not relate to each other (but still found that ‘grit, perseverance, and tenacity are the essential elements that impact learners’ ability to succeed to be prepared for the demands of today’s world’!).

There are, then, grounds for suspecting that Duckworth and her supporters have fallen foul of the ‘jangle fallacy’ – the erroneous assumption that two identical or almost identical things are different because they are labelled differently. This would also help to explain the lack of empirical support for the notion of ‘grit’. Not only are the numerous variables insufficiently differentiated, but the measures of ‘grit’ (such as Duckworth’s Grit-S measure) do not adequately target some of these variables (e.g. long-term goals, where ‘long-term’ is not defined) (Muenks et al., 2017). In addition, these measures are self-reporting and not, therefore, terribly reliable.

Referring to more general approaches to character education, one report (Gutman & Schoon, 2012) has argued that there is little empirical evidence of a causal relationship between self-concept and educational outcomes. Taking this one step further, Kathryn Ecclestone (Ecclestone, 2012) suggests that at best, the concepts and evidence that serve as the basis of these interventions are inconclusive and fragmented; ‘at worst, [they are] prey to ‘advocacy science’ or, in [their] worst manifestations, to simple entrepreneurship that competes for publicly funded interventions’ (cited in Cabanas & Illouz, 2019: 80).

Criticisms of ‘grit’

Given the lack of supporting research, any practical application of ‘grit’ ideas is premature. Duckworth herself, in an article entitled ‘Don’t Believe the Hype About Grit, Pleads the Scientist Behind the Concept’ (Dahl, 2016), cautions against hasty applications:

[By placing too much emphasis on grit, the danger is] that grit becomes a scapegoat — another reason to blame kids for not doing well, or to say that we don’t have a responsibility as a society to help them. [She worries that some interpretations of her work might make a student’s failure seem like his problem, as if he just didn’t work hard enough.] I think to separate and pit against each other character strengths on the one hand — like grit — and situational opportunities on the other is a false dichotomy […] Kids need to develop character, and they need our support in doing so.

Marc Jones, in the blog mentioned above, writes that ‘to me, grit is simply another tool for attacking the poor and the other’. You won’t win any prizes for guessing which kinds of students are most likely to be the targets of grit interventions. A clue: think of the ‘no-nonsense’ charters in the US and academies in the UK. This is what Kenneth Saltzman has to say:

‘Grit’ is a pedagogy of control that is predicated upon a promise made to poor children that if they learnt the tools of self-control and learnt to endure drudgery, then they can compete with rich children for scarce economic resources. (Saltzman, 2017: 38)

[It] is a behaviourist form of learned self-control targeting poor students of color and has been popularized post-crisis in the wake of educational privatization and defunding as the cure for poverty. [It] is designed to suggest that individual resilience and self-reliance can overcome social violence and unsupportive social contexts in the era of the shredded social state. (Saltzman, 2017: 15)

Grit is misrepresented by proponents as opening a world of individual choices rather than discussed as a mode of educational and social control in the austere world of work defined by fewer and fewer choices as secure public sector work is scaled back, unemployment continuing at high levels. (Saltzman, 2017: 49)

Whilst ‘grit’ is often presented as a way of dealing with structural inequalities in schools, critics see it as more of a problem than a solution: ‘It’s the kids who are most impacted by, rebel against, or criticize the embedded racism and classism of their institutions that are being told to have more grit, that school is hard for everyone’ (EquiTEA, 2018). A widely cited article by Nicholas Tampio (2016) points out that ‘Duckworth celebrates educational models such as Beast at West Point that weed out people who don’t obey orders’. He continues ‘that is a disastrous model for education in a democracy. US schools ought to protect dreamers, inventors, rebels and entrepreneurs – not crush them in the name of grit’.

If you’re interested in reading more critics of grit, the blog ‘Debunked!’ is an excellent source of links.

Measuring grit

Analyses of emotional behaviour have become central to economic analysis and, beginning in the 1990s, there have been constant efforts to create ‘formal instruments of classification of emotional behaviour and the elaboration of the notion of emotional competence’ (Illouz, 2007: 64). The measurement and manipulation of various aspects of ‘emotional intelligence’ have become crucial as ways ‘to control, predict, and boost performance’ (Illouz, 2007: 65). An article in the Journal of Benefit-Cost Analysis (Belfield et al., 2015) makes the economic importance of emotions very clear. Entitled ‘The Economic Value of Social and Emotional Learning’, it examines the economic value of these skills within a benefit-cost analysis (BCA) framework, and finds that the benefits of [social and emotional learning] interventions substantially outweigh the costs.

In recent years, the OECD has commissioned a number of reports on social and emotional learning and, as with everything connected with the OECD, is interested in measuring ‘non-cognitive skills such as perseverance (“grit”), conscientiousness, self-control, trust, attentiveness, self-esteem and self-efficacy, resilience to adversity, openness to experience, empathy, humility, tolerance of diverse opinions and the ability to engage productively in society’ (Kautz et al., 2014: 9). The measurement of personality factors will feature in the OECD’s PISA programme. Elsewhere, Ben Williamson reports that ‘US schools [are] now under pressure—following the introduction of the Every Student Succeeds Act in 2015—to provide measurable evidence of progress on the development of students’ non-academic learning’ (Williamson, 2017).

Grit, which ‘starts and ends with the lone individual as economic actor, worker, and consumer’ (Saltzman, 2017: 50), is a recent addition to the categories of emotional competence, and it should come as no surprise that educational authorities have so wholeheartedly embraced it. It is the claim that something (i.e. ‘grit’) can be taught and developed that leads directly to the desire to measure it. In a world where everything must be accountable, we need to know how effective and cost-effective our grit interventions have been.

The idea of measuring personality constructs like ‘grit’ worries even Angela Duckworth. She writes (Duckworth, 2016):

These days, however, I worry I’ve contributed, inadvertently, to an idea I vigorously oppose: high-stakes character assessment. New federal legislation can be interpreted as encouraging states and schools to incorporate measures of character into their accountability systems. This year, nine California school districts will begin doing this. But we’re nowhere near ready — and perhaps never will be — to use feedback on character as a metric for judging the effectiveness of teachers and schools. We shouldn’t be rewarding or punishing schools for how students perform on these measures.

Diane Ravitch (Ravitch, 2016) makes the point rather more forcefully: ‘The urge to quantify the unmeasurable must be recognized for what it is: stupid; arrogant; harmful; foolish, yet another way to standardize our beings’. But, like it or not, attempts to measure ‘grit’ and ‘grit’ interventions are unlikely to go away any time soon.

‘Grit’ and technology

Whenever there is talk about educational measurement and metrics, we are never far away from the world of edtech. It may not have escaped your notice that the OECD and the US Department of State for Education, enthusiasts for promoting ‘grit’, are also major players in the promotion of the datafication of education. The same holds true for organisations like the World Education Forum, the World Bank and the various philanthro-capitalist foundations to which I have referred so often in this blog. Advocacy of social and emotional learning goes hand in hand with edtech advocacy.

Two fascinating articles by Ben Williamson (2017; 2019) focus on ClassDojo, which, according to company information, reaches more than 10 million children globally every day. The founding directors of ClassDojo, writes Ben Williamson (2017), ‘explicitly describe its purpose as promoting ‘character development’ in schools and it is underpinned by particular psychological concepts from character research. Its website approvingly cites the journalist Paul Tough, author of two books on promoting ‘grit’ and ‘character’ in children, and is informed by character research conducted with the US network of KIPP charter schools (Knowledge is Power Program)’. In a circular process, ClassDojo has also ‘helped distribute and popularise concepts such as growth mindset, grit and mindfulness’ (Williamson, 2019).

The connections between ‘grit’ and edtech are especially visible when we focus on Stanford and Silicon Valley. ClassDojo was born in Palo Alto. Duckworth was a consulting scholar at Stanford 2014 -15, where Carol Dweck is a Professor of Psychology. Dweck is the big name behind growth mindset theory, which, as Sarah Mercer and Zoltán Dörnyei indicate, is closely related to ‘grit’. Dweck is also the co-founder of MindsetWorks, whose ‘Brainology’ product is ‘an online interactive program in which middle school students learn about how the brain works, how to strengthen their own brains, and how to ….’. Stanford is also home to the Stanford Lytics Lab, ‘which has begun applying new data analytics techniques to the measurement of non-cognitive learning factors including perseverance, grit, emotional state, motivation and self-regulation’, as well as the Persuasive Technologies Lab, ‘which focuses on the development of machines designed to influence human beliefs and behaviors across domains including health, business, safety, and education’ (Williamson, 2017). The Professor of Education Emeritus at Stanford is Linda Darling-Hammond, one of the most influential educators in the US. Darling-Hammond is known, among many other things, for collaborating with Pearson to develop the edTPA, ‘a nationally available, performance-based assessment for measuring the effectiveness of teacher candidates’. She is also a strong advocate of social-emotional learning initiatives and extols the virtues of ‘developing grit and a growth mindset’ (Hamadi & Darling-Hammond, 2015).

The funding of grit

Angela Duckworth’s Character Lab (‘Our mission is to advance scientific insights that help kids thrive’) is funded by, among others, the Chan Zuckerberg Initiative, the Bezos Family Foundation and Stanford’s Mindset Scholars Network. Precisely how much money Character Lab has is difficult to ascertain, but the latest grant from the Chan Zuckerberg Initiative was worth $1,912,000 to cover the period 2018 – 2021. Covering the same period, the John Templeton Foundation, donated $3,717,258 , the purpose of the grant being to ‘make character development fast, frictionless, and fruitful’.

In an earlier period (2015 – 2018), the Walton Family Foundation pledged $6.5 million ‘to promote and measure character education, social-emotional learning, and grit’, with part of this sum going to Character Lab and part going to similar research at Harvard Graduate School of Education. Character Lab also received $1,300,000 from the Overdeck Family Foundation for the same period.

It is not, therefore, an overstatement to say that ‘grit’ is massively funded. The funders, by and large, are the same people who have spent huge sums promoting personalized learning through technology (see my blog post Personalized learning: Hydra and the power of ambiguity). Whatever else it might be, ‘grit’ is certainly ‘a commercial tech interest’ (as Ben Williamson put it in a recent tweet).

Postscript

In the 2010 Cohen brothers’ film, ‘True Grit’, the delinquent ‘kid’, Moon, is knifed by his partner, Quincy. Turning to Rooster Cogburn, the man of true grit, Moon begs for help. In response, Cogburn looks at the dying kid and deadpans ‘I can do nothing for you, son’.

References

Belfield, C., Bowden, A., Klapp, A., Levin, H., Shand, R., & Zander, S. (2015). The Economic Value of Social and Emotional Learning. Journal of Benefit-Cost Analysis, 6(3), pp. 508-544. doi:10.1017/bca.2015.55

Cabanas, E. & Illouz, E. (2019). Manufacturing Happy Citizens. Cambridge: Polity Press.

Chaykowski, K. (2017). How ClassDojo Built One Of The Most Popular Classroom Apps By Listening To Teachers. Forbes, 22 May, 2017. https://www.forbes.com/sites/kathleenchaykowski/2017/05/22/how-classdojo-built-one-of-the-most-popular-classroom-apps-by-listening-to-teachers/#ea93d51e5ef5

Credé, M. (2018). What shall we do about grit? A critical review of what we know and what we don’t know. Educational Researcher, 47(9), 606-611.

Credé, M., Tynan, M. C., & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492. doi:10.1037/pspp0000102

Dahl, M. (2016). Don’t Believe the Hype About Grit, Pleads the Scientist Behind the Concept. The Cut, May 9, 2016. https://www.thecut.com/2016/05/dont-believe-the-hype-about-grit-pleads-the-scientist-behind-the-concept.html

De Bruyckere, P., Kirschner, P. A. & Hulshof, C. (2020). More Urban Myths about Learning and Education. Routledge.

Duckworth, A. (2016). Don’t Grade Schools on Grit. New York Times, March 26, 2016 https://www.nytimes.com/2016/03/27/opinion/sunday/dont-grade-schools-on-grit.html?auth=login-google&smid=nytcore-ipad-share&smprod=nytcore-ipad

Ecclestone, K. (2012). From emotional and psychological well-being to character education: Challenging policy discourses of behavioural science and ‘vulnerability’. Research Papers in Education, 27 (4), pp. 463-480

EquiTEA (2018). The Problem with Teaching ‘Grit’. Medium, 11 December 2018. https://medium.com/@eec/the-problem-with-teaching-grit-8b37ce43a87e

Gutman, L. M. & Schoon, I. (2013). The impact of non-cognitive skills on outcomes for young people: Literature review. London: Institute of Education, University of London

Hamedani, M. G. & Darling-Hammond, L. (2015). Social Emotional Learning in High School: How Three Urban High Schools Engage, Educate, and Empower Youth. Stanford Center for Opportunity Policy in Education

Kirschner, P.A. & Neelen, M. (2016). To Grit Or Not To Grit: That’s The Question. 3-Star Learning Experiences, July 5, 2016 https://3starlearningexperiences.wordpress.com/2016/07/05/to-grit-or-not-to-grit-thats-the-question/

Illouz, E. (2007). Cold Intimacies: The making of emotional capitalism. Cambridge: Polity Press

Kautz, T., Heckman, J. J., Diris, R., ter Weel, B & Borghans, L. (2014). Fostering and Measuring Skills: Improving Cognitive and Non-cognitive Skills to Promote Lifetime Success. OECD Education Working Papers 110, OECD Publishing.

Mercer, S. & Dörnyei, Z. (2020). Engaging Language Learners in Contemporary Classrooms. Cambridge University Press.

Muenks, K., Wigfield, A., Yang, J. S., & O’Neal, C. R. (2017). How true is grit? Assessing its relations to high school and college students’ personality characteristics, self-regulation, engagement, and achievement. Journal of Educational Psychology, 109, pp. 599–620.

Ravitch, D. (2016). Angela Duckworth, please don’t assess grit. Blog post, 27 March 2016, https://dianeravitch.net/2016/03/27/angela-duckworth-please-dont-assess-grit/

Saltzman, K. J. (2017). Scripted Bodies. Routledge.

Tampio, N. (2016). Teaching ‘grit’ is bad for children, and bad for democracy. Aeon, 2 June: https://aeon.co/ideas/teaching-grit-is-bad-for-children-and-bad-for-democracy

Taşpinar, K., & Külekçi, G. (2018). GRIT: An Essential Ingredient of Success in the EFL Classroom. International Journal of Languages’ Education and Teaching, 6, 208-226.

Teimouri, Y., Plonsky, L., & Tabandeh, F. (2020). L2 Grit: Passion and perseverance for second-language learning. Language Teaching Research.

Wei, H., Gao, K., & Wang, W. (2019). Understanding the relationship between grit and foreign language performance among middle schools students: The roles of foreign language enjoyment and classroom Environment. Frontiers in Psychology, 10, 1508. doi: 10.3389/fpsyg.2019.01508

Williamson, B. (2017). Decoding ClassDojo: psycho-policy, social-emotional learning and persuasive educational technologies. Learning, Media and Technology, 42 (4): pp. 440-453, DOI: 10.1080/17439884.2017.1278020

Williamson, B. (2019). ‘Killer Apps for the Classroom? Developing Critical Perspectives on ClassDojo and the ‘Ed-tech’ Industry. Journal of Professional Learning, 2019 (Semester 2) https://cpl.asn.au/journal/semester-2-2019/killer-apps-for-the-classroom-developing-critical-perspectives-on-classdojo

Yamashita, T. (2018). Grit and second language acquisition: Can passion and perseverance predict performance in Japanese language learning? Unpublished MA thesis, University of Massachusetts, Amherst.

 

Critical digital illiteracy – reading about EdTech

The ‘Routledge Handbook of Language Learning and Technology’ (eds. Farr and Murray, 2016) claims to be ‘the essential reference’ on the topic and its first two sections are devoted to ‘Historical and conceptual concepts’ and ‘Core issues’. One chapter (‘Limitations and boundaries in language learning and technology’ by Kern and Malinowski) mentions that ‘a growing body of research in intercultural communication and online language learning recognises how all technologies are embedded in cultural and linguistic practices, meaning that a given technological artefact can be used in radically different ways, and for different purposes by different groups of people’ (p.205). However, in terms of critical analyses of technology and language learning, that’s about as far as this book goes. In over 500 pages, there is one passing reference to privacy and a couple of brief mentions of the digital divide. There is no meaningful consideration of the costs, ownership or externalities of EdTech, of the ways in which EdTech is sold and marketed, of the vested interests that profit from EdTech, of the connections between EdTech and the privatisation of education, of the non-educational uses to which data is put, or of the implications of attention tracking, facial analysis and dataveillance in educational settings.

The Routledge Handbook is not alone in this respect. Li Li’s ‘New Technologies and Language Learning’ (Palgrave, 2017) is breathlessly enthusiastic about the potential of EdTech. The opening chapter catalogues a series of huge investments in global EdTech, as if the scale of investment was an indication of its wisdom. No mention of the lack of evidence that huge investments into IWBs and PCs in classrooms led to any significant improvement in learning. No mention of how these investments were funded (or which other parts of budgets were cut). Instead, we are told that ‘computers can promote visual, verbal and kinaesthetic learning’ (p.5).

I have never come across a book-length critical analysis of technology and language learning. As the world of language teaching jumps on board Zoom, Google Meet, Microsoft Teams, Skype (aka Microsoft) and the like, the need for a better critical awareness of EdTech and language learning has never been more urgent. Fortunately, there is a growing body of critical literature on technology and general education. Here are my twelve favourites:

1 Big Data in Education

Ben Williamson (Sage, 2017)

An investigation into the growing digitalization and datafication of education. Williamson looks at how education policy is enacted through digital tools, the use of learning analytics and educational data science. His interest is in the way that technology has reshaped the way we think about education and the book may be read as a critical response to the techno-enthusiasm of Mayer-Schönberger and Cukier’s ‘Learning with Big Data: The Future of Education’ (Houghton Mifflin Harcourt, 2014). Williamson’s blog, Code Acts in Education, is excellent.

 

2 Distrusting Educational Technology

Neil Selwyn (Routledge, 2014)

Neil Selwyn is probably the most widely-quoted critical voice in this field, and this book is as good a place to start with his work as any. EdTech, for Selwyn, is a profoundly political affair, and this book explores the gulf between how it could be used, and how it is actually used. Unpacking the ideological agendas of what EdTech is and does, Selwyn covers the reduction of education along data-driven lines, the deskilling of educational labour, the commodification of learning, issues of inequality, and much more. An essential primer.

 

 

3 The Great American Education-Industrial Complex

Anthony G. Picciano & Joel Spring (Routledge, 2013)

Covering similar ground to both ‘Education Networks’ and ‘Edu.net’ (see below), this book’s subtitle, ‘Ideology, Technology, and Profit’, says it all. Chapter 4 (‘Technology in American Education’) is of particular interest, tracing the recent history of EdTech and the for-profit sector. Chapter 5 provides a wide range of examples of the growing privatization (through EdTech) of American schooling.

 

 

4 Disruptive Fixation

Christo Sims (Princeton University Press, 2017)

The story of a New York school, funded by philanthropists and put together by games designers and educational reformers, that promised to ‘reinvent the classroom for the digital age’. And how it all went wrong … reverting to conventional rote learning with an emphasis on discipline, along with gender and racialized class divisions. A cautionary tale about techno-philanthropism.

 

 

5 Education Networks

Joel Spring (Routledge, 2012)

Similar in many ways to ‘Edu.net’ (see below), this is an analysis of the relationships between the interest groups (international agencies, private companies and philanthropic foundations) that are pushing for greater use of EdTech. Spring considers the psychological, social and political implications of the growth of EdTech and concludes with a discussion of the dangers of consumerist approaches to education and dataveillance.

 

 

6 Edu.net

Stephen J. Ball, Carolina Junemann & Diego Santori (Routledge, 2017)

An account of the ways in which international agencies, private companies (e.g. Bridge International Academies, Pearson) and philanthropic foundations shape global education policies, with a particular focus on India and Ghana. These policies include the standardisation of education, the focus on core subjects, the use of corporate management models and test-based accountability, and are key planks in what has been referred to as the Global Education Reform Movement (GERM). Chapter 4 (‘Following things’) focusses on the role of EdTech in realising GERM goals.

 

7 Education and Technology

Neil Selwyn (Continuum, 2011)

Although covering some similar ground to his ‘Distrusting Educational Technology’, this handy volume summarises key issues, including ‘does technology inevitably change education?’, ‘what can history tell us about education and technology?’, ‘does technology improve learning?’, ‘does technology make education fairer?’, ‘will technology displace the teacher?’ and ‘will technology displace the school?’.

 

 

8 The Evolution of American Educational Technology

Paul Saettler (Information Age, 2004)

A goldmine of historical information, this is the first of three history books on my list. Early educational films from the start of the 20^th century, educational radio, teaching machines and programmed instruction, early computer-assisted instruction like the PLATO project, educational broadcasting and television … moving on to interactive video, teleconferencing, and artificial intelligence. A fascinatingly detailed study of educational dreams and obsolescence.

 

9 Oversold and Underused

Larry Cuban (Harvard University Press, 2003)

Larry Cuban’s ground-breaking ‘Teachers and Machines: The Classroom Use of Technology since 1920’ (published in 1986, four years before Saettler’s history) was arguably the first critical evaluation of EdTech. In this title, Cuban pursues his interest in the troubled relationship between teachers and technology, arguing that more attention needs to be paid to the civic and social goals of schooling, goals that make the question of how many computers are in classrooms trivial. Larry Cuban’s blog is well worth following.

 

10 The Flickering Mind

Todd Oppenheimer (Random House, 2003)

A journalistic account of how approximately $70 billion was thrown at EdTech in American schools at the end of the 20^th century in an attempt to improve them. It’s a tale of getting the wrong priorities, technological obsolescence and, ultimately, a colossal waste of money. Technology has changed since the writing of this book, but as the epigram of Alphonse Karr (cited by Oppenheimer in his afterword) puts it – ‘plus ça change, plus c’est la même chose’.

 

 

11 Teaching Machines

Bill Ferster (John Hopkins University Press, 2014)

This is the third history of EdTech on my list. A critical look at past attempts to automate instruction, and learning from successes and failures as a way of trying to avoid EdTech insanity (‘doing the same thing over and over again and expecting different results’). Not explicitly political, but the final chapter offers a useful framework for ‘making sense of teaching machines’.

 

 

12 The Technical Fix

Kevin Robbins & Frank Webster (Macmillan, 1989)

Over thirty years old now, this remarkably prescient book situates the push for more EdTech in Britain in the 1980s as a part of broader social and political forces demanding a more market-oriented and entrepreneurial approach to education. The argument that EdTech cannot be extracted from relations of power and the social values that these entail is presented forcefully. Technology, write the authors, ‘is always shaped by, even constitutive of, prevailing values and power distribution’.

 

 

And here’s hoping that Audrey Watters’ new book sees the light of day soon, so it can be added to the list of history books!

 

 

 

 

 

 

Life skills, technology, teacher evaluation and the World Bank

If you cast your eye over the English language teaching landscape, you can’t help noticing a number of prominent features that weren’t there, or at least were much less visible, twenty years ago. I’d like to highlight three. First, there is the interest in life skills (aka 21^st century skills). Second, there is the use of digital technology to deliver content. And third, there is a concern with measuring educational outputs through frameworks such as the Pearson GSE. In this post, I will focus primarily on the last of these, with a closer look at measuring teacher performance.

Recent years have seen the development of a number of frameworks for evaluating teacher competence in ELT. These include

• The British Council CPD Framework
• The Cambridge English Teaching Framework
• The EAQUALS Framework for Language Teacher Training and Development
• The TESOL Technology Standards Framework

TESOL has also produced a set of guidelines for developing professional teaching standards for EFL.

Frameworks such as these were not always intended as tools to evaluate teachers. The British Council’s framework, for example, was apparently designed for teachers to understand and plan their own professional development. Similarly, the Cambridge framework says that it is for teachers to see where they are in their development – and think about where they want to go next. But much like the CEFR for language competence, frameworks can be used for purposes rather different from their designers’ intentions. I think it is likely that frameworks such as these are more often used to evaluate teachers than for teachers to evaluate themselves.

But where did the idea for such frameworks come from? Was there a suddenly perceived need for things like this to aid in self-directed professional development? Were teachers’ associations calling out for frameworks to help their members? Even if that were the case, it would still be useful to know why, and why now.

One possibility is that the interest in life skills, digital technology and the measurement of educational outputs have all come about as a result of what has been called the Global Educational Reform Movement, or GERM (Sahlberg, 2016). GERM dates back to the 1980s and the shifts (especially in the United States under Reagan and the United Kingdom under Thatcher) in education policy towards more market-led approaches which emphasize (1) greater competition between educational providers, (2) greater autonomy from the state for educational providers (and therefore a greater role for private suppliers), (3) greater choice of educational provider for students and their parents, and (4) standardized tests and measurements which allow consumers of education to make more informed choices. One of the most significant GERM vectors is the World Bank.

The interest in incorporating the so-called 21^st century skills as part of the curriculum can be traced back to the early 1980s when the US National Commission on Excellence in Education recommended the inclusion of a range of skills, which eventually crystallized into the four Cs of communication, collaboration, critical thinking and creativity. The labelling of this skill set as ‘life skills’ or ‘21^st century skills’ was always something of a misnomer: the reality was that these were the soft skills required by the world of work. The key argument for their inclusion in the curriculum was that they were necessary for the ‘competitiveness and wealth of corporations and countries’ (Trilling & Fadel, 2009: 7). Unsurprisingly, the World Bank, whose interest in education extends only so far as its economic value, embraced the notion of ‘life skills’ with enthusiasm. Its document ‘Life skills : what are they, why do they matter, and how are they taught?’ (World Bank, 2013), makes the case very clearly. It took a while for the world of English language teaching to get on board, but by 2012, Pearson was already sponsoring a ‘signature event’ at IATEFL Glasgow entitled ‘21st Century Skills for ELT’. Since then, the currency of ‘life skills’ as an ELT buzz phrase has not abated.

Just as the World Bank’s interest in ‘life skills’ is motivated by the perceived need to prepare students for the world of work (for participation in the ‘knowledge economy’), the Bank emphasizes the classroom use of computers and resources from the internet: Information and communication technology (ICT) allows the adaptation of globally available information to local learning situations. […] A large percentage of the World Bank’s education funds are used for the purchase of educational technology. […] According to the Bank’s figures, 40 per cent of their education budget in 2000 and 27 per cent in 2001 was used to purchase technology. (Spring, 2015: 50).

Digital technology is also central to capturing data, which will allow for the measurement of educational outputs. As befits an organisation of economists that is interested in the cost-effectiveness of investments into education, it accords enormous importance to what are thought to be empirical measures or accountability. So intrinsic to the Bank’s approach is this concern with measurement that ‘the Bank’s implicit message to national governments seems to be: ‘improve your data collection capacity so that we can run more reliable cross-country analysis and regressions’. (Verger & Bonal, 2012: 131).

Measuring the performance of teachers is, of course, a part of assessing educational outputs. The World Bank, which sees global education as fundamentally ‘broken’, has, quite recently, turned more of its attention to the role of teachers. A World Bank blog from 2019 explains the reasons:

A growing body of evidence suggests the learning crisis is, at its core, a teaching crisis. For students to learn, they need good teachers—but many education systems pay little attention to what teachers know, what they do in the classroom, and in some cases whether they even show up. Rapid technological change is raising the stakes. Technology is already playing a crucial role in providing support to teachers, students, and the learning process more broadly. It can help teachers better manage the classroom and offer different challenges to different students. And technology can allow principals, parents, and students to interact seamlessly.

A key plank in the World Banks’s attempts to implement its educational vision is its System Assessment and Benchmarking for Education Results (SABER), which I will return to in due course. As part of its SABER efforts, last year the World Bank launched its ‘Teach’ tool . This tool is basically an evaluation framework. Videos of lessons are recorded and coded for indicators of teacher efficiency by coders who can be ‘90% reliable’ after only four days of training. The coding system focuses on the time that students spend on-task, but also ‘life skills’ like collaboration and critical thinking (see below).

Like the ELT frameworks, it can be used as a professional development tool, but, like them, it may also be used for summative evaluation.

The connections between those landmarks on the ELT landscape and the concerns of the World Bank are not, I would suggest, coincidental. The World Bank is, of course, not the only player in GERM, but it is a very special case. It is the largest single source of external financing in ‘developing countries’ (Beech, 2009: 345), managing a portfolio of $8.9 billion, with operations in 70 countries as of August 2013 (Spring, 2015: 32). Its loans come attached with conditions which tie the borrowing countries to GERM objectives. Arguably of even greater importance than its influence through funding, is the Bank’s direct entry into the world of ideas:

The Bank yearns for a deeper and more comprehensive impact through avenues of influence transcending both project and program loans. Not least in education, the World Bank is investing much in its quest to shape global opinion about economic, developmental, and social policy. Rather than imposing views through specific loan negotiations, Bank style is broadening in attempts to lead borrower country officials to its preferred way of thinking. (Jones, 2007: 259).

The World Bank sees itself as a Knowledge Bank and acts accordingly. Rizvi and Lingard (2010: 48) observe that ‘in many nations of the Global South, the only extant education policy analysis is research commissioned by donor agencies such as the World Bank […] with all the implications that result in relation to problem setting, theoretical frameworks and methodologies’. Hundreds of academics are engaged to do research related to the Bank’s areas of educational interest, and ‘the close links with the academic world give a strong credibility to the ideas disseminated by the Bank […] In fact, many ideas that acquired currency and legitimacy were originally proposed by them. This is the case of testing students and using the results to evaluate progress in education’ (Castro, 2009: 472).

Through a combination of substantial financial clout and relentless marketing (Selwyn, 2013: 50), the Bank has succeeded in shaping global academic discourse. In partnership with similar institutions, it has introduced a way of classifying and thinking about education (Beech, 2009: 352). It has become, in short, a major site ‘for the organization of knowledge about education’ (Rizvi & Lingard, 2010: 79), wielding ‘a degree of power that has arguably enabled it to shape the educational agendas of nations throughout the Global South’ and beyond (Menashy, 2012).

So, is there any problem in the world of ELT taking up the inclusion of ‘life skills’? I think there is. The first is one of definition. Creativity and critical thinking are very poorly defined, meaning very different things to different people, so it is not always clear what is being taught. Following on from this, there is substantial debate about whether such skills can actually be taught at all, and, if they can, how they should be taught. It seems highly unlikely that the tokenistic way in which they are ‘taught’ in most published ELT courses can be of any positive impact. But this is not my main reservation, which is that, by and large, we have come to uncritically accept the idea that English language learning is mostly concerned with preparation for the workplace (see my earlier post ‘The EdTech Imaginary in ELT’).

Is there any problem with the promotion of digital technologies in ELT? Again, I think there is, and a good proportion of the posts on this blog have argued for the need for circumspection in rolling out more technology in language learning and teaching. My main reason is that while it is clear that this trend is beneficial to technology vendors, it is much less clear that advantages will necessarily accrue to learners. Beyond this, there must be serious concerns about data ownership, privacy, and the way in which the datafication of education, led by businesses and governments in the Global North, is changing what counts as good education, a good student or an effective teacher, especially in the Global South. ‘Data and metrics,’ observe Williamson et al. (2020: 353), ‘do not just reflect what they are designed to measure, but actively loop back into action that can change the very thing that was measured in the first place’.

And what about tools for evaluating teacher competences? Here I would like to provide a little more background. There is, first of all, a huge question mark about how accurately such tools measure what they are supposed to measure. This may not matter too much if the tool is only used for self-evaluation or self-development, but ‘once smart systems of data collection and social control are available, they are likely to be widely applied for other purposes’ (Sadowski, 2020: 138). Jaime Saavedra, head of education at the World Bank, insists that the World Bank’s ‘Teach’ tool is not for evaluation and is not useful for firing teachers who perform badly.

Saavedra needs teachers to buy into the tool, so he obviously doesn’t want to scare them off. However, ‘Teach’ clearly is an evaluation tool (if not, what is it?) and, as with other tools (I’m thinking of CEFR and teacher competency frameworks in ELT), its purposes will evolve. Eric Hanushek, an education economist at Stanford University, has commented that ‘this is a clear evaluation tool at the probationary stage … It provides a basis for counseling new teachers on how they should behave … but then again if they don’t change over the first few years you also have information you should use’.

At this point, it is useful to take a look at the World Bank’s attitudes towards teachers. Teachers are seen to be at the heart of the ‘learning crisis’. However, the greatest focus in World Bank documents is on (1) teacher absenteeism in some countries, (2) unskilled and demotivated teachers, and (3) the reluctance of teachers and their unions to back World Bank-sponsored reforms. As real as these problems are, it is important to understand that the Bank has been complicit in them:

For decades, the Bank has criticised pre-service and in-service teacher training as not cost-effective For decades, the Bank has been pushing the hiring of untrained contract teachers as a cheap fix and a way to get around teacher unions – and contract teachers are again praised in the World Bank Development Report (WDR). This contradicts the occasional places in the WDR in which the Bank argues that developing countries need to follow the lead of the few countries that attract the best students to teaching, improve training, and improve working conditions. There is no explicit evidence offered at all for the repeated claim that teachers are unmotivated and need to be controlled and monitored to do their job. The Bank has a long history of blaming teachers and teacher unions for educational failures. The Bank implicitly argues that the problem of teacher absenteeism, referred to throughout the report, means teachers are unmotivated, but that simply is not true. Teacher absenteeism is not a sign of low motivation. Teacher salaries are abysmally low, as is the status of teaching. Because of this, teaching in many countries has become an occupation of last resort, yet it still attracts dedicated teachers. Once again, the Bank has been very complicit in this state of affairs as it, and the IMF, for decades have enforced neoliberal, Washington Consensus policies which resulted in government cutbacks and declining real salaries for teachers around the world. It is incredible that economists at the Bank do not recognise that the deterioration of salaries is the major cause of teacher absenteeism and that all the Bank is willing to peddle are ineffective and insulting pay-for-performance schemes. (Klees, 2017).

The SABER framework (referred to above) focuses very clearly on policies for hiring, rewarding and firing teachers.

[The World Bank] places the private sector’s methods of dealing with teachers as better than those of the public sector, because it is more ‘flexible’. In other words, it is possible to say that teachers can be hired and fired more easily; that is, hired without the need of organizing a public competition and fired if they do not achieve the expected outcomes as, for example, students’ improvements in international test scores. Further, the SABER document states that ‘Flexibility in teacher contracting is one of the primary motivations for engaging the private sector’ (World Bank, 2011: 4). This affirmation seeks to reduce expenditures on teachers while fostering other expenses such as the creation of testing schemes and spending more on ICTs, as well as making room to expand the hiring of private sector providers to design curriculum, evaluate students, train teachers, produce education software, and books. (De Siqueira, 2012).

The World Bank has argued consistently for a reduction of education costs by driving down teachers’ salaries. One of the authors of the World Bank Development Report 2018 notes that ‘in most countries, teacher salaries consume the lion’s share of the education budget, so there are already fewer resources to implement other education programs’. Another World Bank report (2007) makes the importance of ‘flexible’ hiring and lower salaries very clear:

In particular, recent progress in primary education in Francophone countries resulted from reduced teacher costs, especially through the recruitment of contractual teachers, generally at about 50% the salary of civil service teachers. (cited in Compton & Weiner, 2008: 7).

Merit pay (or ‘pay for performance’) is another of the Bank’s preferred wheezes. Despite enormous problems in reaching fair evaluations of teachers’ work and a distinct lack of convincing evidence that merit pay leads to anything positive (and may actually be counter-productive) (De Bruyckere et al., 2018: 143 – 147), the Bank is fully committed to the idea. Perhaps this is connected to the usefulness of merit pay in keeping teachers on their toes, compliant and fearful of losing their jobs, rather than any desire to improve teacher effectiveness?

There is evidence that this may be the case. Yet another World Bank report (Bau & Das, 2017) argues, on the basis of research, that improved TVA (teacher value added) does not correlate with wages in the public sector (where it is hard to fire teachers), but it does in the private sector. The study found that ‘a policy change that shifted public hiring from permanent to temporary contracts, reducing wages by 35 percent, had no adverse impact on TVA’. All of which would seem to suggest that improving the quality of teaching is of less importance to the Bank than flexible hiring and firing. This is very much in line with a more general advocacy of making education fit for the world of work. Lois Weiner of New Jersey City University puts it like this:

The architects of [GERM] policies—imposed first in developing countries—openly state that the changes will make education better fit the new global economy by producing workers who are (minimally) educated for jobs that require no more than a 7th or 8th grade education; while a small fraction of the population receive a high quality education to become the elite who oversee finance, industry, and technology. Since most workers do not need to be highly educated, it follows that teachers with considerable formal education and experience are neither needed nor desired because they demand higher wages, which is considered a waste of government money. Most teachers need only be “good enough”—as one U.S. government official phrased it—to follow scripted materials that prepare students for standardized tests. (Weiner, 2012).

It seems impossible to separate the World Bank’s ‘Teach’ tool from the broader goals of GERM. Teacher evaluation tools, like the teaching of 21^st century skills and the datafication of education, need to be understood properly, I think, as means to an end. It’s time to spell out what that end is.

The World Bank’s mission is ‘to end extreme poverty (by reducing the share of the global population that lives in extreme poverty to 3 percent by 2030)’ and ‘to promote shared prosperity (by increasing the incomes of the poorest 40 percent of people in every country)’. Its education activities are part of this broad aim and are driven by subscription to human capital theory (a view of the skills, knowledge and experience of individuals in terms of their ability to produce economic value). This may be described as the ‘economization of education’: a shift in educational concerns away from ‘such things as civic participation, protecting human rights, and environmentalism to economic growth and employment’ (Spring, 2015: xiii). Both students and teachers are seen as human capital. For students, human capital education places an emphasis on the cognitive skills needed to succeed in the workplace and the ‘soft skills’, needed to function in the corporate world (Spring, 2015: 2). Accordingly, World Bank investments require ‘justifications on the basis of manpower demands’ (Heyneman, 2003: 317). One of the Bank’s current strategic priorities is the education of girls: although human rights and equity may also play a part, the Bank’s primary concern is that ‘Not Educating Girls Costs Countries Trillions of Dollars’ .

According to the Bank’s logic, its educational aims can best be achieved through a combination of support for the following:

• cost accounting and quantification (since returns on investment must be carefully measured)
• competition and market incentives (since it is believed that the ‘invisible hand’ of the market leads to the greatest benefits)
• the private sector in education and a rolling back of the role of the state (since it is believed that private ownership improves efficiency)

The package of measures is a straightforward reflection of ‘what Western mainstream economists believe’ (Castro, 2009: 474).

Mainstream Western economics is, however, going through something of a rocky patch right now. Human capital theory is ‘useful when prevailing conditions are right’ (Jones, 2007: 248), but prevailing conditions are not right in much of the world (even in the United States), and the theory ‘for the most part ignores the intersections of poverty, equity and education’ (Menashy, 2012). In poorer countries evidence for the positive effects of markets in education is in very short supply, and even in richer countries it is still not conclusive (Verger & Bonal, 2012: 135). An OECD Education Paper (Waslander et al., 2010: 64) found that the effects of choice and competition between schools were at best small, if indeed any effects were found at all. Similarly, the claim that privatization improves efficiency is not sufficiently supported by evidence. Analyses of PISA data would seem to indicate that, ‘all else being equal (especially when controlling for the socio-economic status of the students), the type of ownership of the school, whether it is a private or a state school, has only modest effects on student achievement or none at all’ (Verger & Bonal, 2012: 133). Educational privatization as a one-size-fits-all panacea to educational problems has little to recommend it.

There are, then, serious limitations in the Bank’s theoretical approach. Its practical track record is also less than illustrious, even by the Bank’s own reckoning. Many of the Bank’s interventions have proved very ‘costly to developing countries. At the Bank’s insistence countries over-invested in vocational and technical education. Because of the narrow definition of recurrent costs, countries ignored investments in reading materials and in maintaining teacher salaries. Later at the Bank’s insistence, countries invested in thousands of workshops and laboratories that, for the most part, became useless ‘white elephants’ (Heyneman, 2003: 333).

As a bank, the World Bank is naturally interested in the rate of return of investment in that capital, and is therefore concerned with efficiency and efficacy. This raises the question of ‘Effective for what?’ and given that what may be effective for one individual or group may not necessarily be effective for another individual or group, one may wish to add a second question: ‘Effective for whom?’ (Biesta, 2020: 31). Critics of the World Bank, of whom there are many, argue that its policies serve ‘the interests of corporations by keeping down wages for skilled workers, cause global brain migration to the detriment of developing countries, undermine local cultures, and ensure corporate domination by not preparing school graduates who think critically and are democratically oriented’ (Spring, 2015: 56). Lest this sound a bit harsh, we can turn to the Bank’s own commissioned history: ‘The way in which [the Bank’s] ideology has been shaped conforms in significant degree to the interests and conventional wisdom of its principal stockholders [i.e. bankers and economists from wealthy nations]. International competitive bidding, reluctance to accord preferences to local suppliers, emphasis on financing foreign exchange costs, insistence on a predominant use of foreign consultants, attitudes toward public sector industries, assertion of the right to approve project managers – all proclaim the Bank to be a Western capitalist institution’ (Mason & Asher, 1973: 478 – 479).

The teaching of ‘life skills’, the promotion of data-capturing digital technologies and the push to evaluate teachers’ performance are, then, all closely linked to the agenda of the World Bank, and owe their existence in the ELT landscape, in no small part, to the way that the World Bank has shaped educational discourse. There is, however, one other connection between ELT and the World Bank which must be mentioned.

The World Bank’s foreign language instructional goals are directly related to English as a global language. The Bank urges, ‘Policymakers in developing countries …to ensure that young people acquire a language with more than just local use, preferably one used internationally.’ What is this international language? First, the World Bank mentions that schools of higher education around the world are offering courses in English. In addition, the Bank states, ‘People seeking access to international stores of knowledge through the internet require, principally, English language skills.’ (Spring, 2015: 48).

Without the World Bank, then, there might be a lot less English language teaching than there is. I have written this piece to encourage people to think more about the World Bank, its policies and particular instantiations of those policies. You might or might not agree that the Bank is an undemocratic, technocratic, neoliberal institution unfit for the necessities of today’s world (Klees, 2017). But whatever you think about the World Bank, you might like to consider the answers to Tony Benn’s ‘five little democratic questions’ (quoted in Sardowski, 2020: 17):

• What power has it got?
• Where did it get this power from?
• In whose interests does it exercise this power?
• To whom is it accountable?
• How can we get rid of it?

References

Bau, N. and Das, J. (2017). The Misallocation of Pay and Productivity in the Public Sector : Evidence from the Labor Market for Teachers. Policy Research Working Paper; No. 8050. World Bank, Washington, DC. Retrieved [18 May 2020] from https://openknowledge.worldbank.org/handle/10986/26502

Beech, J. (2009). Who is Strolling Through The Global Garden? International Agencies and Educational Transfer. In Cowen, R. and Kazamias, A. M. (Eds.) Second International Handbook of Comparative Education. Dordrecht: Springer. pp. 341 – 358

Biesta, G. (2020). Educational Research. London: Bloomsbury.

Castro, C. De M., (2009). Can Multilateral Banks Educate The World? In Cowen, R. and Kazamias, A. M. (Eds.) Second International Handbook of Comparative Education. Dordrecht: Springer. pp. 455 – 478

Compton, M. and Weiner, L. (Eds.) (2008). The Global Assault on Teaching, Teachers, and their Unions. New York: Palgrave Macmillan

De Bruyckere, P., Kirschner, P.A. and Hulshof, C. (2020). More Urban Myths about Learning and Education. New York: Routledge.

De Siqueira, A. C. (2012). The 2020 World Bank Education Strategy: Nothing New, or the Same Old Gospel. In Klees, S. J., Samoff, J. and Stromquist, N. P. (Eds.) The World Bank and Education. Rotterdam: Sense Publishers. pp. 69 – 81

Heyneman, S.P. (2003). The history and problems in the making of education policy at the World Bank 1960–2000. International Journal of Educational Development 23 (2003) pp. 315–337. Retrieved [18 May 2020] from https://www.academia.edu/29593153/The_History_and_Problems_in_the_Making_of_Education_Policy_at_the_World_Bank_1960_2000

Jones, P. W. (2007). World Bank Financing of Education. 2^nd edition. Abingdon, Oxon.: Routledge.

Klees, S. (2017). A critical analysis of the World Bank’s World Development Report on education. Retrieved [18 May 2020] from: https://www.brettonwoodsproject.org/2017/11/critical-analysis-world-banks-world-development-report-education/

Mason, E. S. & Asher, R. E. (1973). The World Bank since Bretton Woods. Washington, DC: Brookings Institution.

Menashy, F. (2012). Review of Klees, S J., Samoff, J. & Stromquist, N. P. (Eds) (2012). The World Bank and Education: Critiques and Alternatives .Rotterdam: Sense Publishers. Education Review, 15. Retrieved [18 May 2020] from https://www.academia.edu/7672656/Review_of_The_World_Bank_and_Education_Critiques_and_Alternatives

Rizvi, F. & Lingard, B. (2010). Globalizing Education Policy. Abingdon, Oxon.: Routledge.

Sadowski, J. (2020). Too Smart. Cambridge, MA.: MIT Press.

Sahlberg, P. (2016). The global educational reform movement and its impact on schooling. In K. Mundy, A. Green, R. Lingard, & A. Verger (Eds.), The handbook of global policy and policymaking in education. New York, NY: Wiley-Blackwell. pp.128 – 144

Selwyn, N. (2013). Education in a Digital World. New York: Routledge.

Spring, J. (2015). Globalization of Education 2nd Edition. New York: Routledge.

Trilling, B. & C. Fadel (2009). 21st Century Skills. San Francisco: Wiley

Verger, A. & Bonal, X. (2012). ‘All Things Being Equal?’ In Klees, S. J., Samoff, J. and Stromquist, N. P. (Eds.) The World Bank and Education. Rotterdam: Sense Publishers. pp. 69 – 81

Waslander, S., Pater, C. & van der Weide, M. (2010). Markets in Education: An analytical review of empirical research on market mechanisms in education. OECD EDU Working Paper 52.

Weiner, L. (2012). Social Movement Unionism: Teachers Can Lead the Way. Reimagine, 19 (2) Retrieved [18 May 2020] from: https://www.reimaginerpe.org/19-2/weiner-fletcher

Williamson, B., Bayne, S. & Shay, S. (2020). The datafication of teaching in Higher Education: critical issues and perspectives, Teaching in Higher Education, 25:4, 351-365, DOI: 10.1080/13562517.2020.1748811

World Bank. (2013). Life skills : what are they, why do they matter, and how are they taught? (English). Adolescent Girls Initiative (AGI) learning from practice series. Washington DC ; World Bank. Retrieved [18 May 2020] from: http://documents.worldbank.org/curated/en/569931468331784110/Life-skills-what-are-they-why-do-they-matter-and-how-are-they-taught