Hijacking Creativity

‘Whenever a word is frequently used in arguments trying to persuade people to believe some opinion or other, our mental twists and turns to make the opinion plausible involve shifting from meaning to meaning without realizing it. This has happened to creativity on a grand scale.’ (Perry, L. (1987). The Educational Value of Creativity. Journal of Art and Design Education 6 (3) ) quoted in Pugliese, 2010: 8)

If you take a look at the word ‘creativity’ in Google’s Ngram viewer, you’ll notice that use of the word really took off around 1950, the year when J. P. Guilford published an article entitled ‘Creativity’ in American Psychologist. Guilford’s background was in the US military. His research was part funded by the US Navy and his subjects were US Air Force personnel. His interest was in the classification and training of military recruits.

With the Cold War between the US and the Soviet Union hotting up, Guilford’s interests increasingly became a matter of national security. In 1954, Carl Rogers, argued that education tended to turn out ‘conformists […] rather than freely creative and original thinkers’ (Rogers, 1954: 249) and that there was a ‘desperate need’ for the latter. He warned that ‘international annihilation will be the price we pay for a lack of creativity’. When Sputnik scared the shit out of the American military, creativity became more important still. It ‘could no longer be left to the chance occurrence of genius; neither could it be left in the realm of the wholly mysterious and the untouchable. Men had to be able to do something about it; creativity had to be a property in many men; it had to be something identifiable; it had to be subject to efforts to gain more of it’ (Razik, 1967).

It wasn’t long before creativity moved beyond purely military concerns to more generally corporate ones. Creativity became one of the motors driving the economy. This process is tracked in a fascinating article by Steven Shapin (2020), who quotes the director of research at General Electric as saying in 1959: ‘I think we can agree at once that we are all in favour of creativity’. Since then, the idea of creativity has rarely looked back.

By the end of the century, the UK government had set up a National Advisory Committee on Creative and Cultural Education, chaired by Ken Robinson. Creativity was seen as a ‘vital investment in human capital for the twenty-first century’ (National Advisory Committee on Creative and Cultural Education, 1999). Quoting the prime minister, Blair, the report stated that ‘our aim must be to create a nation where the creative talents of all the people are used to build a true enterprise economy for the twenty-first century — where we compete on brains, not brawn’.

A few years later, in the US, the Partnership for 21^st Century Skills was founded, supported primarily by the corporate community with companies like AOL Time Warner, Apple and Microsoft providing financial backing. The ‘21^st century skills’ required by global employers (or more specifically that global employers wanted national governments to pay for) could be catchily boiled down to the 4Cs – communication, collaboration, critical reflection and creativity. What was meant by creativity is made clearer in Trilling and Fadel’s bible of 21^st century skills (2009: 56):

‘Given the 21st century demands to continuously innovate new services, better processes, and improved products for the world’s global economy, and for the creative knowledge required in more and more of the world’s better-paying jobs, it should come as no surprise that creativity and innovation are very high on the list of 21st century skills. In fact, many believe that our current Knowledge Age is quickly giving way to an Innovation Age, where the ability to solve problems in new ways (like the greening of energy use), to invent new technologies (like bio- and nanotechnology) or create the new killer application of existing technologies (like efficient and affordable electric cars and solar panels, or even to discover new branches of knowledge and invent entirely new industries, will all be highly prized.’

In this line of thought, creativity is blurred with ‘innovation skills’ and inextricably linked to business (and employee) performance. It involves creative thinking techniques (such as brainstorming), the ability to work collaboratively and creatively with others, openness to new ideas and perspectives, originality and inventiveness in work, and understanding real-world limits to adopting new ideas (Trilling & Fadel, 2009: 59). Although never defined very precisely, the purpose of creativity in education (as well as 21^st skills more generally) is crystal-clear:

‘A fundamental role of education is to equip students with the competences they need – and will need – in order to succeed in society. Creative thinking is a necessary competence for today’s young people to develop. It can help them adapt to a constantly and rapidly changing world, and one that demands flexible workers equipped with ‘21st century’ skills that go beyond core literacy and numeracy. After all, children today will likely be employed in sectors or roles that do not yet exist’. (OECD, 2019: 6)

Creativity, then, has become first and foremost about the development of human capital and, by extension, the health of financial capital. In the World Economic Forum’s list of ‘5 Things You Need To Know About Creativity’, #1 on the list is ‘Creativity is good for the Economy’, #4 is ‘It’s important for leadership’, and #5 is ‘It’s crucial for the future of work’. For the World Bank, creativity is more or less synonymous with entrepreneurship (World Bank, 2010).

Given the importance that the OECD attaches to creativity, it was inevitable that they should seek to measure it. The next round of PISA tests, postponed to 2022 because of Covid-19, will incorporate evaluation of creative thinking. As the OECD itself recognises (OECD, 2019), this will be no easy task. There are problems in establishing a valid and agreed construct of creative thinking / creativity. There is debate about the extent to which creative thinking is domain-specific (does creative thinking in science different to creative thinking in the arts?). Previous attempts to measure creativity have been less than satisfactory. But none of this will stop the OECD juggernaut, and shortcomings in the first round of evaluations can be taken, creatively, as ‘an opportunity to learn’ (Trilling & Fadel, 2009: 59). There will be a washback effect, but this is all to the good in the eyes of the OECD. One of their most significant objectives in measuring creativity is to encourage ‘changes in education policies and pedagogies’ (OECD, 2019: 5): ‘the results will also encourage a wider societal debate on both the importance and methods of supporting this crucial competence through education’. To a large extent, it is an agenda-setting exercise.

Creativity’s most well-known cheerleader is the late Ken Robinson. His advocacy of creativity in education for the purposes of developing human capital is clear from his contribution to the National Advisory Committee on Creative and Cultural Education (1999) report. Subsequently, he changed his tune a little, and was careful to expand on his reasons for promoting creativity. Creativity, for Robinson, became something of broader importance than it was for those with a 21^st century skills agenda. ‘There’s a lot of talk these days about 21st century skills,’ he said, ‘and I go along with a great deal of it, my only reservation about the idea of 21st century skills is that when they’re listed, they often include skills that were relevant at any time, in any century, it’s not that they’re a completely brand new set of things that people need to learn now that they didn’t have to learn before, but the context is very different’. In another interview, when pushed about creativity as an ‘essential 21^st century skill’ – ‘why is creativity especially important right now?’ – Robinson again avoided going too far down the 21^st century skills path. In reply, he offered a number of reasons, but the economy was the last that he mentioned. Human capital mattered to Robinson (‘any conversation about education that doesn’t take account of the economy is really, in some respects, detached and naïve from the world that we live in’ he said in another interview), but he made a point of downplaying it. As a highly accomplished rhetorician, Robinson knew how to tailor his messages for his audiences. His success and fame were due in large part to his ability to craft messages for everybody, and his readiness to allow the significance of creativity to shift from one meaning to another played, in my view, a large role in his appeal.

In ELT, there is no doubt that creativity is, as Maley and Kiss (2018: v) put it, ‘a fashionable concept’. In addition to Maley & Kiss’s ‘Creativity and English Language Teaching’ (2018), recent publications have included ‘The Creative Teacher’s Compendium’ (Clare & Marsh, 2020), ‘Hacking Creativity’ (Peachey, 2019), ‘50 Creative Activities’ (Maley, 2018), ‘Creativity in English Language Teaching’ (Xerri & Vassallo, 2016), ‘Creativity in the English language classroom’ (Maley & Peachey, 2015) and ‘Being Creative’ (Pugliese, 2010). In addition, there have been chapters on creativity in recent books about 21^st century skills in ELT, such as ‘21st Century Skills in the ELT Classroom – A Guide for Teachers’ (Graham, 2020) and ‘English for 21^st Century Skills’ (Mavridi & Xerri, 2020). Robinson is regularly cited.

What is striking about all these publications is that the kind of creativity that is promoted has virtually nothing to do with the kind of creativity that has been discussed in the first part of this article. The notion of language learners as human capital is absent, the purpose of creativity teaching is entirely different, and the creativity of the 4 Cs of 21^st century skills has transformed into something else altogether. Even in the edited collections with ‘21^st century skills’ in their titles, creativity has little or nothing to do with the creativity of the OECD. In most of these titles, ‘21^st century skills’ are not mentioned at all, or only briefly in passing. In the 330 pages of Maley and Kiss (2018), for example, there are only three mentions of the term.

Instead, we have something that is not very ‘21^st century’ at all. Definitions of creativity in these ELT books are very broad, and acknowledge the problems in even providing a definition. Recognising these difficulties, Nik Peachey (2019: iv) doesn’t even attempt to provide a definition. Instead, he offers a selection of ideas and activities which have something to do with the concept. Maley (in Xerri & Vassallo, 2016: 10) takes a similar approach, offering a list of attributes, including things like newness / originality, immediacy, wonder, curiosity / play, inspiration, finding / making connections, unpredictability, relevance and flow. Pugliese (2010: 114) asks teachers how they interpret creativity and this list includes problem-solving, the teacher’s aesthetic drive, a combination of the previous two, and a search for Rogerian self-actualization. Both writers focus heavily on the teacher’s own commitment to creativity. For Pugliese (2010: 12), ‘creativity is about wanting to be creative’.

In practice, the classroom ideas that are on offer can usually be put into one or more of the following categories:

• Activities that involve the arts: drama, stories, music, song, chants, poetry and dance, etc. Maley (2018) is especially interested in poetry, and Pugliese (2010) explores music and the visual arts in more detail.
• Activities that involves the learners in personalized self-expression, with emotional responses prioritized.
• Activities which are in some way exploratory, unpredictable or ‘different’. The work of John Fanselow (e.g. 1987) is an important inspiration here.

The overall result is a relabelled mash-up of ideas that have been around for some time: exploitation of literature, music and art; humanistic approaches inspired by Stevick, Rinvolucri and others; a sprinkling of positive psychology; and, sometimes, suggestions for using digital technology to facilitate creative expression of some kind. I hope I am not being unfair if I suggest that the problem of definition arises because the 21^st century label of creativity has been stuck on bottles of vintage wine.

Most of these writers seem content to ignore 21^st century OECD-style creativity, to pretend that it is not the driver of the ‘fashionable concept’ they are writing about. However, the reason for this silence surfaces from time to time: most of these ELT writers disapprove of, even dislike, the OECD version of creativity. Here, for example, is Chris Kennedy in the foreword to Maley & Peachey (2015: 2):

‘It is worrying in our market-driven world that […] certain concepts, and the words used to express them, lose their value through over-use or ill-definition. […] The danger is that such terms may be hijacked by public bodies and private institutions which employ them as convenient but opaque policy pegs on which practitioners, including educators, are expected to hang their approaches and behaviours. ‘Creativity’ is one such term, and UK government reports on the subject in the last few years show the concept of creativity being used to support a particular instrumental political view as a means of promoting the economy, rather than as a focus for developing individual skills and talents.’

And here’s David Nunan (in Mavridi & Xerri, 2020: 6) dishing out some vitriol:

‘I have been unable to find any evidence that the ability to solve such [problem-solving 21^st century-style creativity tasks] transfers to the ability to solve such problems in real life. This has not stopped some people building their careers out of the concept and amassing considerable compensation in the process. Robinson even garnered a knighthood’.

This is all rather strange. It is creativity as a 21^st century skill that has made the topic a ‘fashionable concept’. The ideas of Alan Maley et al about creativity become more plausible because the meaning of the key term can shift around. His book (with Nik Peachey) was commissioned by the British Council, an organisation that is profoundly committed to the idea that 21^st century skills, including creativity, are essential for young people ‘to be fully prepared for life and work in a global economy’. In this light, Maley & Peachey (2015), which kicks off with a Maley poem before the Chris Kennedy foreword, may almost be seen as a subversive hijacking, a détournement of British Council discourse. But détourneurs can be détourné in their turn …

Maley’s co-author, Tamas Kiss, on ‘Creativity and English Language Teaching’, a book which so strenuously avoided the discourse of 21^st century creativity, chose to discuss this work in the following way for a webpage for his university:

‘Dr Kiss explained that creativity has been the subject of investigation in several fields including psychology and business, as well as language teaching, and is one of the ‘core skills’ of most 21st century educational frameworks:

“People have realised that traditional knowledge transfer systems are not necessarily preparing students for 21st century jobs,” said Tamas, “New educational frameworks, for example those developed by the Council of Europe, emphasize cross-cultural communication, problem-solving, and creativity.”’

The university in question is Xi’an Jiaotong University, to the west of Shanghai. In the same year as the publication of the book that Kiss co-authored with Maley, Barbara Schulte gave a conference presentation entitled ‘Appropriating or hijacking creativity? Educational reform and creative learning in China’ (Schulte, 2018). She noted the increasing importance accorded to creativity in China’s educational reforms, the country’s increasing engagement with OECD benchmarks, and the way in which creative approaches ‘originally intended to empower learners are turned into their exact opposites, constraining learners’ spaces even more than with conventional approaches’.

Creativity is a classic weasel word. Its use should come accompanied with a hazard warning.

References

Clare, A. & Marsh, A. (2020). The Creative Teacher’s Compendium. Teddington, Middx.: Pavilion

Fanselow, J. (1987). Breaking Rules. Harlow: Longman

Graham, C. (Ed.) (2020). 21st Century Skills in the ELT Classroom – A Guide for Teachers. Reading: Granet

Guilford, J. P. (1950). Creativity. American Psychologist, 5 (9): pp.444–454

Maley, A. (2018). Alan Maley’s 50 Creative Activities. Cambridge: Cambridge University Press

Maley, A. & Kiss, T. (2018). Creativity and English Language Teaching. London: Palgrave Macmillan

Maley, A. & Peachey, N. (Eds.) (2015). Creativity in the English language classroom. London: British Council

Mavridi, S. & Xerri, D. (Eds.) English for 21^st Century Skills. Newbury, Berks.: Express Publishing

National Advisory Committee on Creative and Cultural Education. (1999). All Our Futures: Creativity, Culture and Education http://sirkenrobinson.com/pdf/allourfutures.pdf

OECD (2019). PISA 2021 Creative Thinking Framework (Third Draft). Paris: OECD.

Peachey, N. (2019). Hacking Creativity. PeacheyPublications.

Pugliese, C. (2010). Being Creative. Peaslake: DELTA

Razik, T. A. (1967). Psychometric measurement of creativity. In Mooney, R. L. & Razik, T. A. (Eds.) Explorations in Creativity. New York: Harper & Row

Rogers, C. (1954). Toward a Theory of Creativity. ETC: A Review of General Semantics, 11: pp. 249-260

Schulte, B. (2018). Appropriating or hijacking creativity? Educational reform and creative learning in China. Abstract from Australian Association for Research in Education (AARE) Conference 2018, Sydney, Australia.

Shapin, S. (2020). The rise and rise of creativity. Aeon 12 October 2020 https://aeon.co/essays/how-did-creativity-become-an-engine-of-economic-growth

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

World Bank (2010). Stepping Up Skills. Washington: The World Bank

Xerri, D. & Vassallo, O. (Eds.) (2016). Creativity in English Language Teaching. Floriana: ELT Council

Bored or boring – instructional grammar videos for flipped learning

Flipped learning undoubtedly has much potential and now, when F2F teaching is not always possible, the case for exploring what it might offer seems greater still. For a variety of reasons (not the least of which are motivational issues), it may not always be possible to flip the classroom, but, if and when it is, how and what should be flipped?

In the most well-known flipped approaches, such as the Khan Academy, students watch instructional videos in their own time, before coming to class where they can work together on practical problems, applying the knowledge they have gained from the instructional video. The flipped part of the learning does not need to be a video (Bergmann et al., 2013), but, in practice, it usually is. But whether video or something else, one of the big questions for me is what, precisely, does it make sense to flip?

In a recently published Cambridge Paper in ELT that I wrote on Flipped Learning, I noted that it is not uncommon for grammar instruction to be flipped. Al-Harbi & Alshumaimeri (2016), for example, describe a Saudi secondary school where the teacher selected a number of grammar areas from the coursebook and then identified instructional videos from YouTube that addressed these areas. Buitrago & Díaz (2018) describe a Colombian university where students were required to watch instructional videos about grammar, some of which were selected from YouTube and others created by members of staff.

To understand better what learners might be doing in their flipped time, I decided to take a look at a selection of YouTube grammar videos. I focussed on one area of grammar only (‘bored’ vs ‘boring’) and from the huge selection available, I prioritised those that were the most popular. Here’s what I found. After a brief commentary on each of the 10 videos, I wrap up with a few observations.

mmmEnglish 1245K views 8.33 minutes

Early on, Emma says ‘These endings are called suffixes and when we add them to the end of a verb, they transform our verb into an adjective, but you need to know how to use each of these types of adjectives and we’re gonna do that right now’. This gives a good taste of what follows. We learn that –ing adjectives refer to ‘the characteristics of a person, a thing, or a situation’ while –ed adjectives refer to an ‘emotion or a feeling’. Bearing in mind that this area of grammar is listed as A2+ (in Pearson’s GSE), explanations of this kind in English may be tricky for many learners. The language grading in explanations like ‘If you say that someone or something is boring, they or it makes you feel bored. Do the thing or the person that is boring is what makes you feel bored. It bores you. OK, there’s our verb’ needs a little attention! On and on goes Emma, until after almost five minutes she reads out a few sentences and students have to decide if the correct adjective has been used. Over a million people have watched this.

Learn English with Let’s Talk 452K views 8.52 minutes

Rashna explains: ‘First, let’s begin by understanding what are adjectives’. My heart sinks. ‘So ‘pretty’ is doing the job of describing or bringing about a quality of the noun ‘girl’, so ‘pretty’ becomes my adjective. So when you’re confused and don’t know how to spot the adjectives, ask the question ‘what kind’. All right. So, if I say I live in a big city, and if I ask what kind of a city, it’s big, so ‘big’ is an adjective that is describing the noun ‘city’. All right. So remember, adjectives are nothing but just words that describe a noun that tell you more about it or bring about some quality.’ Over a quarter of the way through and we haven’t yet got on to –ed and –ing. I recommend watching all the way through to the end just to admire the whiteboard work. You might enjoy the comments, too (e.g. ‘Thanks very much. This lesson was confused me so much.’) Coming up for half a million views.

Alejo Lopera Inglés 428K views 4.07 minutes

The only English here is in the example sentences, with Spanish being used for the rest. The explanation hinges on ‘pienso’ (think) for –ing and ‘sentimiento’ (feeling) for –ed, which only kind of works. Alejo takes us through a few examples using a combination of talking-head video and background slides. His delivery is engaging and using Spanish makes things clearer than English only.

English Lessons with Adam 357K views 5.27 minutes

Standing in front of the whiteboard, Adam says that his video is especially useful for beginners. He rambles on for over 5 minutes in language which is far more complicated than the language he is explaining. Here’s a flavour: Now, what does it mean to be bored and what does it mean to be boring? When we talk about “bored”, we’re describing a feeling. Okay? When we talk about “interested”, we’re describing a feeling. So all of the “ed” adjectives are actually feelings, and you can only use them to talk about people and sometimes animals. Why? Because things, like chairs, or tables, or whatever, they don’t have feelings. […]”I am worried”, now people don’t realize that “worried” can have “worrying” as another adjective. “The situation is worrying” means the situation is making me feel worried. Okay? Maybe the whole global political situation, whatever. Now, hopefully none of you are confused by this lesson because I’m trying to make it not confusing. Okay? Everybody okay with that? […] Now, I just want to point out one other thing: Don’t confuse feeling adjectives with “ed” with actual feelings. Okay? If somebody is loved, does he feel loved? Maybe yes, maybe no. We’re not talking about that person’s feelings.

Crown Academy of English 270K views 26.57 minutes

Using screen capture and voiceover software, the script is mostly read aloud from the screen. There is no attempt to make either the script or the delivery interesting. The approach is as traditional as can be: it focuses first on form, with no shying away from grammatical jargon, and eventually moves on to meaning. And then, if you’re still awake, there’s a discrimination exercise. After over 25 minutes of death-by-Powerpoint, the lesson comes, mercifully, to an end.

 

Learn English with Rebecca 274K views 3.30 minutes

From the same stable as Adam’s video, this is more controlled than his ramble, and with slightly better language grading, but is still hard to follow, in part because no examples are given in written form. As with Adam, Rebecca bangs on about how important it is to get this grammar right, because ‘if you make a mistake you could be saying something very unpleasant about yourself’. It’s hard to tell what level it’s intended for.

Francisco Ochoa Inglés Fácil 64K views 11.02 minutes

Switching between Spanish and English, Pacho rattles non-stop through 6 discrimination sentences, taking the difference between feelings (which take the Spanish ‘estar’) and states (which take the Spanish ‘ser’) as his key explanatory tool. This doesn’t quite work, but following his breakneck delivery is more of a problem. The only thing he doesn’t translate are the commas in his examples. I challenge you not to feel confused / confusing by the time he gets to the third sentence. Even Pacho seems to be struggling. Words like ‘hence’ and tenses like past perfect continuous don’t help his 11 minute monologue. I loved the way that he says at the end that the only way to learn this stuff is by applying the language in the way he has just done.

BBC Learning English 48K views 0.56 minutes

In under a minute, Sam from BBC Learning English achieves much greater clarity than anyone else I watched, helped by a carefully planned script, very controlled language and a split screen showing the key points as she makes them. Towards the end, she rattles through 5 more –ed / -ing pairs rather too quickly. It’s a shame, I thought, that she (or the producers) felt the need to reference the old trope about how boring grammar lessons are.

Shaw English Online 46K views 8.49 minutes

The explanation is mercifully brief and the language of Fanny, the presenter, is well controlled. We could do without the exhortations to listen carefully, etc, ‘because this is very important’, but you can’t have everything. A lot of examples are given, before the explanations are repeated. The repetitions don’t help as Fanny resorts to more complicated language than the language she is explaining (e.g. ‘But when you say the teacher was boring, you are describing the teacher, OK, the teacher made the students feel bored, because he or she was boring’). After nearly 4 minutes of presentation, there are some practice discrimination tasks, but Fanny’s relentless commentary gets seriously in the way. The lesson is rounded off with a few minutes of repeat-after-me pronunciation practice.

Mad English TV 24K views 6.59 minutes

In a surreal opening, the presenter talks about the three different states of H2O, before explaining that people, too, can have different states. Eventually, we get to the idea that ‘boring’ is an accusation, ‘bored’ is a state: ‘If you go up to your teacher and say ‘you’re boring’, that’s an insult’. The language grading is all over the place, as is the explanation itself. As a general rule, the longer the explanation, the less clear it is. At 7 minutes, this video is no exception to the rule. When we get to a mini-test (a useful feature that not all other videos have), the choice is ‘My cat is _______’. To know the answer, you need to know if you’re making an accusation about the cat. Got it?

Flipped learning and grammar

Although grammar instruction might seem a strong candidate for a flipped treatment, videoed explanations are clearly not the way to do it. Many coursebooks have perfectly adequate guided discoveries of this and other standard grammar points. Newer courses on platforms have interactive guided discoveries (and often also offer a more traditional deductive route) that will also do the trick much better than videoed explanations. Would learners not be better off doing something else altogether with their time? Initial vocabulary study, listening, reading, writing, almost anything in fact, is a more appropriate target for flipping than grammar, when approached in this way. Video is not the solution to a problem: on the evidence here, it makes the problem worse.

The popularity of grammar videos

It’s very hard to watch this stuff and not scoff, but there’s no denying the immense popularity of videos like these. Much as I find it difficult to believe, people must be learning something (or think they are learning something) from watching them. Otherwise, they presumably wouldn’t consume them to such an extent. Perhaps, these videos conform to expectations about what English lessons should be like? Perhaps viewers subscribe to a belief in ‘no pain, no gain’? Perhaps they simply don’t know where to find something that would help them more? Or perhaps they have been told to watch by their flipping teachers?

Emma has had 1.25 million views. Advertising earnings from 1 million YouTube views are generally reckoned to be between $600-$7000, but are likely to be at the higher end of this scale if (1) people watch the video through to the end (which is probably the case here), and (2) viewers interact with the video through likes and comment (for this video Emma has received 2353 comments). Earnings are also higher when you have more subscribers to your channel. Emma can count on 3.25 million subscribers and Rachna of Let’s Talk has 4.77 million subscribers. By way of contrast, Russell Stannard’s Teacher Training Videos has 40,000 subscribers. There’s gold in them thar hills.

Grammar videos and the world of ELT

Free grammar videos, along with self-study apps like Duolingo, are a huge and thriving sector of ELT. They rarely, if ever, feature in research, conference presentations or the broader discourse of ELT, a world, it seems, much more oriented to products you have to pay for.

References

Al-Harbi, S.S., & Alshumaimeri, Y.A. (2016). The flipped classroom impact in grammar class on EFL Saudi secondary school students’ performances and attitudes. English Language Teaching, 9(10): 60–80. Available at: https://files.eric.ed.gov/fulltext/EJ1113506.pdf

Bergmann, J., Overmeyer, J., & Wilie, B. (2013). The flipped class: myth vs. reality. The Daily Riff, July 9, 2013. Available at: http://www.thedailyriff.com/articles/the-flipped-class-conversation-689.php

Buitrago, C. R., & Díaz, J. (2018). Flipping your writing lessons: Optimizing your time in your EFL writing classroom. In Mehring, J., & Leis, A. (Eds.), Innovations in Flipping the Language Classroom. Singapore: Springer, 69–91.

Unpacking ‘the new normal’ in ELT

What is the ‘new normal’?

Among the many words and phrases that have been coined or gained new currency since COVID-19 first struck, I find ‘the new normal’ particularly interesting. In the educational world, its meaning is so obvious that it doesn’t need spelling out. But in case you’re unclear about what I’m referring to, the title of this webinar, run by GENTEFL, the Global Educators Network Association of Teachers of English as a Foreign Language (an affiliate of IATEFL), will give you a hint.

Teaching in a VLE may be overstating it a bit, but you get the picture. ‘The new normal’ is the shift away from face-to-face teaching in bricks-and-mortar institutions, towards online teaching of one kind or another. The Malaysian New Straits Times refers to it as ‘E-learning, new way forward in new norm’. The TEFL Academy says that ‘digital learning is the new normal’, and the New Indian Express prefers the term ‘tech education’.

I’ll come back to these sources in a little while.

Whose new normal?

There is, indeed, a strong possibility that online learning and teaching may become ‘the new normal’ for many people working in education. In corporate training and in higher education, ‘tech education’ will likely become increasingly common. Many universities, especially but not only in the US, Britain and Australia, have been relying on ‘international students’ (almost half a million in the UK in 2018/ 2019), in particular Chinese, to fill their coffers. With uncertainty about how and when these universities will reopen for the next academic year, a successful transition to online is a matter of survival – a challenge that a number of universities will probably not be able to rise to. The core of ELT, private TEFL schools in Inner Circle countries, likewise dependent on visitors from other countries, has also been hard hit. It is not easy for them to transition to online, since the heart of their appeal lies in their physical location.

But elsewhere, the picture is rather different. A recent Reddit discussion began as follows: ‘In Vietnam, [English language] schools have reopened and things have returned to normal almost overnight. There’s actually a teacher shortage at the moment as so many left and interest in online learning is minimal, although most schools are still offering it as an option’. The consensus in the discussion that follows is that bricks-and-mortar schools will take a hit, especially with adult (but not kids’) groups, but that ‘teaching online will not be the new normal’.

By far the greatest number of students studying English around the world are in primary and secondary schools. It is highly unlikely that online study will be the ‘new normal’ for most of these students (although we may expect to see attempts to move towards more blended approaches). There are many reasons for this, but perhaps the most glaringly obvious is that the function of schools is not exclusively educational: child-care, allowing parents to go to work, is the first among these.

We can expect some exceptions. In New York, for example, current plans include a ‘hybrid model’ (a sexed-up term for blended learning), in which students are in schools for part of the time and continue learning remotely for the rest. The idea emerged after Governor Andrew Cuomo ‘convened a committee with the Bill and Melinda Gates Foundation to reimagine education for students when school goes back in session in the fall’. How exactly this will pan out remains to be seen, but, in much of the rest of the world, where the influence of the Gates Foundation is less strong, ‘hybrid schooling’ is likely to be seen as even more unpalatable and unworkable than it is by many in New York.

In short, the ‘new normal’ will affect some sectors of English language teaching much more than others. For some, perhaps the majority, little change can be expected once state schools reopen. Smaller classes, maybe, more blended, but not a wholesale shift to ‘tech education’.

Not so new anyway!

Scott Galloway, a New York professor of marketing and author of the best-selling ‘The Four’ (an analysis of the Big Four tech firms), began a recent blog post as follows:

After COVID-19, nothing will be the same. The previous sentence is bullsh*t. On the contrary, things will never be more the same, just accelerated.

He elaborates his point by pointing out that many universities were already in deep trouble before COVID. Big tech had already moved massively into education and healthcare, which are ‘the only two sectors, other than government, that offer the margin dollars required to sate investors’ growth expectations’ (from another recent post by Galloway). Education start-ups have long been attracting cheap capital: COVID has simply sped the process up.

Coming from a very different perspective, Audrey Watters gave a conference presentation over three years ago entitled ‘Education Technology as ‘The New Normal’’. I have been writing about the normalization of digital tools in language teaching for over six years. What is new is the speed, rather than the nature, of the change.

Galloway draws an interesting parallel with the SARS virus, which, he says, ‘was huge for e-commerce in Asia, and it helped Alibaba break out into the consumer space. COVID-19 could be to education in the United States what SARS was to e-commerce in Asia’.

‘The new normal’ as a marketing tool

Earlier in this post, I mentioned three articles that discussed the ‘new normal’ in education. The first of these, from the New Straits Times, looks like a news article, but features extensive quotes from Shereen Chee, chief operating officer of Sunago Education, a Malaysian vendor of online English classes. The article is basically an advert for Sunago: one section includes the following:

Sunago combines digitisation and the human touch to create a personalised learning experience. […] Chee said now is a great time for employers to take advantage of the scheme and equip their team with enhanced English skills, so they can hit the ground running once the Covid-19 slump is over.

The second reference about ‘digital learning is the new normal’ comes from The TEFL Academy, which sells online training courses, particularly targeting prospective teachers who want to work online. The third reference, from the New Indian Express, was written by Ananth Koppar, the founder of Kshema Technologies Pvt Ltd, India’s first venture-funded software company. Koppar is hardly a neutral reporter.

Other examples abound. For example, a similar piece called ‘The ‘New Normal’ in Education’ can be found in FE News (10 June 2020). This was written by Simon Carter, Marketing and Propositions Director of RM Education, an EdTech vendor in the UK. EdTech has a long history of promoting its wares through sponsored content and adverts masquerading as reportage.

It is, therefore, a good idea, whenever you come across the phrase, ‘the new normal’, to adopt a sceptical stance from the outset. I’ll give two more examples to illustrate my point.

A recent article (1 April 2020) in the ELTABB (English Language Teachers Association Berlin Brandenburg) journal is introduced as follows:

With online language teaching being the new normal in ELT, coaching principles can help teachers and students share responsibility for the learning process.

Putting aside, for the moment, my reservations about whether online teaching is, in fact, the new normal in ‘ELT’, I’m happy to accept that coaching principles may be helpful in online teaching. But I can’t help noticing that the article was written by a self-described edupreneur and co-founder of the International Language Coaching Association (€50 annual subscription) which runs three-day training courses (€400).

My second example is a Macmillan webinar by Thom Kiddle called ‘Professional Development for teachers in the ‘new normal’. It’s a good webinar, a very good one in my opinion, but you’ll notice a NILE poster tacked to the wall behind Thom as he speaks. NILE, a highly reputed provider of teacher education courses in the UK, has invested significantly in online teacher education in recent years and is well-positioned to deal with the ‘new normal’. It’s also worth noting that the webinar host, Macmillan, is in a commercial partnership with NILE, the purpose of which is to ‘develop and promote quality teacher education programmes worldwide’. As good as the webinar is, it is also clearly, in part, an advertisement.

The use of the phrase ‘the new normal’ as a marketing hook is not new. Although its first recorded use dates back to the first part of the 20^th century, it became more widespread at the start of the 21^st. One populariser of the phrase was Roger McNamee, a venture capitalist and early investor in technology, including Facebook, who wrote a book called ‘The New Normal: Great Opportunities in a Time of Great Risk’ (2004). Since then, the phrase has been used extensively to refer to the state of the business world after the financial crisis of 2018. (For more about the history of the phrase, see here.) More often than not, users of the phrase are selling the idea (and sometimes a product) that we need to get used to a new configuration of the world, one in which technology plays a greater role.

Normalizing ‘the new normal’

Of all the most unlikely sources for a critique of ‘the new normal’, the World Economic Forum has the following to offer in a blog post entitled ‘There’s nothing new about the ‘new normal’. Here’s why’:

The language of a ‘new normal’ is being deployed almost as a way to quell any uncertainty ushered in by the coronavirus. With no cure in sight, everyone from politicians and the media to friends and family has perpetuated this rhetoric as they imagine settling into life under this ‘new normal’. This framing is inviting: it contends that things will never be the same as they were before — so welcome to a new world order. By using this language, we reimagine where we were previously relative to where we are now, appropriating our present as the standard. As we weigh our personal and political responses to this pandemic, the language we employ matters. It helps to shape and reinforce our understanding of the world and the ways in which we choose to approach it. The analytic frame embodied by the persistent discussion of the ‘new normal’ helps bring order to our current turbulence, but it should not be the lens through which we examine today’s crisis.

We can’t expect the World Economic Forum to become too critical of the ‘new normal’ of digital learning, since they have been pushing for it so hard for so long. But the quote from their blog above may usefully be read in conjunction with an article by Jun Yu and Nick Couldry, called ‘Education as a domain of natural data extraction: analysing corporate discourse about educational tracking’ (Information, Communication and Society, 2020, DOI: 10.1080/1369118X.2020.1764604). The article explores the general discursive framing by which the use of big data in education has come to seem normal. The authors looked at the public discourse of eight major vendors of educational platforms that use big data (including Macmillan, Pearson, Knewton and Blackboard). They found that ‘the most fundamental move in today’s dominant commercial discourse is to promote the idea that data and its growth are natural’. In this way, ‘software systems, not teachers, [are] central to education’. Yu and Couldry’s main interest is in the way that discourse shapes the normalization of dataveillance, but, in a more general sense, the phrase, ‘the new normal’, is contributing to the normalization of digital education. If you think that’s fine, I suggest you dip into some of the books I listed in my last blog post.

TEFL, platform capitalism and coronavirus

Online teaching is big business. Very big business. Online language teaching is a significant part of it, expected to be worth over $5 billion by 2025. Within this market, the biggest demand is for English and the lion’s share of the demand comes from individual learners. And a sizable number of them are Chinese kids.

There are a number of service providers, and the competition between them is hot. To give you an idea of the scale of this business, here are a few details taken from a report in USA Today. VIPKid, is valued at over $3 billion, attracts celebrity investors, and has around 70,000 tutors who live in the US and Canada. 51Talk has 14,800 English teachers from a variety of English-speaking countries. BlingABC gets over 1,000 American applicants a month for its online tutoring jobs. There are many, many others.

Demand for English teachers in China is huge. The Pie News, citing a Chinese state media announcement, reported in September of last year that there were approximately 400,000 foreign citizens working in China as English language teachers, two-thirds of whom were working illegally. Recruitment problems, exacerbated by quotas and more stringent official requirements for qualifications, along with a very restricted desired teacher profile (white, native-speakers from a few countries like the US and the UK), have led more providers to look towards online solutions. Eric Yang, founder of the Shanghai-based iTutorGroup, which operates under a number of different brands and claims to be the ‘largest English-language learning institution in the world’, said that he had been expecting online tutoring to surpass F2F classes within a few years. With coronavirus, he now thinks it will come ‘much earlier’.

Typically, the work does not require much, if anything, in the way of training (besides familiarity with the platform), although a 40-hour TEFL course is usually preferred. Teachers deliver pre-packaged lessons. According to the USA Today report, Chinese students pay between $49 and $80 dollars an hour for the classes.

It’s a highly profitable business and the biggest cost to the platform providers is the rates they pay the tutors. If you google “Teaching TEFL jobs online”, you’ll quickly find claims that teachers can earn $40 / hour and up. Such claims are invariably found on the sites of recruitment agencies, who are competing for attention. However, although it’s possible that a small number of people might make this kind of money, the reality is that most will get nowhere near it. Scroll down the pages a little and you’ll discover that a more generally quoted and accepted figure is between $14 and $20 / hour. These tutors are, of course, freelancers, so the wages are before tax, and there is no health coverage or pension plan.

VIPKid, for example, considered to be one of the better companies, offers payment in the $14 – $22 / hour range. Others offer considerably less, especially if you are not a white, graduate US citizen. Current rates advertised on OETJobs include work for Ziktalk ($10 – 15 / hour), NiceTalk ($10 – 11 / hour), 247MyTutor ($5 – 8 / hour) and Weblio ($5 – 6 / hour). The number of hours that you get is rarely fixed and tutors need to build up a client base by getting good reviews. They will often need to upload short introductory videos, selling their skills. They are in direct competition with other tutors.

They also need to make themselves available when demand for their services is highest. Peak hours for VIPKid, for example, are between 2 and 8 in the morning, depending on where you live in the US. Weekends, too, are popular. With VIPKid, classes are scheduled in advance, but this is not always the case with other companies, where you log on to show that you are available and hope someone wants you. This is the case with, for example, Cambly (which pays $10.20 / hour … or rather $0.17 / minute) and NiceTalk. According to one review, Cambly has a ‘priority hours system [which] allows teachers who book their teaching slots in advance to feature higher on the teacher list than those who have just logged in, meaning that they will receive more calls’. Teachers have to commit to a set schedule and any changes are heavily penalised. The review states that ‘new tutors on the platform should expect to receive calls for about 50% of the time they’re logged on’.

 

Taking the gig economy to its logical conclusion, there are other companies where tutors can fix their own rates. SkimaTalk, for example, offers a deal where tutors first teach three unpaid lessons (‘to understand how the system works and build up their initial reputation on the platform’), then the system sets $16 / hour as a default rate, but tutors can change this to anything they wish. With another, Palfish, where tutors set their own rate, the typical rate is $10 – 18 / hour, and the company takes a 20% commission. With Preply, here is the deal on offer:

Your earnings depend on the hourly rate you set in your profile and how often you can provide lessons. Preply takes a 100% commission fee of your first lesson payment with every new student. For all subsequent lessons, the commission varies from 33 to 18% and depends on the number of completed lesson hours with students. The more tutoring you do through Preply, the less commission you pay.

Not one to miss a trick, Ziktalk (‘currently focusing on language learning and building global audience’) encourages teachers ‘to upload educational videos in order to attract more students’. Or, to put it another way, teachers provide free content in order to have more chance of earning $10 – 15 / hour. Ah, the joys of digital labour!

And, then, coronavirus came along. With schools shutting down, first in China and then elsewhere, tens of millions of students are migrating online. In Hong Kong, for example, the South China Morning Post reports that schools will remain closed until April 20, at the earliest, but university entrance exams will be going ahead as planned in late March. CNBC reported yesterday that classes are being cancelled across the US, and the same is happening, or is likely to happen, in many other countries.

Shares in the big online providers soared in February, with Forbes reporting that $3.2 billion had been added to the share value of China’s e-Learning leaders. Stock in New Oriental (owners of BlingABC, mentioned above) ‘rose 7.3% last month, adding $190 million to the wealth of its founder Yu Minhong [whose] current net worth is estimated at $3.4 billion’.

DingTalk, a communication and management app owned by Alibaba (and the most downloaded free app in China’s iOS App Store), has been adapted to offer online services for schools, reports Xinhua, the official state-run Chinese news agency. The scale of operations is enormous: more than 10,000 new cloud servers were deployed within just two hours.

Current impacts are likely to be dwarfed by what happens in the future. According to Terry Weng, a Shenzhen-based analyst, ‘The gradual exit of smaller education firms means there are more opportunities for TAL and New Oriental. […] Investors are more keen for their future performance.’ Zhu Hong, CTO of DingTalk, observes ‘the epidemic is like a catalyst for many enterprises and schools to adopt digital technology platforms and products’.

For edtech investors, things look rosy. Smaller, F2F providers are in danger of going under. In an attempt to mop up this market and gain overall market share, many elearning providers are offering weighty discounts and free services. Profits can come later.

For the hundreds of thousands of illegal or semi-legal English language teachers in China, things look doubly bleak. Their situation is likely to become even more precarious, with the online gig economy their obvious fall-back path. But English language teachers everywhere are likely to be affected one way or another, as will the whole world of TEFL.

Now seems like a pretty good time to find out more about precarity (see the Teachers as Workers website) and native-speakerism (see TEFL Equity Advocates).

The Unlearned Lessons of Programmed Learning

From time to time, I have mentioned Programmed Learning (or Programmed Instruction) in this blog (here and here, for example). It felt like time to go into a little more detail about what Programmed Instruction was (and is) and why I think it’s important to know about it.

A brief description

The basic idea behind Programmed Instruction was that subject matter could be broken down into very small parts, which could be organised into an optimal path for presentation to students. Students worked, at their own speed, through a series of micro-tasks, building their mastery of each nugget of learning that was presented, not progressing from one to the next until they had demonstrated they could respond accurately to the previous task.

There were two main types of Programmed Instruction: linear programming and branching programming. In the former, every student would follow the same path, the same sequence of frames. This could be used in classrooms for whole-class instruction and I tracked down a book (illustrated below) called ‘Programmed English Course Student’s Book 1’ (Hill, 1966), which was an attempt to transfer the ideas behind Programmed Instruction to a zero-tech, class environment. This is very similar in approach to the material I had to use when working at an Inlingua school in the 1980s.

An example of how self-paced programming worked is illustrated here, with a section on comparatives.

With branching programming, ‘extra frames (or branches) are provided for students who do not get the correct answer’ (Kay et al., 1968: 19). This was only suitable for self-study, but it was clearly preferable, as it allowed for self-pacing and some personalization. The material could be presented in books (which meant that students had to flick back and forth in their books) or with special ‘teaching machines’, but the latter were preferred.

In the words of an early enthusiast, Programmed Instruction was essentially ‘a device to control a student’s behaviour and help him to learn without the supervision of a teacher’ (Kay et al.,1968: 58). The approach was inspired by the work of Skinner and it was first used as part of a university course in behavioural psychology taught by Skinner at Harvard University in 1957. It moved into secondary schools for teaching mathematics in 1959 (Saettler, 2004: 297).

Enthusiasm and uptake

The parallels between current enthusiasm for the power of digital technology to transform education and the excitement about Programmed Instruction and teaching machines in the 1960s are very striking (McDonald et al., 2005: 90). In 1967, it was reported that ‘we are today on the verge of what promises to be a revolution in education’ (Goodman, 1967: 3) and that ‘tremors of excitement ran through professional journals and conferences and department meetings from coast to coast’ (Kennedy, 1967: 871). The following year, another commentator referred to the way that the field of education had been stirred ‘with an almost Messianic promise of a breakthrough’ (Ornstein, 1968: 401). Programmed instruction was also seen as an exciting business opportunity: ‘an entire industry is just coming into being and significant sales and profits should not be too long in coming’, wrote one hopeful financial analyst as early as 1961 (Kozlowski, 1967: 47).

The new technology seemed to offer a solution to the ‘problems of education’. Media reports in 1963 in Germany, for example, discussed a shortage of teachers, large classes and inadequate learning progress … ‘an ‘urgent pedagogical emergency’ that traditional teaching methods could not resolve’ (Hof, 2018). Individualised learning, through Programmed Instruction, would equalise educational opportunity and if you weren’t part of it, you would be left behind. In the US, two billion dollars were spent on educational technology by the government in the decade following the passing of the National Defense Education Act, and this was added to by grants from private foundations. As a result, ‘the production of teaching machines began to flourish, accompanied by the marketing of numerous ‘teaching units’ stamped into punch cards as well as less expensive didactic programme books and index cards. The market grew dramatically in a short time’ (Hof, 2018).

In the field of language learning, however, enthusiasm was more muted. In the year in which he completed his doctoral studies[1], the eminent linguist, Bernard Spolsky noted that ‘little use is actually being made of the new technique’ (Spolsky, 1966). A year later, a survey of over 600 foreign language teachers at US colleges and universities reported that only about 10% of them had programmed materials in their departments (Valdman, 1968: 1). In most of these cases, the materials ‘were being tried out on an experimental basis under the direction of their developers’. And two years after that, it was reported that ‘programming has not yet been used to any very great extent in language teaching, so there is no substantial body of experience from which to draw detailed, water-tight conclusions’ (Howatt, 1969: 164).

By the early 1970s, Programmed Instruction was already beginning to seem like yesterday’s technology, even though the principles behind it are still very much alive today (Thornbury (2017) refers to Duolingo as ‘Programmed Instruction’). It would be nice to think that language teachers of the day were more sceptical than, for example, their counterparts teaching mathematics. It would be nice to think that, like Spolsky, they had taken on board Chomsky’s (1959) demolition of Skinner. But the widespread popularity of Audiolingual methods suggests otherwise. Audiolingualism, based essentially on the same Skinnerian principles as Programmed Instruction, needed less outlay on technology. The machines (a slide projector and a record or tape player) were cheaper than the teaching machines, could be used for other purposes and did not become obsolete so quickly. The method also lent itself more readily to established school systems (i.e. whole-class teaching) and the skills sets of teachers of the day. Significantly, too, there was relatively little investment in Programmed Instruction for language teaching (compared to, say, mathematics), since this was a smallish and more localized market. There was no global market for English language learning as there is today.

Lessons to be learned

1 Shaping attitudes

It was not hard to persuade some educational authorities of the value of Programmed Instruction. As discussed above, it offered a solution to the problem of ‘the chronic shortage of adequately trained and competent teachers at all levels in our schools, colleges and universities’, wrote Goodman (1967: 3), who added, there is growing realisation of the need to give special individual attention to handicapped children and to those apparently or actually retarded’. The new teaching machines ‘could simulate the human teacher and carry out at least some of his functions quite efficiently’ (Goodman, 1967: 4). This wasn’t quite the same thing as saying that the machines could replace teachers, although some might have hoped for this. The official line was more often that the machines could ‘be used as devices, actively co-operating with the human teacher as adaptive systems and not just merely as aids’ (Goodman, 1967: 37). But this more nuanced message did not always get through, and ‘the Press soon stated that robots would replace teachers and conjured up pictures of classrooms of students with little iron men in front of them’ (Kay et al., 1968: 161).

For teachers, though, it was one thing to be told that the machines would free their time to perform more meaningful tasks, but harder to believe when this was accompanied by a ‘rhetoric of the instructional inadequacies of the teacher’ (McDonald, et al., 2005: 88). Many teachers felt threatened. They ‘reacted against the ‘unfeeling machine’ as a poor substitute for the warm, responsive environment provided by a real, live teacher. Others have seemed to take it more personally, viewing the advent of programmed instruction as the end of their professional career as teachers. To these, even the mention of programmed instruction produces a momentary look of panic followed by the appearance of determination to stave off the ominous onslaught somehow’ (Tucker, 1972: 63).

Some of those who were pushing for Programmed Instruction had a bigger agenda, with their sights set firmly on broader school reform made possible through technology (Hof, 2018). Individualised learning and Programmed Instruction were not just ends in themselves: they were ways of facilitating bigger changes. The trouble was that teachers were necessary for Programmed Instruction to work. On the practical level, it became apparent that a blend of teaching machines and classroom teaching was more effective than the machines alone (Saettler, 2004: 299). But the teachers’ attitudes were crucial: a research study involving over 6000 students of Spanish showed that ‘the more enthusiastic the teacher was about programmed instruction, the better the work the students did, even though they worked independently’ (Saettler, 2004: 299). In other researched cases, too, ‘teacher attitudes proved to be a critical factor in the success of programmed instruction’ (Saettler, 2004: 301).

2 Returns on investment

Pricing a hyped edtech product is a delicate matter. Vendors need to see a relatively quick return on their investment, before a newer technology knocks them out of the market. Developments in computing were fast in the late 1960s, and the first commercially successful personal computer, the Altair 8800, appeared in 1974. But too high a price carried obvious risks. In 1967, the cheapest teaching machine in the UK, the Tutorpack (from Packham Research Ltd), cost £7 12s (equivalent to about £126 today), but machines like these were disparagingly referred to as ‘page-turners’ (Higgins, 1983: 4). A higher-end linear programming machine cost twice this amount. Branching programme machines cost a lot more. The Mark II AutoTutor (from USI Great Britain Limited), for example, cost £31 per month (equivalent to £558), with eight reels of programmes thrown in (Goodman, 1967: 26). A lower-end branching machine, the Grundytutor, could be bought for £ 230 (worth about £4140 today).

This was serious money, and any institution splashing out on teaching machines needed to be confident that they would be well used for a long period of time (Nordberg, 1965). The programmes (the software) were specific to individual machines and the content could not be updated easily. At the same time, other technological developments (cine projectors, tape recorders, record players) were arriving in classrooms, and schools found themselves having to pay for technical assistance and maintenance. The average teacher was ‘unable to avail himself fully of existing aids because, to put it bluntly, he is expected to teach for too many hours a day and simply has not the time, with all the administrative chores he is expected to perform, either to maintain equipment, to experiment with it, let alone keeping up with developments in his own and wider fields. The advent of teaching machines which can free the teacher to fulfil his role as an educator will intensify and not diminish the problem’ (Goodman, 1967: 44). Teaching machines, in short, were ‘oversold and underused’ (Cuban, 2001).

3 Research and theory

Looking back twenty years later, B. F. Skinner conceded that ‘the machines were crude, [and] the programs were untested’ (Skinner, 1986: 105). The documentary record suggests that the second part of this statement is not entirely true. Herrick (1966: 695) reported that ‘an overwhelming amount of research time has been invested in attempts to determine the relative merits of programmed instruction when compared to ‘traditional’ or ‘conventional’ methods of instruction. The results have been almost equally overwhelming in showing no significant differences’. In 1968, Kay et al (1968: 96) noted that ‘there has been a definite effort to examine programmed instruction’. A later meta-analysis of research in secondary education (Kulik et al.: 1982) confirmed that ‘Programmed Instruction did not typically raise student achievement […] nor did it make students feel more positively about the subjects they were studying’.

It was not, therefore, the case that research was not being done. It was that many people were preferring not to look at it. The same holds true for theoretical critiques. In relation to language learning, Spolsky (1966) referred to Chomsky’s (1959) rebuttal of Skinner’s arguments, adding that ‘there should be no need to rehearse these inadequacies, but as some psychologists and even applied linguists appear to ignore their existence it might be as well to remind readers of a few’. Programmed Instruction might have had a limited role to play in language learning, but vendors’ claims went further than that and some people believed them: ‘Rather than addressing themselves to limited and carefully specified FL tasks – for example the teaching of spelling, the teaching of grammatical concepts, training in pronunciation, the acquisition of limited proficiency within a restricted number of vocabulary items and grammatical features – most programmers aimed at self-sufficient courses designed to lead to near-native speaking proficiency’ (Valdman, 1968: 2).

4 Content

When learning is conceptualised as purely the acquisition of knowledge, technological optimists tend to believe that machines can convey it more effectively and more efficiently than teachers (Hof, 2018). The corollary of this is the belief that, if you get the materials right (plus the order in which they are presented and appropriate feedback), you can ‘to a great extent control and engineer the quality and quantity of learning’ (Post, 1972: 14). Learning, in other words, becomes an engineering problem, and technology is its solution.

One of the problems was that technology vendors were, first and foremost, technology specialists. Content was almost an afterthought. Materials writers needed to be familiar with the technology and, if not, they were unlikely to be employed. Writers needed to believe in the potential of the technology, so those familiar with current theory and research would clearly not fit in. The result was unsurprising. Kennedy (1967: 872) reported that ‘there are hundreds of programs now available. Many more will be published in the next few years. Watch for them. Examine them critically. They are not all of high quality’. He was being polite.

5 Motivation

As is usually the case with new technologies, there was a positive novelty effect with Programmed Instruction. And, as is always the case, the novelty effect wears off: ‘students quickly tired of, and eventually came to dislike, programmed instruction’ (McDonald et al.: 89). It could not really have been otherwise: ‘human learning and intrinsic motivation are optimized when persons experience a sense of autonomy, competence, and relatedness in their activity. Self-determination theorists have also studied factors that tend to occlude healthy functioning and motivation, including, among others, controlling environments, rewards contingent on task performance, the lack of secure connection and care by teachers, and situations that do not promote curiosity and challenge’ (McDonald et al.: 93). The demotivating experience of using these machines was particularly acute with younger and ‘less able’ students, as was noted at the time (Valdman, 1968: 9).

The unlearned lessons

I hope that you’ll now understand why I think the history of Programmed Instruction is so relevant to us today. In the words of my favourite Yogi-ism, it’s like deja vu all over again. I have quoted repeatedly from the article by McDonald et al (2005) and I would highly recommend it – available here. Hopefully, too, Audrey Watters’ forthcoming book, ‘Teaching Machines’, will appear before too long, and she will, no doubt, have much more of interest to say on this topic.

References

Chomsky N. 1959. ‘Review of Skinner’s Verbal Behavior’. Language, 35:26–58.

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

Goodman, R. 1967. Programmed Learning and Teaching Machines 3rd edition. (London: English Universities Press)

Herrick, M. 1966. ‘Programmed Instruction: A critical appraisal’ The American Biology Teacher, 28 (9), 695 -698

Higgins, J. 1983. ‘Can computers teach?’ CALICO Journal, 1 (2)

Hill, L. A. 1966. Programmed English Course Student’s Book 1. (Oxford: Oxford University Press)

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

Howatt, A. P. R. 1969. Programmed Learning and the Language Teacher. (London: Longmans)

Kay, H., Dodd, B. & Sime, M. 1968. Teaching Machines and Programmed Instruction. (Harmondsworth: Penguin)

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

Kulik, C.-L., Schwalb, B. & Kulik, J. 1982. ‘Programmed Instruction in Secondary Education: A Meta-analysis of Evaluation Findings’ Journal of Educational Research, 75: 133 – 138

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

Nordberg, R. B. 1965. Teaching machines-six dangers and one advantage. In J. S. Roucek (Ed.), Programmed teaching: A symposium on automation in education (pp. 1–8). (New York: Philosophical Library)

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

Post, D. 1972. ‘Up the programmer: How to stop PI from boring learners and strangling results’. Educational Technology, 12(8), 14–1

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

Skinner, B. F. 1986. ‘Programmed Instruction Revisited’ The Phi Delta Kappan, 68 (2), 103 – 110

Spolsky, B. 1966. ‘A psycholinguistic critique of programmed foreign language instruction’ International Review of Applied Linguistics in Language Teaching, Volume 4, Issue 1-4: 119–130

Thornbury, S. 2017. Scott Thornbury’s 30 Language Teaching Methods. (Cambridge: Cambridge University Press)

Tucker, C. 1972. ‘Programmed Dictation: An Example of the P.I. Process in the Classroom’. TESOL Quarterly, 6(1), 61-70

Valdman, A. 1968. ‘Programmed Instruction versus Guided Learning in Foreign Language Acquisition’ Die Unterrichtspraxis / Teaching German, 1 (2), 1 – 14

 

 

 

[1] Spolsky’ doctoral thesis for the University of Montreal was entitled ‘The psycholinguistic basis of programmed foreign language instruction’.

 

 

 

 

 

Edtech and climate change denial

Over the last week, the Guardian has been running a series of articles on the global corporations that contribute most to climate change and the way that these vested interests lobby against changes to the law which might protect the planet. Beginning in the 1990s, an alliance of fossil fuel and automobile corporations, along with conservative think tanks and politicians, developed a ‘denial machine’ which sought to undermine the scientific consensus on climate change. Between 2003 and 2010, it has been estimated that over $550 million was received from a variety of sources to support this campaign. The Guardian’s current series is an update and reminder of the research into climate change denial that has been carried out in recent years.

In the past, it was easier to trace where the money came from (e.g. ExxonMobil or Koch Industries), but it appears that the cash is now being channelled through foundations like Donors Trust and Donors Capital, who, in turn, pass it on to other foundations and think tanks (see below) that promote the denial of climate change.

The connection between climate change denial and edtech becomes clear when you look at the organisations behind the ‘denial machine’. I have written about some of these organisations before (see this post ) so when I read the reports in the Guardian, there were some familiar names.

Besides their scepticism about climate change, all of the organisations believe that education should be market-driven, free from governmental interference, and characterised by consumer choice. These aims are facilitated by the deployment of educational technology. Here are some examples.

State Policy Network

The State Policy Network (SPN) is an American umbrella organization for a large group of conservative and libertarian think tanks that seek to influence national and global policies. Among other libertarian causes, it opposes climate change regulations and supports the privatisation of education, in particular the expansion of ‘digital education’.

The Cato Institute

The mission of the Cato Institute, a member of the SPN, ‘is to originate, disseminate, and increase understanding of public policies based on the principles of individual liberty, limited government, free markets, and peace. Our vision is to create free, open, and civil societies founded on libertarian principles’. The Institute has said that it had never been in the business of “promoting climate science denial”; it did not dispute human activity’s impact on the climate, but believed it was minimal. Turning to education, it believes that ‘states should institute school choice on a broad scale, moving toward a competitive education market. The only way to transform the system is to break up the long-standing government monopoly and use the dynamics of the market to create innovations, better methods, and new schools’. Innovations and better methods will, of course, be driven by technology.

FreedomWorks

FreedomWorks, another member of the SPN and another conservative and libertarian advocacy group, is widely associated with the Tea Party Movement . Recent posts on its blog have been entitled ‘The Climate Crisis that Wasn’t: Scientists Agree there is “No Cause for Alarm”’, ‘Climate Protesters: If You Want to Save the Planet, You Should Support Capitalism Not Socialism’ and ‘Electric Vehicle Tax Credit: Nothing But Regressive Cronyism’. Its approach to education is equally uncompromising. It seeks to abolish the US Department of Education, describes American schools as ‘failing’, wants market-driven educational provision and absolute parental choice . Technology will play a fundamental role in bringing about the desired changes: ‘just as computers and the Internet have fundamentally reshaped the way we do business, they will also soon reshape education’ .

The Heritage Foundation

The Heritage Foundation, the last of the SPN members that I’ll mention here, is yet another conservative American think tank which rejects the scientific consensus on climate change . Its line on education is neatly summed up in this extract from a blog post by a Heritage senior policy analyst: ‘Virtual or online learning is revolutionizing American education. It has the potential to dramatically expand the educational opportunities of American students, largely overcoming the geographic and demographic restrictions. Virtual learning also has the potential to improve the quality of instruction, while increasing productivity and lowering costs, ultimately reducing the burden on taxpayers‘.

The Institute of Economic Affairs

Just to show that the ‘denial machine’ isn’t an exclusively American phenomenon, I include ‘the UK’s most influential conservative think tank [which] has published at least four books, as well as multiple articles and papers, over two decades suggesting manmade climate change may be uncertain or exaggerated. In recent years the group has focused more on free-market solutions to reducing carbon emissions’ . It is an ‘associate member of the SPN’ . No surprise to discover that a member of the advisory council of the IEA is James Tooley, a close associate of Michael Barber, formerly Chief Education Advisor at Pearson. Tooley’s articles for the IEA include ‘Education without the State’  and ‘Transforming incentives will unleash the power of entrepreneurship in the education sector’ .

The IEA does not disclose its funding, but anyone interested in finding out more should look here ‘Revealed: how the UK’s powerful right-wing think tanks and Conservative MPs work together’ .

Microsoft, Facebook and Google

Let me be clear to start: Microsoft, Facebook and Google are not climate change deniers. However, Facebook and Microsoft are financial backers of the SPN. In a statement, a spokesperson for Microsoft said: “As a large company, Microsoft has great interest in the many policy issues discussed across the country. We have a longstanding record of engaging with a broad assortment of groups on a bipartisan basis, both at the national and local level. In regard to State Policy Network, Microsoft has focused our participation on their technology policy work group because it is valuable forum to hear various perspectives about technology challenges and to share potential solutions” . Google has made substantial contributions to the Competitive Enterprise Institute (a conservative US policy group ‘that was instrumental in convincing the Trump administration to abandon the Paris agreement and has criticised the White House for not dismantling more environmental rules’). In the Guardian report, Google ‘defended its contributions, saying that its “collaboration” with organisations such as CEI “does not mean we endorse the organisations’ entire agenda”. “When it comes to regulation of technology, Google has to find friends wherever they can and I think it is wise that the company does not apply litmus tests to who they support,” the source said’ .

You have to wonder what these companies (all of whom support environmental causes in various ways) might consider more important than the future of the planet. Could it be that the libertarian think tanks are important allies in resisting any form of internet governance, in objecting to any constraints on the capture of data?

The neutrality of educational technology

At a recent ELT conference, a plenary presentation entitled ‘Getting it right with edtech’ (sponsored by a vendor of – increasingly digital – ELT products) began with the speaker suggesting that technology was basically neutral, that what you do with educational technology matters far more than the nature of the technology itself. The idea that technology is a ‘neutral tool’ has a long pedigree and often accompanies exhortations to embrace edtech in one form or another (see for example Fox, 2001). It is an idea that is supported by no less a luminary than Chomsky, who, in a 2012 video entitled ‘The Purpose of Education’ (Chomsky, 2012), said that:

As far as […] technology […] and education is concerned, technology is basically neutral. It’s kind of like a hammer. I mean, […] the hammer doesn’t care whether you use it to build a house or whether a torturer uses it to crush somebody’s skull; a hammer can do either. The same with the modern technology; say, the Internet, and so on.

Although hammers are not usually classic examples of educational technology, they are worthy of a short discussion. Hammers come in all shapes and sizes and when you choose one, you need to consider its head weight (usually between 16 and 20 ounces), the length of the handle, the shape of the grip, etc. Appropriate specifications for particular hammering tasks have been calculated in great detail. The data on which these specifications is based on an analysis of the hand size and upper body strength of the typical user. The typical user is a man, and the typical hammer has been designed for a man. The average male hand length is 177.9 mm, that of the average woman is 10 mm shorter (Wang & Cai, 2017). Women typically have about half the upper body strength of men (Miller et al., 1993). It’s possible, but not easy to find hammers designed for women (they are referred to as ‘Ladies hammers’ on Amazon). They have a much lighter head weight, a shorter handle length, and many come in pink or floral designs. Hammers, in other words, are far from neutral: they are highly gendered.

Moving closer to educational purposes and ways in which we might ‘get it right with edtech’, it is useful to look at the smart phone. The average size of these devices has risen in recent years, and is now 5.5 inches, with the market for 6 inch screens growing fast. Why is this an issue? Well, as Caroline Criado Perez (2019: 159) notes, ‘while we’re all admittedly impressed by the size of your screen, it’s a slightly different matter when it comes to fitting into half the population’s hands. The average man can fairly comfortably use his device one-handed – but the average woman’s hand is not much bigger than the handset itself’. This is despite the fact the fact that women are more likely to own an iPhone than men  .

It is not, of course, just technological artefacts that are gendered. Voice-recognition software is also very biased. One researcher (Tatman, 2017) has found that Google’s speech recognition tool is 13% more accurate for men than it is for women. There are also significant biases for race and social class. The reason lies in the dataset that the tool is trained on: the algorithms may be gender- and socio-culturally-neutral, but the dataset is not. It would not be difficult to redress this bias by training the tool on a different dataset.

The same bias can be found in automatic translation software. Because corpora such as the BNC or COCA have twice as many male pronouns as female ones (as a result of the kinds of text that are selected for the corpora), translation software reflects the bias. With Google Translate, a sentence in a language with a gender-neutral pronoun, such as ‘S/he is a doctor’ is rendered into English as ‘He is a doctor’. Meanwhile, ‘S/he is a nurse’ is translated as ‘She is a nurse’ (Criado Perez, 2019: 166).

Datasets, then, are often very far from neutral. Algorithms are not necessarily any more neutral than the datasets, and Cathy O’Neil’s best-seller ‘Weapons of Math Destruction’ catalogues the many, many ways in which algorithms, posing as neutral mathematical tools, can increase racial, social and gender inequalities.

It would not be hard to provide many more examples, but the selection above is probably enough. Technology, as Langdon Winner (Winner, 1980) observed almost forty years ago, is ‘deeply interwoven in the conditions of modern politics’. Technology cannot be neutral: it has politics.

So far, I have focused primarily on the non-neutrality of technology in terms of gender (and, in passing, race and class). Before returning to broader societal issues, I would like to make a relatively brief mention of another kind of non-neutrality: the pedagogic. Language learning materials necessarily contain content of some kind: texts, topics, the choice of values or role models, language examples, and so on. These cannot be value-free. In the early days of educational computer software, one researcher (Biraimah, 1993) found that it was ‘at least, if not more, biased than the printed page it may one day replace’. My own impression is that this remains true today.

Equally interesting to my mind is the fact that all educational technologies, ranging from the writing slate to the blackboard (see Buzbee, 2014), from the overhead projector to the interactive whiteboard, always privilege a particular kind of teaching (and learning). ‘Technologies are inherently biased because they are built to accomplish certain very specific goals which means that some technologies are good for some tasks while not so good for other tasks’ (Zhao et al., 2004: 25). Digital flashcards, for example, inevitably encourage a focus on rote learning. Contemporary LMSs have impressive multi-functionality (i.e. they often could be used in a very wide variety of ways), but, in practice, most teachers use them in very conservative ways (Laanpere et al., 2004). This may be a result of teacher and institutional preferences, but it is almost certainly due, at least in part, to the way that LMSs are designed. They are usually ‘based on traditional approaches to instruction dating from the nineteenth century: presentation and assessment [and] this can be seen in the selection of features which are most accessible in the interface, and easiest to use’ (Lane, 2009).

The argument that educational technology is neutral because it could be put to many different uses, good or bad, is problematic because the likelihood of one particular use is usually much greater than another. There is, however, another way of looking at technological neutrality, and that is to look at its origins. Elsewhere on this blog, in post after post, I have given examples of the ways in which educational technology has been developed, marketed and sold primarily for commercial purposes. Educational values, if indeed there are any, are often an afterthought. The research literature in this area is rich and growing: Stephen Ball, Larry Cuban, Neil Selwyn, Joel Spring, Audrey Watters, etc.

Rather than revisit old ground here, this is an opportunity to look at a slightly different origin of educational technology: the US military. The close connection of the early history of the internet and the Advanced Research Projects Agency (now DARPA) of the United States Department of Defense is fairly well-known. Much less well-known are the very close connections between the US military and educational technologies, which are catalogued in the recently reissued ‘The Classroom Arsenal’ by Douglas D. Noble.

Following the twin shocks of the Soviet Sputnik 1 (in 1957) and Yuri Gagarin (in 1961), the United States launched a massive programme of investment in the development of high-tech weaponry. This included ‘computer systems design, time-sharing, graphics displays, conversational programming languages, heuristic problem-solving, artificial intelligence, and cognitive science’ (Noble, 1991: 55), all of which are now crucial components in educational technology. But it also quickly became clear that more sophisticated weapons required much better trained operators, hence the US military’s huge (and continuing) interest in training. Early interest focused on teaching machines and programmed instruction (branches of the US military were by far the biggest purchasers of programmed instruction products). It was essential that training was effective and efficient, and this led to a wide interest in the mathematical modelling of learning and instruction.

What was then called computer-based education (CBE) was developed as a response to military needs. The first experiments in computer-based training took place at the Systems Research Laboratory of the Air Force’s RAND Corporation think tank (Noble, 1991: 73). Research and development in this area accelerated in the 1960s and 1970s and CBE (which has morphed into the platforms of today) ‘assumed particular forms because of the historical, contingent, military contexts for which and within which it was developed’ (Noble, 1991: 83). It is possible to imagine computer-based education having developed in very different directions. Between the 1960s and 1980s, for example, the PLATO (Programmed Logic for Automatic Teaching Operations) project at the University of Illinois focused heavily on computer-mediated social interaction (forums, message boards, email, chat rooms and multi-player games). PLATO was also significantly funded by a variety of US military agencies, but proved to be of much less interest to the generals than the work taking place in other laboratories. As Noble observes, ‘some technologies get developed while others do not, and those that do are shaped by particular interests and by the historical and political circumstances surrounding their development (Noble, 1991: 4).

According to Noble, however, the influence of the military reached far beyond the development of particular technologies. Alongside the investment in technologies, the military were the prime movers in a campaign to promote computer literacy in schools.

Computer literacy was an ideological campaign rather than an educational initiative – a campaign designed, at bottom, to render people ‘comfortable’ with the ‘inevitable’ new technologies. Its basic intent was to win the reluctant acquiescence of an entire population in a brave new world sculpted in silicon.

The computer campaign also succeeded in getting people in front of that screen and used to having computers around; it made people ‘computer-friendly’, just as computers were being rendered ‘used-friendly’. It also managed to distract the population, suddenly propelled by the urgency of learning about computers, from learning about other things, such as how computers were being used to erode the quality of their working lives, or why they, supposedly the citizens of a democracy, had no say in technological decisions that were determining the shape of their own futures.

Third, it made possible the successful introduction of millions of computers into schools, factories and offices, even homes, with minimal resistance. The nation’s public schools have by now spent over two billion dollars on over a million and a half computers, and this trend still shows no signs of abating. At this time, schools continue to spend one-fifth as much on computers, software, training and staffing as they do on all books and other instructional materials combined. Yet the impact of this enormous expenditure is a stockpile of often idle machines, typically used for quite unimaginative educational applications. Furthermore, the accumulated results of three decades of research on the effectiveness of computer-based instruction remain ‘inconclusive and often contradictory’. (Noble, 1991: x – xi)

Rather than being neutral in any way, it seems more reasonable to argue, along with (I think) most contemporary researchers, that edtech is profoundly value-laden because it has the potential to (i) influence certain values in students; (ii) change educational values in [various] ways; and (iii) change national values (Omotoyinbo & Omotoyinbo, 2016: 173). Most importantly, the growth in the use of educational technology has been accompanied by a change in the way that education itself is viewed: ‘as a tool, a sophisticated supply system of human cognitive resources, in the service of a computerized, technology-driven economy’ (Noble, 1991: 1). These two trends are inextricably linked.

References

Biraimah, K. 1993. The non-neutrality of educational computer software. Computers and Education 20 / 4: 283 – 290

Buzbee, L. 2014. Blackboard: A Personal History of the Classroom. Minneapolis: Graywolf Press

Chomsky, N. 2012. The Purpose of Education (video). Learning Without Frontiers Conference. https://www.youtube.com/watch?v=DdNAUJWJN08

Criado Perez, C. 2019. Invisible Women. London: Chatto & Windus

Fox, R. 2001. Technological neutrality and practice in higher education. In A. Herrmann and M. M. Kulski (Eds), Expanding Horizons in Teaching and Learning. Proceedings of the 10th Annual Teaching Learning Forum, 7-9 February 2001. Perth: Curtin University of Technology. http://clt.curtin.edu.au/events/conferences/tlf/tlf2001/fox.html

Laanpere, M., Poldoja, H. & Kikkas, K. 2004. The second thoughts about pedagogical neutrality of LMS. Proceedings of IEEE International Conference on Advanced Learning Technologies, 2004. https://ieeexplore.ieee.org/abstract/document/1357664

Lane, L. 2009. Insidious pedagogy: How course management systems impact teaching. First Monday, 14(10). https://firstmonday.org/ojs/index.php/fm/article/view/2530/2303Lane

Miller, A.E., MacDougall, J.D., Tarnopolsky, M. A. & Sale, D.G. 1993. ‘Gender differences in strength and muscle fiber characteristics’ European Journal of Applied Physiology and Occupational Physiology. 66(3): 254-62 https://www.ncbi.nlm.nih.gov/pubmed/8477683

Noble, D. D. 1991. The Classroom Arsenal. Abingdon, Oxon.: Routledge

Omotoyinbo, D. W. & Omotoyinbo, F. R. 2016. Educational Technology and Value Neutrality. Societal Studies, 8 / 2: 163 – 179 https://www3.mruni.eu/ojs/societal-studies/article/view/4652/4276

O’Neil, C. 2016. Weapons of Math Destruction. London: Penguin

Sundström, P. Interpreting the Notion that Technology is Value Neutral. Medicine, Health Care and Philosophy 1, 1998: 42-44

Tatman, R. 2017. ‘Gender and Dialect Bias in YouTube’s Automatic Captions’ Proceedings of the First Workshop on Ethics in Natural Language Processing, pp. 53–59 http://www.ethicsinnlp.org/workshop/pdf/EthNLP06.pdf

Wang, C. & Cai, D. 2017. ‘Hand tool handle design based on hand measurements’ MATEC Web of Conferences 119, 01044 (2017) https://www.matec-conferences.org/articles/matecconf/pdf/2017/33/matecconf_imeti2017_01044.pdf

Winner, L. 1980. Do Artifacts have Politics? Daedalus 109 / 1: 121 – 136

Zhao, Y, Alvarez-Torres, M. J., Smith, B. & Tan, H. S. 2004. The Non-neutrality of Technology: a Theoretical Analysis and Empirical Study of Computer Mediated Communication Technologies. Journal of Educational Computing Research 30 (1 &2): 23 – 55

EdTech: a cautionary tale

When the startup, AltSchool, was founded in 2013 by Max Ventilla, the former head of personalization at Google, it quickly drew the attention of venture capitalists and within a few years had raised $174 million from the likes of the Zuckerberg Foundation, Peter Thiel, Laurene Powell Jobs and Pierre Omidyar. It garnered gushing articles in a fawning edtech press which enthused about ‘how successful students can be when they learn in small, personalized communities that champion project-based learning, guided by educators who get a say in the technology they use’. It promised ‘a personalized learning approach that would far surpass the standardized education most kids receive’.

Ventilla was an impressive money-raiser who used, and appeared to believe, every cliché in the edTech sales manual. Dressed in regulation jeans, polo shirt and fleece, he claimed that schools in America were ‘stuck in an industrial-age model, [which] has been in steady decline for the last century’ . What he offered, instead, was a learner-centred, project-based curriculum providing real-world lessons. There was a focus on social-emotional learning activities and critical thinking was vital.

The key to the approach was technology. From the start, software developers, engineers and researchers worked alongside teachers everyday, ‘constantly tweaking the Personalized Learning Plan, which shows students their assignments for each day and helps teachers keep track of and assess student’s learning’. There were tablets for pre-schoolers, laptops for older kids and wall-mounted cameras to record the lessons. There were, of course, Khan Academy videos. Ventilla explained that “we start with a representation of each child”, and even though “the vast majority of the learning should happen non-digitally”, the child’s habits and preferences gets converted into data, “a digital representation of the important things that relate to that child’s learning, not just their academic learning but also their non-academic learning. Everything logistic that goes into setting up the experience for them, whether it’s who has permission to pick them up or their allergy information. You name it.” And just like Netflix matches us to TV shows, “If you have that accurate and actionable representation for each child, now you can start to personalize the whole experience for that child. You can create that kind of loop you described where because we can represent a child well, we can match them to the right experiences.”

AltSchool seemed to offer the possibility of doing something noble, of transforming education, ‘bringing it into the digital age’, and, at the same time, a healthy return on investors’ money. Expanding rapidly, nine AltSchool microschools were opened in New York and the Bay Area, and plans were afoot for further expansion in Chicago. But, by then, it was already clear that something was going wrong. Five of the schools were closed before they had really got started and the attrition rate in some classrooms had reached about 30%. Revenue in 2018 was only $7 million and there were few buyers for the AltSchool platform. Quoting once more from the edTech bible, Ventilla explained the situation: ‘Our whole strategy is to spend more than we make,’ he says. Since software is expensive to develop and cheap to distribute, the losses, he believes, will turn into steep profits once AltSchool refines its product and lands enough customers.

The problems were many and apparent. Some of the buildings were simply not appropriate for schools, with no playgrounds or gyms, malfunctioning toilets, among other issues. Parents were becoming unhappy and accused AltSchool of putting ‘its ambitions as a tech company above its responsibility to teach their children. […] We kind of came to the conclusion that, really, AltSchool as a school was kind of a front for what Max really wants to do, which is develop software that he’s selling,’ a parent of a former AltSchool student told Business Insider. ‘We had really mediocre educators using technology as a crutch,’ said one father who transferred his child to a different private school after two years at AltSchool. […] We learned that it’s almost impossible to really customize the learning experience for each kid.’ Some parents began to wonder whether AltSchool had enticed families into its program merely to extract data from their children, then toss them aside?

With the benefit of hindsight, it would seem that the accusations were hardly unfair. In June of this year, AltSchool announced that its four remaining schools would be operated by a new partner, Higher Ground Education (a well-funded startup founded in 2016 which promotes and ‘modernises’ Montessori education). Meanwhile, AltSchool has been rebranded as Altitude Learning, focusing its ‘resources on the development and expansion of its personalized learning platform’ for licensing to other schools across the country.

Quoting once more from the edTech sales manual, Ventilla has said that education should drive the tech, not the other way round. Not so many years earlier, before starting AltSchool, Ventilla also said that he had read two dozen books on education and emerged a fan of Sir Ken Robinson. He had no experience as a teacher or as an educational administrator. Instead, he had ‘extensive knowledge of networks, and he understood the kinds of insights that can be gleaned from big data’.

Personalized learning at IATEFL

It’s international ELT conference season again, with TESOL Chicago having just come to a close and IATEFL Brighton soon to start. I decided to take a look at how the subject of personalized learning will be covered at the second of these. Taking the conference programme , I trawled through looking for references to my topic.

My first question was: how do conference presenters feel about personalised learning? One way of finding out is by looking at the adjectives that are found in close proximity. This is what you get.

The overall enthusiasm is even clearer when the contexts are looked at more closely. Here are a few examples:

• inspiring assessment, personalising learning
• personalised training can contribute to professionalism and […] spark ideas for teacher trainers
• a personalised educational experience that ultimately improves learner outcomes
• personalised teacher development: is it achievable?

Particularly striking is the complete absence of anything that suggests that personalized learning might not be a ‘good thing’. The assumption throughout is that personalized learning is desirable and the only question that is asked is how it can be achieved. Unfortunately (and however much we might like to believe that it is a ‘good thing’), there is a serious lack of research evidence which demonstrates that this is the case. I have written about this here and here and here . For a useful summary of the current situation, see Benjamin Riley’s article where he writes that ‘it seems wise to ask what evidence we presently have that personalized learning works. Answer: Virtually none. One remarkable aspect of the personalized-learning craze is how quickly the concept has spread despite the almost total absence of rigorous research in support of it, at least thus far.’

Given that personalized learning can mean so many things and given the fact that people do not have space to define their terms in their conference abstracts, it is interesting to see what other aspects of language learning / teaching it is associated with. The four main areas are as follows (in alphabetical order):

• assessment (especially formative assessment) / learning outcomes
• continuous professional development
• learner autonomy
• technology / blended learning

The IATEFL TD SIG would appear to be one of the main promoters of personalized learning (or personalized teacher development) with a one-day pre-conference event entitled ‘Personalised teacher development – is it achievable?’ and a ‘showcase’ forum entitled ‘Forum on Effective & personalised: the holy grail of CPD’. Amusingly (but coincidentally, I suppose), the forum takes place in the ‘Cambridge room’ (see below).

I can understand why the SIG organisers may have chosen this focus. It’s something of a hot topic, and getting hotter. For example:

• Cambridge University Press has identified personalization as one of the ‘six key principles of effective teacher development programmes’ and is offering tailor-made teacher development programmes for institutions.
• NILE and Macmillan recently launched a partnership whose brief is to ‘curate personalised professional development with an appropriate mix of ‘formal’ and ‘informal’ learning delivered online, blended and face to face’.
• Pearson has developed the Pearson’s Teacher Development Interactive (TDI) – ‘an interactive online course to train and certify teachers to deliver effective instruction in English as a foreign language […] You can complete each module on your own time, at your own pace from anywhere you have access to the internet.’

These examples do not, of course, provide any explanation for why personalized learning is a hot topic, but the answer to that is simple. Money. Billions and billions, and if you want a breakdown, have a look at the appendix of Monica Bulger’s report, ‘Personalized Learning: The Conversations We’re Not Having’ . Starting with Microsoft and the Gates Foundation plus Facebook and the Chan / Zuckerberg Foundation, dozens of venture philanthropists have thrown unimaginable sums of money at the idea of personalized learning. They have backed up their cash with powerful lobbying and their message has got through. Consent has been successfully manufactured.

One of the most significant players in this field is Pearson, who have long been one of the most visible promoters of personalized learning (see the screen capture). At IATEFL, two of the ten conference abstracts which include the word ‘personalized’ are directly sponsored by Pearson. Pearson actually have ten presentations they have directly sponsored or are very closely associated with. Many of these do not refer to personalized learning in the abstract, but would presumably do so in the presentations themselves. There is, for example, a report on a professional development programme in Brazil using TDI (see above). There are two talks about the GSE, described as a tool ‘used to provide a personalised view of students’ language’. The marketing intent is clear: Pearson is to be associated with personalized learning (which is, in turn, associated with a variety of tech tools) – they even have a VP of data analytics, data science and personalized learning.

But the direct funding of the message is probably less important these days than the reinforcement, by those with no vested interests, of the set of beliefs, the ideology, which underpin the selling of personalized learning products. According to this script, personalized learning can promote creativity, empowerment, inclusiveness and preparedness for the real world of work. It sets itself up in opposition to lockstep and factory models of education, and sets learners free as consumers in a world of educational choice. It is a message with which it is hard for many of us to disagree.

It is also a marvellous example of propaganda, of the way that consent is manufactured. (If you haven’t read it yet, it’s probably time to read Herman and Chomsky’s ‘Manufacturing Consent: The Political Economy of the Mass Media’.) An excellent account of the way that consent for personalized learning has been manufactured can be found at Benjamin Doxtdator’s blog .

So, a hot topic it is, and its multiple inclusion in the conference programme will no doubt be welcomed by those who are selling ‘personalized’ products. It must be very satisfying to see how normalised the term has become, how it’s no longer necessary to spend too much on promoting the idea, how it’s so associated with technology, (formative) assessment, autonomy and teacher development … since others are doing it for you.

Chatbots

 

Here’s a conversation I had recently with Cleverbot.

User (me): Hi Cleverbot. What are your views on the future of chatbots in language learning?

Cleverbot: Are you talking to yourself?

User: No, I’m asking you a question.

Cleverbot: Then what’s the question again? I forgot.

User: What are your views on the future of chatbots in language learning?

Cleverbot: Don’t you want me to finish my story?

User: No, I want you to answer my question.

Cleverbot: What is your question?

User: Do you think there is a future for chatbots in language education?

Cleverbot: Sure, if you are talking about the moon.

I also tried to have a conversation with Alice, the avatar from EFL Classroom Bot, listed by Larry Ferlazzo as one of ‘the best online chatbots for practicing English’. I didn’t get any more sense out of her than out of Cleverbot.

Chatbots, apparently, are the next big thing. Again. David Mattin, head of trends and insights at trendwatching.com, writes (in the September 2016 issue of ‘Business Life’) that ‘the chatbot revolution is coming’ and that chatbots are a step towards the dream of an interface between user and technology that is so intuitive that the interface ‘simply fades away’. Chatbots have been around for some time. Remember Clippy – the Microsoft Office bot in the late 1990s – which you had to disable in order to stop yourself punching your computer screen? Since then, bots have become ubiquitous. There have been problems, such as Microsoft’s Tay bot that had to be taken down after sixteen hours earlier this year, when, after interacting with other Twitter users, it developed into an abusive Nazi. But chatbots aren’t going away and you’ve probably interacted with one to book a taxi, order food or attempt to talk to your bank. In September this year, the Guardian described them as ‘the talk of the town’ and ‘hot property in Silicon Valley’.

The real interest in chatbots is not, however, in the ‘exciting interface’ possibilities (both user interface and user experience remain pretty crude), but in the way that they are leaner, sit comfortably with the things we actually do on a phone and the fact that they offer a way of cutting out the high fees that developers have to pay to app stores . After so many start-up failures, chatbots offer a glimmer of financial hope to developers.

It’s no surprise, of course, to find the world of English language teaching beginning to sit up and take notice of this technology. A 2012 article by Ben Lehtinen in PeerSpectives enthuses about the possibilities in English language learning and reports the positive feedback of the author’s own students. ELTJam, so often so quick off the mark, developed an ELT Bot over the course of a hackathon weekend in March this year. Disappointingly, it wasn’t really a bot – more a case of humans pretending to be a bot pretending to be humans – but it probably served its exploratory purpose. And a few months ago Duolingo began incorporating bots. These are currently only available for French, Spanish and German learners in the iPhone app, so I haven’t been able to try it out and evaluate it. According to an infomercial in TechCrunch, ‘to make talking to the bots a bit more compelling, the company tried to give its different bots a bit of personality. There’s Chef Robert, Renee the Driver and Officer Ada, for example. They will react differently to your answers (and correct you as necessary), but for the most part, the idea here is to mimic a real conversation. These bots also allow for a degree of flexibility in your answers that most language-learning software simply isn’t designed for. There are plenty of ways to greet somebody, for example, but most services will often only accept a single answer. When you’re totally stumped for words, though, Duolingo offers a ‘help my reply’ button with a few suggested answers.’ In the last twelve months or so, Duolingo has considerably improved its ability to recognize multiple correct ways of expressing a particular idea, and its ability to recognise alternative answers to its translation tasks. However, I’m highly sceptical about its ability to mimic a real conversation any better than Cleverbot or Alice the EFL Bot, or its ability to provide systematically useful corrections.

My reasons lie in the current limitations of AI and NLP (Natural Language Processing). In a nutshell, we simply don’t know how to build a machine that can truly understand human language. Limited exchanges in restricted domains can be done pretty well (such as the early chatbot that did a good job of simulating an encounter with an evasive therapist, or, more recently ordering a taco and having a meaningless, but flirty conversation with a bot), but despite recent advances in semantic computing, we’re a long way from anything that can mimic a real conversation. As Audrey Watters puts it, we’re not even close.

When it comes to identifying language errors made by language learners, we’re not really much better off. Apps like Grammarly are not bad at identifying grammatical errors (but not good enough to be reliable), but pretty hopeless at dealing with lexical appropriacy. Much more reliable feedback to learners can be offered when the software is trained on particular topics and text types. Write & Improve does this with a relatively small selection of Cambridge English examination tasks, but a free conversation ….? Forget it.

So, how might chatbots be incorporated into language teaching / learning? A blog post from December 2015 entitled AI-powered chatbots and the future of language learning suggests one plausible possibility. Using an existing messenger service, such as WhatsApp or Telegram, an adaptive chatbot would send tasks (such as participation in a conversation thread with a predetermined topic, register, etc., or pronunciation practice or translation exercises) to a learner, provide feedback and record the work for later recycling. At the same time, the bot could send out reminders of work that needs to be done or administrative tasks that must be completed.

Kat Robb has written a very practical article about using instant messaging in English language classrooms. Her ideas are interesting (although I find the idea of students in a F2F classroom messaging each other slightly bizarre) and it’s easy to imagine ways in which her activities might be augmented with chatbot interventions. The Write & Improve app, mentioned above, could deploy a chatbot interface to give feedback instead of the flat (and, in my opinion, perfectly adequate) pop-up boxes currently in use. Come to think of it, more or less any digital language learning tool could be pimped up with a bot. Countless revisions can be envisioned.

But the overwhelming question is: would it be worth it? Bots are not likely, any time soon, to revolutionise language learning. What they might just do, however, is help to further reduce language teaching to a series of ‘mechanical and scripted gestures’. More certain is that a lot of money will be thrown down the post-truth edtech drain. Then, in the not too distant future, this latest piece of edtech will fall into the trough of disillusionment, to be replaced by the latest latest thing.