Posts Tagged ‘novelty effects’

Innovation and ELT

Next week sees the prize ceremony of the nineteenth edition of the British Council’s ELTons awards, celebrating ‘innovation in English language teaching and learning … the newest and most original courses, books, publications, apps, platforms, projects, and more.’ Since the Council launched the ELTons in 2003, it hasn’t been entirely clear what is meant by ‘innovation’. But, reflecting the use of the term in the wider (business) world, ‘innovation’ was seen as a positive value, an inherently good thing, and almost invariably connected to technological innovation. One of the award categories in the ELTons is for ‘digital innovation’, but many of the winners and shortlisted nominations in other categories have been primarily innovative in their use of technology (at first, CD-ROMs, before web-based applications became standard).

Historian Jill Lepore, among others, has traced the mantra of innovation at the start of this century back to renewed interest in the work of mid-20th century Austrian economist, Joseph Schumpeter, in the 1990s. Schumpeter wrote about ‘creative disruption’, and his ideas gained widespread traction with the publication in 1997 of Clayton Christensen’s ‘The Innovator’s Dilemma: The Revolutionary Book that Will Change the Way You Do Business’. Under Christensen, ‘creative disruption’ morphed into ‘disruptive innovation’. The idea was memorably expressed in Facebook’s motto of ‘Move fast and break things’. Disruptive innovation was always centrally concerned with expanding the market for commercial products by leveraging technology to gain access to more customers. Innovation, then, was and is a commercial strategy, and could be used either in product development or simply as an advertising slogan.

From the start of the innovation wave, the British Council has been keen to position itself in the vanguard. It does this for two reasons. Firstly, it needs to promote its own products and, with the cuts to British Council funding, its need to generate more income is increasingly urgent: ELT products are the main source of this income. Secondly, as part of the Council’s role in pushing British ‘soft power’, it seeks to promote Britain as a desirable, and therefore innovative, place to do business or study. This is wonderfully reflected in a series of videos for the Council’s LearnEnglish website called ‘Britain is Great’, subsets of which are entitled ‘Entrepreneurs are GREAT’ and ‘Innovation is GREAT’ with films celebrating the work of people like Richard Branson and James Dyson. For a while, the Council had a ‘Director, English Language Innovation’, and the current senior management team includes a ‘Director Digital, Partnerships and Innovation’ and a ‘Director Transformation’. With such a focus on innovation at the heart of its organisation, it is hardly surprising that the British Council should celebrate the idea in its ELTons awards. The ELTons celebrate the Council itself, and its core message, as much as they do the achievements of the award winners. Finalists in the ELTons receive a ‘promotional kit’ which includes ‘assets for the promotion of products or publications’. These assets (badges, banners, and so on) serve to promote the Council brand at the same time as advertising the shortlisted products themselves.

Innovation and a better world

Innovation, especially ‘disruptive innovation’, is not, however, what it used to be. The work of Clayton Christensen has been largely discredited (Russell & Vinsel, 2016). The Facebook motto has been changed and ‘the Era of “Move Fast and Break Things” Is Over’ (Taneja, 2019). The interest in ‘minimal viable products’ has shifted to an interest in ‘minimal virtuous products’. This is reflected in the marketing of edtech with the growing focus on how product X or Y will make the world a better place in some way. The ELTons introduced ‘Judges’ Commendations’ for ‘Equality, Diversity and Inclusion’ and, this year, a new commendation for ‘Environmental Sustainability and Climate Action’. Innovation is still celebrated, but ‘disruption’ has undergone a slide of meaning, so that it is more likely now to refer to disruption caused by the Covid pandemic, and our responses to it. For example, TESOL Italy’s upcoming annual conference, entitled ‘Disruptive Innovations in ELT’, encourages contributions not only about online study and ‘interactive e-learning platforms’, but also about ‘sustainable development and social justice’, ‘resilience, collaboration, empathy, digital literacy, soft skills, and global competencies’. Innovation is still presented as a good, even necessary, thing.

I am not suggesting that the conflation of innovation with positive social good is purely virtue-signalling, although it is sometimes clearly that. However, the rhetorical shift makes it harder for anyone to criticise innovations, when they are presented as solutions to problems that need to be solved. Allen et al (2021) argue that ‘those who propose solutions are always virtuous because they clearly care about a problem we must solve. Those who suggest the solution will not work, and who have no better solution, are denying the problem the opportunity of the resolution it so desperately needs’.

There are, though, good reasons to be wary of ‘innovation’ in education. First among these is the lessons of history, which teach us that today’s ‘next big thing’ is usually tomorrow’s ‘last next big thing’ (Allen, et al., 2021). On the technology front, from programmed instruction to interactive whiteboards, educational history is littered with artefacts that have been oversold and underused (Cuban, 2001). Away from technology, from Multiple Intelligences to personalized learning, we see the same waves of enthusiasm and widespread adoption, followed by waning interest and abandonment. The waste of money and effort along the way has been colossal, although that is not to say that there have not been some, sometimes significant, gains.

The second big reason to be wary of technological innovations in education is that they focus our attention on products of various kinds. But products are not at the heart of schooling: it is labour, especially the work of teachers, which occupies that place. It is not Zoom that made possible the continuation of education during the pandemic lockdowns. Indeed, in many parts of the world, lower-tech or zero-tech solutions had to be found. It was teachers’ readiness to adapt to the new circumstances that allowed education to stumble onwards during the crisis. Vinsel and Russell’s recent book, ‘The Innovation Delusion’ (2021) compellingly argues that the focus on innovation has led us to ‘devalue the work that underpins modern life’. They point out (Russell and Vinsel, 2016) that ‘feminist theorists have long argued that obsessions with technological novelty obscures all of the labour, including housework, that women, disproportionately, do to keep life on track’. Parallels with the relationship between teachers and technology are hard to avoid. The presentation of innovation as an inherently desirable value ‘rarely asks who benefits, to what end?’

The ‘ELT’ in the ELTons

It’s time to consider the ‘ELT’ part of the ELTons. ‘ELT’ is a hypothetical construct that is often presented as a concrete reality, rather than a loosely-bound constellation of a huge number of different practices and attitudes, many of which have very little in common with each other. This reification of ‘ELT’ can serve a number of purposes, one of which is to frame discourse in particular ways. In a post from a few years ago, Andrew Wickham and I discussed how the framing of ‘ELT’ (and education, more generally) as an industry serves particular interests, but may be detrimental to the interests of others.

Perhaps a useful way of viewing ‘ELT’ is as a discourse community. Borg (2003) argues that ‘membership of a discourse community is usually a matter of choice’. That is to say that you are part of ‘ELT’ if you choose to identify yourself as such. In Europe, huge numbers of English language teachers do not choose to identify themselves primarily as an ‘ELT teacher’: they may see this label as relevant to them, but a more immediate and primary self-identification is often as a ‘school teacher’, a ‘primary school teacher’, a ‘(modern) languages teacher’, a ‘CLIL teacher’, and so on. They work in the state / public sectors. The concerns and interests of those who do not self-identify as ‘ELT practitioners’ are most likely to revolve around their local contexts and issues. Those of us who self-identify as ‘ELT practitioners’ are more likely to be interested in what we share with others who self-identify in the same way in different parts of the globe. The relevance of local contexts and issues is mostly to be found in how they may shed light on more global concerns. If you prioritise the local over the global, your participation in the ‘ELT’ discourse community is likely to be limited. Things like the ELTons are simply off your radar.

Borg (2003) also points out that discourse communities typically have ‘experts who perform gatekeeping roles’. The discourse of ‘ELT’ is enacted in magazines, blogs, videos, webinars and conferences aimed at English language teachers. I exclude from this list academic journals and books which are known to be consulted only rarely by the vast majority of teachers. Similarly, I exclude the more accessible books that have been written specifically for English language teachers, which are mostly sold in minuscule quantities, except for those that are required reading for training courses. The greatest number of contributors to the discourse of ‘ELT’ are authors, developers and publishers of language teaching materials and tools, teachers representing product vendors or (directly or indirectly) promoting their own products, representatives of private teaching / training schools, and organisations, representatives of international examination bodies, and representatives of universities (which, in some countries, essentially function as private institutions (Chowdhury & Ha, 2014)).

In other words, the discourse of ‘ELT’ is shaped to a very significant extent by gatekeepers who have a product to sell. Their customers are often those who do not self-identify in the same way as members of the ‘ELT’ discourse community. The British Council is a key gatekeeper in this discourse and it is a private sector operator par excellence.

The lack of interest in the workers of ‘ELT’ is well documented – see for example the Teachers as Workers blog. It is hardly unexpected, especially in the private sector. The British Council has a long history of labour disputes. At the present time, the Public and Commercial Services Union in the UK is balloting members about strike action against forced redundancies, which ‘are disproportionately targeted at middle to lower graded staff, while at the same time new management positions and a new deputy chief executive officer post are to be created’. One of the aims of the union is to stop the privatisation / outsourcing of Council jobs. The British government’s recent failure to relocate British Council employees in Afghanistan led to over 100,000 people signing a petition demanding action. The public silence of the British Council did little to inspire confidence in their interest in their workers.

The Council is a many-headed beast, and some of these heads do very admirable work in sponsoring or supporting a large variety of valuable projects. I don’t think the ELTons is one of these. The ideology behind them is highly questionable, and their ‘best before’ date has long expired. And given the financial constraints that the Council is now operating under, the money might be better spent elsewhere.


Allen, R., Evans, M. & White, B. (2021) The Next Big Thing in School Improvement. Woodbridge: John Catt Educational

Borg, E. (2003) Discourse Community. ELT Journal 57 (4): 398-400

Chowdhury, R. & Ha, P. L. (2014) Desiring TESOL and International Education. Bristol: Multilingual Matters

Christensen, C. M. (1997) The Innovator’s Dilemma: The Revolutionary Book that Will Change the Way You Do Business. Cambridge: Harvard Business Review Press

Cuban, L. (2001) Oversold and Underused: Computers in the Classroom. Cambridge: Harvard University Press

Lepore, J. (2014) The Disruption Machine. The New Yorker, June 16, 2014.

Russell, A. L. & Vinsel, L. (2016) Hail the Maintainers. Aeon, 7 April 2016

Taneja, H. (2019) The Era of “Move Fast and Break Things” Is Over. Harvard Business Review, January 22, 2019,

Vinsel, L. & Russell, A. L. (2020) The Innovation Delusion. New York: Currency Books


At the beginning of March, I’ll be going to Cambridge to take part in a Digital Learning Colloquium (for more information about the event, see here ). One of the questions that will be explored is how research might contribute to the development of digital language learning. In this, the first of two posts on the subject, I’ll be taking a broad overview of the current state of play in edtech research.

I try my best to keep up to date with research. Of the main journals, there are Language Learning and Technology, which is open access; CALICO, which offers quite a lot of open access material; and reCALL, which is the most restricted in terms of access of the three. But there is something deeply frustrating about most of this research, and this is what I want to explore in these posts. More often than not, research articles end with a call for more research. And more often than not, I find myself saying ‘Please, no, not more research like this!’

First, though, I would like to turn to a more reader-friendly source of research findings. Systematic reviews are, basically literature reviews which can save people like me from having to plough through endless papers on similar subjects, all of which contain the same (or similar) literature review in the opening sections. If only there were more of them. Others agree with me: the conclusion of one systematic review of learning and teaching with technology in higher education (Lillejord et al., 2018) was that more systematic reviews were needed.

Last year saw the publication of a systematic review of research on artificial intelligence applications in higher education (Zawacki-Richter, et al., 2019) which caught my eye. The first thing that struck me about this review was that ‘out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis’. In other words, only just over 5% of the research was considered worthy of inclusion.

The review did not paint a very pretty picture of the current state of AIEd research. As the second part of the title of this review (‘Where are the educators?’) makes clear, the research, taken as a whole, showed a ‘weak connection to theoretical pedagogical perspectives’. This is not entirely surprising. As Bates (2019) has noted: ‘since AI tends to be developed by computer scientists, they tend to use models of learning based on how computers or computer networks work (since of course it will be a computer that has to operate the AI). As a result, such AI applications tend to adopt a very behaviourist model of learning: present / test / feedback.’ More generally, it is clear that technology adoption (and research) is being driven by technology enthusiasts, with insufficient expertise in education. The danger is that edtech developers ‘will simply ‘discover’ new ways to teach poorly and perpetuate erroneous ideas about teaching and learning’ (Lynch, 2017).

This, then, is the first of my checklist of things that, collectively, researchers need to do to improve the value of their work. The rest of this list is drawn from observations mostly, but not exclusively, from the authors of systematic reviews, and mostly come from reviews of general edtech research. In the next blog post, I’ll look more closely at a recent collection of ELT edtech research (Mavridi & Saumell, 2020) to see how it measures up.

1 Make sure your research is adequately informed by educational research outside the field of edtech

Unproblematised behaviourist assumptions about the nature of learning are all too frequent. References to learning styles are still fairly common. The most frequently investigated skill that is considered in the context of edtech is critical thinking (Sosa Neira, et al., 2017), but this is rarely defined and almost never problematized, despite a broad literature that questions the construct.

2 Adopt a sceptical attitude from the outset

Know your history. Decades of technological innovation in education have shown precious little in the way of educational gains and, more than anything else, have taught us that we need to be sceptical from the outset. ‘Enthusiasm and praise that are directed towards ‘virtual education, ‘school 2.0’, ‘e-learning and the like’ (Selwyn, 2014: vii) are indications that the lessons of the past have not been sufficiently absorbed (Levy, 2016: 102). The phrase ‘exciting potential’, for example, should be banned from all edtech research. See, for example, a ‘state-of-the-art analysis of chatbots in education’ (Winkler & Söllner, 2018), which has nothing to conclude but ‘exciting potential’. Potential is fine (indeed, it is perhaps the only thing that research can unambiguously demonstrate – see section 3 below), but can we try to be a little more grown-up about things?

3 Know what you are measuring

Measuring learning outcomes is tricky, to say the least, but it’s understandable that researchers should try to focus on them. Unfortunately, ‘the vast array of literature involving learning technology evaluation makes it challenging to acquire an accurate sense of the different aspects of learning that are evaluated, and the possible approaches that can be used to evaluate them’ (Lai & Bower, 2019). Metrics such as student grades are hard to interpret, not least because of the large number of variables and the danger of many things being conflated in one score. Equally, or possibly even more, problematic, are self-reporting measures which are rarely robust. It seems that surveys are the most widely used instrument in qualitative research (Sosa Neira, et al., 2017), but these will tell us little or nothing when used for short-term interventions (see point 5 below).

4 Ensure that the sample size is big enough to mean something

In most of the research into digital technology in education that was analysed in a literature review carried out for the Scottish government (ICF Consulting Services Ltd, 2015), there were only ‘small numbers of learners or teachers or schools’.

5 Privilege longitudinal studies over short-term projects

The Scottish government literature review (ICF Consulting Services Ltd, 2015), also noted that ‘most studies that attempt to measure any outcomes focus on short and medium term outcomes’. The fact that the use of a particular technology has some sort of impact over the short or medium term tells us very little of value. Unless there is very good reason to suspect the contrary, we should assume that it is a novelty effect that has been captured (Levy, 2016: 102).

6 Don’t forget the content

The starting point of much edtech research is the technology, but most edtech, whether it’s a flashcard app or a full-blown Moodle course, has content. Research reports rarely give details of this content, assuming perhaps that it’s just fine, and all that’s needed is a little tech to ‘present learners with the ‘right’ content at the ‘right’ time’ (Lynch, 2017). It’s a foolish assumption. Take a random educational app from the Play Store, a random MOOC or whatever, and the chances are you’ll find it’s crap.

7 Avoid anecdotal accounts of technology use in quasi-experiments as the basis of a ‘research article’

Control (i.e technology-free) groups may not always be possible but without them, we’re unlikely to learn much from a single study. What would, however, be extremely useful would be a large, collated collection of such action-research projects, using the same or similar technology, in a variety of settings. There is a marked absence of this kind of work.

8 Enough already of higher education contexts

Researchers typically work in universities where they have captive students who they can carry out research on. But we have a problem here. The systematic review of Lundin et al (2018), for example, found that ‘studies on flipped classrooms are dominated by studies in the higher education sector’ (besides lacking anchors in learning theory or instructional design). With some urgency, primary and secondary contexts need to be investigated in more detail, not just regarding flipped learning.

9 Be critical

Very little edtech research considers the downsides of edtech adoption. Online safety, privacy and data security are hardly peripheral issues, especially with younger learners. Ignoring them won’t make them go away.

More research?

So do we need more research? For me, two things stand out. We might benefit more from, firstly, a different kind of research, and, secondly, more syntheses of the work that has already been done. Although I will probably continue to dip into the pot-pourri of articles published in the main CALL journals, I’m looking forward to a change at the CALICO journal. From September of this year, one issue a year will be thematic, with a lead article written by established researchers which will ‘first discuss in broad terms what has been accomplished in the relevant subfield of CALL. It should then outline which questions have been answered to our satisfaction and what evidence there is to support these conclusions. Finally, this article should pose a “soft” research agenda that can guide researchers interested in pursuing empirical work in this area’. This will be followed by two or three empirical pieces that ‘specifically reflect the research agenda, methodologies, and other suggestions laid out in the lead article’.

But I think I’ll still have a soft spot for some of the other journals that are coyer about their impact factor and that can be freely accessed. How else would I discover (it would be too mean to give the references here) that ‘the effective use of new technologies improves learners’ language learning skills’? Presumably, the ineffective use of new technologies has the opposite effect? Or that ‘the application of modern technology represents a significant advance in contemporary English language teaching methods’?


Bates, A. W. (2019). Teaching in a Digital Age Second Edition. Vancouver, B.C.: Tony Bates Associates Ltd. Retrieved from

ICF Consulting Services Ltd (2015). Literature Review on the Impact of Digital Technology on Learning and Teaching. Edinburgh: The Scottish Government.

Lai, J.W.M. & Bower, M. (2019). How is the use of technology in education evaluated? A systematic review. Computers & Education, 133(1), 27-42. Elsevier Ltd. Retrieved January 14, 2020 from

Levy, M. 2016. Researching in language learning and technology. In Farr, F. & Murray, L. (Eds.) The Routledge Handbook of Language Learning and Technology. Abingdon, Oxon.: Routledge. pp.101 – 114

Lillejord S., Børte K., Nesje K. & Ruud E. (2018). Learning and teaching with technology in higher education – a systematic review. Oslo: Knowledge Centre for Education

Lundin, M., Bergviken Rensfeldt, A., Hillman, T. et al. (2018). Higher education dominance and siloed knowledge: a systematic review of flipped classroom research. International Journal of Educational Technology in Higher Education 15, 20 (2018) doi:10.1186/s41239-018-0101-6

Lynch, J. (2017). How AI Will Destroy Education. Medium, November 13, 2017.

Mavridi, S. & Saumell, V. (Eds.) (2020). Digital Innovations and Research in Language Learning. Faversham, Kent: IATEFL

Selwyn, N. (2014). Distrusting Educational Technology. New York: Routledge

Sosa Neira, E. A., Salinas, J. and de Benito Crosetti, B. (2017). Emerging Technologies (ETs) in Education: A Systematic Review of the Literature Published between 2006 and 2016. International Journal of Emerging Technologies in Education, 12 (5).

Winkler, R. & Söllner, M. (2018): Unleashing the Potential of Chatbots in Education: A State-Of-The-Art Analysis. In: Academy of Management Annual Meeting (AOM). Chicago, USA.

Zawacki-Richter, O., Bond, M., Marin, V. I. And Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education 2019

Back in the middle of the last century, the first interactive machines for language teaching appeared. Previously, there had been phonograph discs and wire recorders (Ornstein, 1968: 401), but these had never really taken off. This time, things were different. Buoyed by a belief in the power of technology, along with the need (following the Soviet Union’s successful Sputnik programme) to demonstrate the pre-eminence of the United States’ technological expertise, the interactive teaching machines that were used in programmed instruction promised to revolutionize language learning (Valdman, 1968: 1). From coast to coast, ‘tremors of excitement ran through professional journals and conferences and department meetings’ (Kennedy, 1967: 871). The new technology was driven by hard science, supported and promoted by the one of the most well-known and respected psychologists and public intellectuals of the day (Skinner, 1961).

In classrooms, the machines acted as powerfully effective triggers in generating situational interest (Hidi & Renninger, 2006). Even more exciting than the mechanical teaching machines were the computers that were appearing on the scene. ‘Lick’ Licklider, a pioneer in interactive computing at the Advanced Research Projects Agency in Arlington, Virginia, developed an automated drill routine for learning German by hooking up a computer, two typewriters, an oscilloscope and a light pen (Noble, 1991: 124). Students loved it, and some would ‘go on and on, learning German words until they were forced by scheduling to cease their efforts’. Researchers called the seductive nature of the technology ‘stimulus trapping’, and Licklider hoped that ‘before [the student] gets out from under the control of the computer’s incentives, [they] will learn enough German words’ (Noble, 1991: 125).

With many of the developed economies of the world facing a critical shortage of teachers, ‘an urgent pedagogical emergency’ (Hof, 2018), the new approach was considered to be extremely efficient and could equalise opportunity in schools across the country. It was ‘here to stay: [it] appears destined to make progress that could well go beyond the fondest dreams of its originators […] an entire industry is just coming into being and significant sales and profits should not be too long in coming’ (Kozlowski, 1961: 47).

Unfortunately, however, researchers and entrepreneurs had massively underestimated the significance of novelty effects. The triggered situational interest of the machines did not lead to intrinsic individual motivation. Students quickly tired of, and eventually came to dislike, programmed instruction and the machines that delivered it (McDonald et al.: 2005: 89). What’s more, the machines were expensive and ‘research studies conducted on its effectiveness showed that the differences in achievement did not constantly or substantially favour programmed instruction over conventional instruction (Saettler, 2004: 303). Newer technologies, with better ‘stimulus trapping’, were appearing. Programmed instruction lost its backing and disappeared, leaving as traces only its interest in clearly defined learning objectives, the measurement of learning outcomes and a concern with the efficiency of learning approaches.

Hot on the heels of programmed instruction came the language laboratory. Futuristic in appearance, not entirely unlike the deck of the starship USS Enterprise which launched at around the same time, language labs captured the public imagination and promised to explore the final frontiers of language learning. As with the earlier teaching machines, students were initially enthusiastic. Even today, when language labs are introduced into contexts where they may be perceived as new technology, they can lead to high levels of initial motivation (e.g. Ramganesh & Janaki, 2017).

Given the huge investments into these labs, it’s unfortunate that initial interest waned fast. By 1969, many of these rooms had turned into ‘“electronic graveyards,” sitting empty and unused, or perhaps somewhat glorified study halls to which students grudgingly repair to don headphones, turn down the volume, and prepare the next period’s history or English lesson, unmolested by any member of the foreign language faculty’ (Turner, 1969: 1, quoted in Roby, 2003: 527). ‘Many second language students shudder[ed] at the thought of entering into the bowels of the “language laboratory” to practice and perfect the acoustical aerobics of proper pronunciation skills. Visions of sterile white-walled, windowless rooms, filled with endless bolted-down rows of claustrophobic metal carrels, and overseen by a humorless, lab director, evoke[d] fear in the hearts of even the most stout-hearted prospective second-language learners (Wiley, 1990: 44).

By the turn of this century, language labs had mostly gone, consigned to oblivion by the appearance of yet newer technology: the internet, laptops and smartphones. Education had been on the brink of being transformed through new learning technologies for decades (Laurillard, 2008: 1), but this time it really was different. It wasn’t just one technology that had appeared, but a whole slew of them: ‘artificial intelligence, learning analytics, predictive analytics, adaptive learning software, school management software, learning management systems (LMS), school clouds. No school was without these and other technologies branded as ‘superintelligent’ by the late 2020s’ (Macgilchrist et al., 2019). The hardware, especially phones, was ubiquitous and, therefore, free. Unlike teaching machines and language laboratories, students were used to using the technology and expected to use their devices in their studies.

A barrage of publicity, mostly paid for by the industry, surrounded the new technologies. These would ‘meet the demands of Generation Z’, the new generation of students, now cast as consumers, who ‘were accustomed to personalizing everything’.  AR, VR, interactive whiteboards, digital projectors and so on made it easier to ‘create engaging, interactive experiences’. The ‘New Age’ technologies made learning fun and easy,  ‘bringing enthusiasm among the students, improving student engagement, enriching the teaching process, and bringing liveliness in the classroom’. On top of that, they allowed huge amounts of data to be captured and sold, whilst tracking progress and attendance. In any case, resistance to digital technology, said more than one language teaching expert, was pointless (Styring, 2015).slide

At the same time, technology companies increasingly took on ‘central roles as advisors to national governments and local districts on educational futures’ and public educational institutions came to be ‘regarded by many as dispensable or even harmful’ (Macgilchrist et al., 2019).

But, as it turned out, the students of Generation Z were not as uniformly enthusiastic about the new technology as had been assumed, and resistance to digital, personalized delivery in education was not long in coming. In November 2018, high school students at Brooklyn’s Secondary School for Journalism staged a walkout in protest at their school’s use of Summit Learning, a web-based platform promoting personalized learning developed by Facebook. They complained that the platform resulted in coursework requiring students to spend much of their day in front of a computer screen, that made it easy to cheat by looking up answers online, and that some of their teachers didn’t have the proper training for the curriculum (Leskin, 2018). Besides, their school was in a deplorable state of disrepair, especially the toilets. There were similar protests in Kansas, where students staged sit-ins, supported by their parents, one of whom complained that ‘we’re allowing the computers to teach and the kids all looked like zombies’ before pulling his son out of the school (Bowles, 2019). In Pennsylvania and Connecticut, some schools stopped using Summit Learning altogether, following protests.

But the resistance did not last. Protesters were accused of being nostalgic conservatives and educationalists kept largely quiet, fearful of losing their funding from the Chan Zuckerberg Initiative (Facebook) and other philanthro-capitalists. The provision of training in grit, growth mindset, positive psychology and mindfulness (also promoted by the technology companies) was ramped up, and eventually the disaffected students became more quiescent. Before long, the data-intensive, personalized approach, relying on the tools, services and data storage of particular platforms had become ‘baked in’ to educational systems around the world (Moore, 2018: 211). There was no going back (except for small numbers of ultra-privileged students in a few private institutions).

By the middle of the century (2155), most students, of all ages, studied with interactive screens in the comfort of their homes. Algorithmically-driven content, with personalized, adaptive tests had become the norm, but the technology occasionally went wrong, leading to some frustration. One day, two young children discovered a book in their attic. Made of paper with yellow, crinkly pages, where ‘the words stood still instead of moving the way they were supposed to’. The book recounted the experience of schools in the distant past, where ‘all the kids from the neighbourhood came’, sitting in the same room with a human teacher, studying the same things ‘so they could help one another on the homework and talk about it’. Margie, the younger of the children at 11 years old, was engrossed in the book when she received a nudge from her personalized learning platform to return to her studies. But Margie was reluctant to go back to her fractions. She ‘was thinking about how the kids must have loved it in the old days. She was thinking about the fun they had’ (Asimov, 1951).


Asimov, I. 1951. The Fun They Had. Accessed September 20, 2019.

Bowles, N. 2019. ‘Silicon Valley Came to Kansas Schools. That Started a Rebellion’ The New York Times, April 21. Accessed September 20, 2019.

Hidi, S. & Renninger, K.A. 2006. ‘The Four-Phase Model of Interest Development’ Educational Psychologist, 41 (2), 111 – 127

Hof, B. 2018. ‘From Harvard via Moscow to West Berlin: educational technology, programmed instruction and the commercialisation of learning after 1957’ History of Education, 47 (4): 445-465

Kennedy, R.H. 1967. ‘Before using Programmed Instruction’ The English Journal, 56 (6), 871 – 873

Kozlowski, T. 1961. ‘Programmed Teaching’ Financial Analysts Journal, 17 (6): 47 – 54

Laurillard, D. 2008. Digital Technologies and their Role in Achieving our Ambitions for Education. London: Institute for Education.

Leskin, P. 2018. ‘Students in Brooklyn protest their school’s use of a Zuckerberg-backed online curriculum that Facebook engineers helped build’ Business Insider, 12.11.18 Accessed 20 September 2019.

McDonald, J. K., Yanchar, S. C. & Osguthorpe, R.T. 2005. ‘Learning from Programmed Instruction: Examining Implications for Modern Instructional Technology’ Educational Technology Research and Development, 53 (2): 84 – 98

Macgilchrist, F., Allert, H. & Bruch, A. 2019. ‚Students and society in the 2020s. Three future ‘histories’ of education and technology’. Learning, Media and Technology, )

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

Noble, D. D. 1991. The Classroom Arsenal. London: The Falmer Press

Ornstein, J. 1968. ‘Programmed Instruction and Educational Technology in the Language Field: Boon or Failure?’ The Modern Language Journal, 52 (7), 401 – 410

Ramganesh, E. & Janaki, S. 2017. ‘Attitude of College Teachers towards the Utilization of Language Laboratories for Learning English’ Asian Journal of Social Science Studies; Vol. 2 (1): 103 – 109

Roby, W.B. 2003. ‘Technology in the service of foreign language teaching: The case of the language laboratory’ In D. Jonassen (ed.), Handbook of Research on Educational Communications and Technology, 2nd ed.: 523 – 541. Mahwah, NJ.: Lawrence Erlbaum Associates

Saettler, P. 2004. The Evolution of American Educational Technology. Greenwich, Conn.: Information Age Publishing

Skinner, B. F. 1961. ‘Teaching Machines’ Scientific American, 205(5), 90-107

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