The paragraph above was written by an AI-powered text generator called neuroflash https://app.neuro-flash.com/home which I told to produce a text on the topic ‘AI and education’. As texts on this topic go, it is both remarkable (in that it was not written by a human) and entirely unremarkable (in that it is practically indistinguishable from hundreds of human-written texts on the same subject). Neuroflash uses a neural network technology called GPT-3 – ‘a large language model’ – and ‘one of the most interesting and important AI systems ever produced’ (Chalmers, 2020). Basically, it generates text by predicting sequences of words based on huge databases. The nature of the paragraph above tells you all you need to know about the kinds of content that are usually found in texts about AI and education.

Not dissimilar from the neuroflash paragraph, educational commentary on uses of AI is characterised by (1) descriptions of AI tools already in use (e.g. speech recognition and machine translation) and (2) vague predictions which invariably refer to ‘the promise of personalised learning, adjusting what we give learners according to what they need to learn and keeping them motivated by giving them content that is of interest to them’ (Hughes, 2022). The question of what precisely will be personalised is unanswered: providing learners with optimal sets of resources (but which ones?), providing counselling services, recommendations or feedback for learners and teachers (but of what kind?) (Luckin, 2022). Nearly four years ago, I wrote https://adaptivelearninginelt.wordpress.com/2018/08/13/ai-and-language-teaching/ about the reasons why these questions remain unanswered. The short answer is that AI in language learning requires a ‘domain knowledge model’. This specifies what is to be learnt and includes an analysis of the steps that must be taken to reach that learning goal. This is lacking in SLA, or, at least, there is no general agreement on what it is. Worse, the models that are most commonly adopted in AI-driven programs (e.g. the deliberate learning of discrete items of grammar and vocabulary) are not supported by either current theory or research (see, for example, VanPatten & Smith, 2022).

In 2021, the IATEFL Learning Technologies SIG organised an event dedicated to AI in education. Unsurprisingly, there was a fair amount of input on AI in assessment, but my interest is in how AI might revolutionize how we learn and teach, not how we assess. What concrete examples did speakers provide?

Rose Luckin, the most well-known British expert on AI in education, kicked things off by mentioning three tools. One of these, Carnegie Learning, is a digital language course that looks very much like any of the ELT courses on offer from the big publishers – a fully blendable, multimedia (e.g. flashcards and videos) synthetic syllabus. This ‘blended learning solution’ is personalizable, since ‘no two students learn alike’, and, it claims, will develop a ‘lifelong love of language’. It appears to be premised on the idea of language learning as optimizing the delivery of ‘content’, of this content consisting primarily of discrete items, and of equating input with uptake. Been there, done that.

A second was Alelo Enskill https://www.alelo.com/about-us/ a chatbot / avatar roleplay program, first developed by the US military to teach Iraqi Arabic and aspects of Iraqi culture to Marines. I looked at the limitations of chatbot technology for language learning here https://adaptivelearninginelt.wordpress.com/2016/12/01/chatbots/ . The third tool mentioned by Luckin was Duolingo. Enough said.

Another speaker at this event was the founder and CEO of Edugo.AI https://www.edugo.ai/ , an AI-powered LMS which uses GPT-3. It allows schools to ‘create and upload on the platform any kind of language material (audio, video, text…). Our AI algorithms process and convert it in gamified exercises, which engage different parts of the brain, and gets students eager to practice’. Does this speaker know anything about gamification (for a quick read, I’d recommend Paul Driver (2012)) or neuroscience, I wonder. What, for that matter, does he know about language learning? Apparently, ‘language is not just about words, language is about sentences’ (Tomasello, 2022). Hmm, this doesn’t inspire confidence.

When you look at current uses of AI in language learning, there is very little (outside of testing, translation and speech ↔ text applications) that could justify enthusiastic claims that AI has any great educational potential. Skepticism seems to me a more reasonable and scientific response: de omnibus dubitandum.

Education is not the only field where AI has been talked up. When Covid hit us, AI was seen as the game-changing technology. It ‘could be deployed to make predictions, enhance efficiencies, and free up staff through automation; it could help rapidly process vast amounts of information and make lifesaving decisions’ (Chakravorti, 2022). The contribution of AI to the development of vaccines has been huge, but its role in diagnosing and triaging patients has been another matter altogether. Hundreds of predictive tools were developed: ‘none of them made a real difference, and some were potentially harmful’ (Heaven, 2021). Expectations were unrealistic and led to the deployment of tools before they were properly trialled. Thirty months down the line, a much more sober understanding of the potential of AI has emerged. Here, then, are the main lessons that have been learnt (I draw particularly on Engler, 2020, and Chakravorti, 2022) that are also relevant to education and language learning.

  • Anticipate what could go wrong before anticipating what might go right. Engler (2020) writes that ‘a poorly kept secret of AI practitioners is that 96% accuracy is suspiciously high for any machine learning problem’. In language learning, it is highly unlikely that personalized recommendations will ever reach anything even approaching this level of reliability. What are the implications for individual learners whose learning is inappropriately personalised?
  • We also know that a significant problem with AI systems is bias (O’Neil, 2016). There is a well-documented history of discriminatory outcomes because of people’s race, gender, social class or disability profile. Bias needs to be addressed proactively, not reactively.
  • Acknowledge from the outset that, for AI to work, huge amounts of data related to prior outcomes will be needed. In the cases of both Covid and language learning, much of this data will be personal. This raises immediate questions of privacy and consent, especially for learners who are children. Don’t minimise this issue.
  • Common by-products of AI use include insecure data storage, digital surveillance and consolidation of market power (Engler, 2020). Since such issues are so pervasive, assume they will be a problem, and need to be considered in evaluating the potential of any piece of AI edtech.
  • Find out what the subject matter experts have to say: ‘AI is only helpful when applied judiciously by subject-matter experts—people with long-standing experience with the problem that they are trying to solve […] Effectively predicting a badly defined problem is worse than doing nothing at all’ (Engler, 2020). It may be that the problem the AI is trying to help solve is the wrong problem and not worth solving at all (e.g. more efficient ‘delivery’ of explicit grammatical knowledge, gamifying gapfills).

To bring this post to an end, I returned to the AI / GTP-3 driven neuroflash program. This time, I asked it to write a longer piece entitled ‘The dangers of artificial intelligence in education: what could go wrong?’. Here’s what it came up with:

There are a few potential dangers of artificial intelligence in education. One is that AI could be used to replace human teachers. This could lead to a decline in the quality of education, as machines are not yet capable of replicating the full range of human emotions and social interactions that are necessary for teaching. Additionally, AI could be used to create biased or “racist” educational materials, as has already happened with some commercial software products. Finally, AI could be used to track and monitor students in ways that invade their privacy, or that could be used to manipulate their behavior.

All of these dangers are real and should be taken seriously. However, it’s important to remember that AI is still a new technology, and its impact on education is not yet fully understood. As such, we should tread cautiously when implementing AI into our educational systems.

When it comes to education, artificial intelligence could be a double-edged sword. While AI has the potential to revolutionize the field of education and help students learn in more efficient ways, there are also dangers that need to be considered.

One of the dangers of AI in education is that it could lead to a more standardized and homogenized form of learning. If all students are relying on AI-based learning tools, they may all end up learning the same things in the same way. This could lead to a loss of creativity and individuality in education.

Another danger is that AI-based learning tools could become too reliant on data and algorithms. This could lead to a situation where students are simply being taught what the machines think they should know, rather than being allowed to explore and discover new things for themselves.

Finally, there is the danger that AI could eventually replace human teachers altogether. While this may seem like a far-fetched scenario, it is not outside the realm of possibility. If AI-based learning tools become sophisticated enough, they may one day be able to do the job of teaching just as well as humans can.

These are just some of the dangers that need to be considered when it comes to artificial intelligence in education. While AI has the potential to revolutionize education, we need to be careful about how we implement it so that we don’t end up doing more harm than good.

References

Chakravorti, B. (2022) Why AI Failed to Live Up to Its Potential During the Pandemic. Harvard Business Review March 17,2022. https://hbr.org/2022/03/why-ai-failed-to-live-up-to-its-potential-during-the-pandemic

Chalmers, D. (2020) Weinberg, Justin (ed.). “GPT-3 and General Intelligence”. Daily Nous. Philosophers On GPT-3 (updated with replies by GPT-3) July 30, 2020. https://dailynous.com/2020/07/30/philosophers-gpt-3/#chalmers

Driver, P. (2012) The Irony of Gamification. In English Digital Magazine 3, British Council Portugal, pp. 21 – 24 http://digitaldebris.info/digital-debris/2011/12/31/the-irony-of-gamification-written-for-ied-magazine.html

Engler, A. (2020) A guide to healthy skepticism of artificial intelligence and coronavirus. Washington D.C.: Brookings Institution https://www.brookings.edu/research/a-guide-to-healthy-skepticism-of-artificial-intelligence-and-coronavirus/

Heaven, W. D. (2021) Hundreds of AI tools have been built to catch covid. None of them helped. MIT Technology Review, July 30, 2021. https://www.technologyreview.com/2021/07/30/1030329/machine-learning-ai-failed-covid-hospital-diagnosis-pandemic/

Hughes, G. (2022) What lies at the end of the AI rainbow? IATEFL LTSIG Newsletter Issue April 2022

Luckin, R. (2022) The implications of AI for language learning and teaching. IATEFL LTSIG Newsletter Issue April 2022

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

Tomasello, G. (2022) Next Generation of AI-Language Education Software:NLP & Language Modules (GPT3). IATEFL LTSIG Newsletter Issue April 2022

VanPatten, B. & Smith, M. (2022) Explicit and Implicit Learning in Second Language Acquisition. Cambridge: Cambridge University Press

There’s an aspect of language learning which everyone agrees is terribly important, but no one can quite agree on what to call it. I’m talking about combinations of words, including fixed expressions, collocations, phrasal verbs and idioms. These combinations are relatively fixed, cannot always be predicted from their elements or generated by grammar rules (Laufer, 2022). They are sometimes referred to as formulaic sequences, formulaic expressions, lexical bundles or lexical chunks, among other multiword items. They matter to English language learners because a large part of English consists of such combinations. Hill (2001) suggests this may be up to 70%. More conservative estimates report 58.6% of writing and 52.3% of speech (Erman & Warren, 2000). Some of these combinations (e.g. ‘of course’, ‘at least’) are so common that they fall into lists of the 1000 most frequent lexical items in the language.

By virtue of their ubiquity and frequency, they are important both for comprehension of reading and listening texts and for the speed at which texts can be processed. This is because knowledge of these combinations ‘makes discourse relatively predictable’ (Boers, 2020). Similarly, such knowledge can significantly contribute to spoken fluency because combinations ‘can be retrieved from memory as prefabricated units rather than being assembled at the time of speaking’ (Boer, 2020).

So far, so good, but from here on, the waters get a little muddier. Given their importance, what is the best way for a learner to acquire a decent stock of them? Are they best acquired through incidental learning (through meaning-focused reading and listening) or deliberate learning (e.g. with focused exercises of flashcards)? If the former, how on earth can we help learners to make sure that they get exposure to enough combinations enough times? If the latter, what kind of practice works best and, most importantly, which combinations should be selected? With, at the very least, many tens of thousands of such combinations, life is too short to learn them all in a deliberate fashion. Some sort of triage is necessary, but how should we go about this? Frequency of occurrence would be one obvious criterion, but this merely raises the question of what kind of database should be used to calculate frequency – the spoken discourse of children will reveal very different patterns from the written discourse of, say, applied linguists. On top of that, we cannot avoid consideration of the learners’ reasons for learning the language. If, as is statistically most probable, they are learning English to use as a lingua franca, how important or relevant is it to learn combinations that are frequent, idiomatic and comprehensible in native-speaker cultures, but may be rare and opaque in many English as a Lingua Franca contexts?

There are few, if any, answers to these big questions. Research (e.g. Pellicer-Sánchez, 2020) can give us pointers, but, the bottom line is that we are left with a series of semi-informed options (see O’Keeffe et al., 2007: 58 – 99). So, when an approach comes along that claims to use software to facilitate the learning of English formulaic expressions (Lin, 2022) I am intrigued, to say the least.

The program is, slightly misleadingly, called IdiomsTube (https://www.idiomstube.com). A more appropriate title would have been IdiomaticityTube (as it focuses on ‘speech formulae, proverbs, sayings, similes, binomials, collocations, and so on’), but I guess ‘idioms’ is a more idiomatic word than ‘idiomaticity’. IdiomsTube allows learners to choose any English-captioned video from YouTube, which is then automatically analysed to identify from two to six formulaic expressions that are presented to the learner as learning objects. Learners are shown these items; the items are hyperlinked to (good) dictionary entries; learners watch the video and are then presented with a small variety of practice tasks. The system recommends particular videos, based on an automated analysis of their difficulty (speech rate and a frequency count of the lexical items they include) and on recommendations from previous users. The system is gamified and, for class use, teachers can track learner progress.

When an article by the program’s developer, Phoebe Lin, (in my view, more of an advertising piece than an academic one) came out in the ReCALL journal, she tweeted that she’d love feedback. I reached out but didn’t hear back. My response here is partly an evaluation of Dr Lin’s program, partly a reflection on how far technology can go in solving some of the knotty problems of language learning.

Incidental and deliberate learning

Researchers have long been interested in looking for ways of making incidental learning of lexical items more likely to happen (Boers, 2021: 39 ff.), of making it more likely that learners will notice lexical items while focusing on the content of a text. Most obviously, texts can be selected, written or modified so they contain multiple instances of a particular item (‘input flooding’). Alternatively, texts can be typographically enhanced so that particular items are highlighted in some way. But these approaches are not possible when learners are given the freedom to select any video from YouTube and when the written presentations are in the form of YouTube captions. Instead, IdiomsTube presents the items before the learner watches the video. They are, in effect, told to watch out for these items in advance. They are also given practice tasks after viewing.

The distinction between incidental and deliberate vocabulary learning is not always crystal-clear. In this case, it seems fairly clear that the approach is more slanted to deliberate learning, even though the selection of video by the learner is determined by a focus on content. Whether this works or not will depend on (1) the level-appropriacy of the videos that the learner watches, (2) the effectiveness of the program in recommending / identifying appropriate videos, (3) the ability of the program to identify appropriate formulaic expressions as learning targets in each video, and (4) the ability of the program to generate appropriate practice of these items.

Evaluating the level of YouTube videos

What makes a video easy or hard to understand? IdiomsTube attempts this analytical task by calculating (1) the speed of the speech and (2) the difficulty of the lexis as determined by the corpus frequency of these items. This gives a score out of five for each category (speed and difficulty). I looked at fifteen videos, all of which were recommended by the program. Most of the ones I looked at were scored at Speed #3 and Difficulty #1. One that I looked at, ‘Bruno Mars Carpool Karaoke’, had a speed of #2 and a difficulty of #1 (i.e. one of the easiest). The video is 15 minutes long. Here’s an extract from the first 90 seconds:

Let’s set this party off right, put yo’ pinky rings up to the moon, twenty four karat magic in the air, head to toe soul player, second verse for the hustlas, gangstas, bad bitches and ya ugly ass friends, I gotta show how a pimp get it in, and they waking up the rocket why you mad

Whoa! Without going into details, it’s clear that something has gone seriously wrong. Evaluating the difficulty of language, especially spoken language, is extremely complex (not least because there’s no objective measure of such a thing). It’s not completely dissimilar to the challenge of evaluating the accuracy, appropriacy and level of sophistication of a learner’s spoken language, and we’re a long way from being able to do that with any acceptable level of reliability. At least, we’re a long, long way from being able to do it well when there are no constraints on the kind of text (which is the case when taking the whole of YouTube as a potential source). Especially if we significantly restrict topic and text type, we can train software to do a much better job. However, this will require human input: it cannot be automated without.

The length of these 15 videos ranged from 3.02 to 29.27 minutes, with the mean length being about 10 minutes, and the median 8.32 minutes. Too damn long.

Selecting appropriate learning items

The automatic identification of formulaic language in a text presents many challenges: it is, as O’Keeffe et al. (2007: 82) note, only partially possible. A starting point is usually a list, and IdiomsTube begins with a list of 53,635 items compiled by the developer (Lin, 2022) over a number of years. The software has to match word combinations in the text to items in the list, and has to recognise variant forms. Formulaic language cannot always be identified just by matching to lists of forms: a piece of cake may just be a piece of cake, and therefore not a piece of cake to analyse. 53,365 items may sound like a lot, but a common estimate of the number of idioms in English is 25,000. The number of multiword units is much, much higher. 53,365 is not going to be enough for any reliable capture.

Since any given text is likely to contain a lot of formulaic language, the next task is to decide how to select for presentation (i.e. as learning objects) from those identified. The challenge is, as Lin (2022) remarks, both technical and theoretical: how can frequency and learnability be measured? There are no easy answers, and the approach of IdiomsTube is, by its own admission, crude. The algorithm prioritises longer items that contain lower frequency single items, and which have a low frequency of occurrence in a corpus of 40,000 randomly-sampled YouTube videos. The aim is to focus on formulaic language that is ‘more challenging in terms of composition (i.e. longer and made up of more difficult words) and, therefore, may be easier to miss due to their infrequent appearance on YouTube’. My immediate reaction is to question whether this approach will not prioritise items that are not worth the bother of deliberate learning in the first place.

The proof is in the proverbial pudding, so I looked at the learning items that were offered by my sample of 15 recommended videos. Sadly, IdiomsTube does not even begin to cut the mustard. The rest of this section details why the selection was so unsatisfactory: you may want to skip this and rejoin me at the start of the next section.

  • In total 85 target items were suggested. Of these 39 (just under half) were not fixed expressions. They were single items. Some of these single items (e.g. ‘blog’ and ‘password’ would be extremely easy for most learners). Of the others, 5 were opaque idioms (the most prototypical kind of idiom), the rest were collocations and fixed (but transparent) phrases and frames.
  • Some items (e.g. ‘I rest my case’) are limited in terms of the contexts in which they can be appropriately used.
  • Some items did not appear to be idiomatic in any way. ‘We need to talk’ and ‘able to do it’, for example, are strange selections, compared to others in their respective lists. They are also very ‘easy’: if you don’t readily understand items like these, you wouldn’t have a hope in hell of understanding the video.
  • There were a number of errors in the recommended target items. Errors included duplication of items within one set (‘get in the way’ + ‘get in the way of something’), misreading of an item (‘the shortest’ misread as ‘the shorts’), mislabelling of an item (‘vend’ instead of ‘vending machine’), linking to the wrong dictionary entry (e.g. ‘mini’ links to ‘miniskirt’, although in the video ‘mini’ = ‘small’, or, in another video, ‘stoke’ links to ‘stoked’, which is rather different!).
  • The selection of fixed expressions is sometimes very odd. In one video, the following items have been selected: get into an argument, vend, from the ground up, shovel, we need to talk, prefecture. The video contains others which would seem to be better candidates, including ‘You can’t tell’ (which appears twice), ‘in charge of’, ‘way too’ (which also appears twice), and ‘by the way’. It would seem, therefore, that some inappropriate items are selected, whilst other more appropriate ones are omitted.
  • There is a wide variation in the kind of target item. One set, for example, included: in order to do, friction, upcoming, run out of steam, able to do it, notification. Cross-checking with Pearson’s Global Scale of English, we have items ranging from A2 to C2+.

The challenges of automation

IdiomsTube comes unstuck on many levels. It fails to recommend appropriate videos to watch. It fails to suggest appropriate language to learn. It fails to provide appropriate practice. You wouldn’t know this from reading the article by Phoebe Lin in the ReCALL journal which does, however, suggest that ‘further improvements in the design and functions of IdiomsTube are needed’. Necessary they certainly are, but the interesting question is how possible they are.

My interest in IdiomsTube comes from my own experience in an app project which attempted to do something not completely dissimilar. We wanted to be able to evaluate the idiomaticity of learner-generated language, and this entailed identifying formulaic patterns in a large corpus. We wanted to develop a recommendation engine for learning objects (i.e. the lexical items) by combining measures of frequency and learnability. We wanted to generate tasks to practise collocational patterns, by trawling the corpus for contexts that lent themselves to gapfills. With some of these challenges, we failed. With others, we found a stopgap solution in human curation, writing and editing.

IdiomsTube is interesting, not because of what it tells us about how technology can facilitate language learning. It’s interesting because it tells us about the limits of technological applications to learning, and about the importance of sorting out theoretical challenges before the technical ones. It’s interesting as a case study is how not to go about developing an app: its ‘special enhancement features such as gamification, idiom-of-the-day posts, the IdiomsTube Teacher’s interface and IdiomsTube Facebook and Instagram pages’ are pointless distractions when the key questions have not been resolved. It’s interesting as a case study of something that should not have been published in an academic journal. It’s interesting as a case study of how techno-enthusiasm can blind you to the possibility that some learning challenges do not have solutions that can be automated.

References

Boers, F. (2020) Factors affecting the learning of multiword items. In Webb, S. (Ed.) The Routledge Handbook of Vocabulary Studies. Abingdon: Routledge. pp. 143 – 157

Boers, F. (2021) Evaluating Second Language Vocabulary and Grammar Instruction. Abingdon: Routledge

Erman, B. & Warren, B. (2000) The idiom principle and the open choice principle. Text, 20 (1): pp. 29 – 62

Hill, J. (2001) Revising priorities: from grammatical failure to collocational success. In Lewis, M. (Ed.) Teaching Collocation: further development in the Lexical Approach. Hove: LTP. Pp.47- 69

Laufer, B. (2022) Formulaic sequences and second language learning. In Szudarski, P. & Barclay, S. (Eds.) Vocabulary Theory, Patterning and Teaching. Bristol: Multilingual Matters. pp. 89 – 98

Lin, P. (2022). Developing an intelligent tool for computer-assisted formulaic language learning from YouTube videos. ReCALL 34 (2): pp.185–200.

O’Keeffe, A., McCarthy, M. & Carter, R. (2007) From Corpus to Classroom. Cambridge: Cambridge University Press

Pellicer-Sánchez, A. (2020) Learning single words vs. multiword items. In Webb, S. (Ed.) The Routledge Handbook of Vocabulary Studies. Abingdon: Routledge. pp. 158 – 173

You have probably heard of the marshmallow experiment, one of the most famous and widely cited studies in social psychology. In the experiments, led by Walter Mischel at Stanford University in 1972, pre-school children were offered a choice between an immediate small reward (such as a marshmallow) or a significantly larger reward if they could wait long enough (a few minutes) to receive it. A series of follow-up studies, beginning in 1988, found that those children who had been able to delay gratification in the original experiments had better educational achievements at school and in college than those who had less self-control.

The idea that character traits like self-control could have an important impact on educational outcomes clearly resonated with many people at the time. The studies inspired further research into what is now called socio-emotional learning, and helped to popularise many educational interventions across the world that sought to teach ‘character and resilience’ in schools. In Britain alone, £5 million was pledged for a programme in 2015 to promote what the government called ‘character work’, an initiative that saw rugby coaches being used to instil the values of respect, teamwork, enjoyment, and discipline in school children.

One person who was massively influenced by the marshmallow experiment (and who, in turn, massively influenced the character-building interventions in schools), was Angela Duckworth (Duckworth et al., 2013), who worked at Stanford between 2014 and 2015. Shortly after her studies into delay of gratification, Duckworth gave a TED talk called ‘Grit: the power of passion and perseverance’ which has now had almost 10 million views. A few years later, her book with the same title (Duckworth, 2016) was published. An instant best-seller, ‘grit’ became a ‘hot topic’ in education, and, according to the editors of a special issue of The Journal for the Psychology of Language Learning (MacIntyre & Khajavy, 2021), ‘interest appears to be rapidly expanding’. Duckworth has argued that self-control and grit are different and unrelated, but a number of studies have contradicted this view (Oxford & Khajafy, 2021), and the relationship between the two is clear in Duckworth’s intellectual and publishing trajectory.

This continued and expanding interest in grit is a little surprising. In a previous (June, 2020) blog post , I looked at the problems with the concept of ‘grit’, drawing on the work of Marcus Credé (2017; 2018) that questioned whether it made sense to talk about ‘grit’ as a unitary construct, noted the difficulty of measuring ‘grit’ and the lack of evidence in support of educational interventions to promote ‘grit’ (despite the millions and millions that have been spent). In a more recent article, Credé and his collaborator, Michael Tynan (Credé & Tynan, 2021), double-down on their criticisms, observing that ‘meta-analytic syntheses of the grit literature have shown that grit is a poor predictor of performance and success in its own right, and that it predicts success in academic and work settings far more poorly than other well-known predictors’. One of these other well-known predictors is the socio-economic status of students’ families. Credé and Tynan remain ‘deeply skeptical of the claim that grit, as a unitary construct formed by combining scores on perseverance and passion, holds much value for researchers focused on SLA—or any other domain’.

In the same journal issue as the Credé and Tynan article, Rebecca Oxford and Gholam Khajavy (2021) sound further notes of caution about work on ‘grit’. They suggest that researchers need to avoid confusing grit with other constructs like self-control – a suggestion that may be hard or impossible to follow if, in fact these constructs are not clearly separable (as Oxford and Khajavy note). They argue, too, that much more attention needs to be paid to socio-economic contexts, that structural barriers to achievement must be given fuller consideration if ‘grit’ is to contribute anything positive to social justice. Whether the other papers in this special edition of the Journal for the Psychology of Language Learning that is devoted to ‘grit’ heed the cautionary advice of Credé and Tynan, Oxford and Khajavy is, I think, open to debate. Perhaps the idea of a whole edition of a journal devoted to ‘grit’ is a problematic starting point. Since there is no shortage of reasons to believe that ‘grit’ isn’t actually a ‘thing’, why take ‘grit’ as a starting point for scholarly enquiry?

It might be instructive to go back to how ‘grit’ became a ‘thing’ in the first place. It’s an approach that the contributors to the special issue of the Journal for the Psychology of Language Learning have not adopted. This brings me back to the marshmallow test. At the time that ‘grit’ was getting going, Alfie Kohn brought out a book called ‘The Myth of the Spoiled Child’ (Kohn, 2014) that included a chapter ‘Why Self-Discipline Is Overrated: A Closer Look at Grit, Marshmallows, and Control from Within’. Kohn argued that educational ideas about ‘grit’ had misrepresented the findings of the marshmallow test and its follow-up studies. He argued that setting was more important than individual self-control, and that deferral of gratification was likely an effect, not a cause of anything. His ideas were supported by some of the original researchers, including Mischel himself. Another, Yuichi Shoda, a co-author of a key paper that linked delay of gratification to SAT scores, has observed that ‘Our paper does not mention anything about interventions or policies’ – many other factors would need to be controlled to validate the causal relationship between self-control and academic achievement (Resnick, 2018).

Interest in recent years in replicating experiments in social psychology has led to confirmation that something was seriously wrong with the follow-ups to the marshmallow experiment. Studies (e.g. Watts et al., 2018) with more representative and larger groups of children have found that correlations between academic achievement and self-control almost vanished when controlled for factors like family background and intelligence. Even if you can teach a child to delay gratification, it won’t necessarily lead to any benefits later on.

Self-control and ‘grit’ may or may not be different things, but one thing they clearly have in common is their correlation with socio-economic differences. It is distinctly possible that attention to ‘grit’, in language learning and in other fields, is a distraction from more pressing concerns. Pity the poor researchers who have hitched themselves to the ‘grit’ bandwagon … As Angela Duckworth has said, research into grit is itself ‘a delay of gratification test’ (Duckworth, 2013). You have to be really passionate about grit and show sustained persistence if you want to keep on publishing on the subject, despite all that we now know. She hopes ‘that as a field we follow through on our intentions to forgo more immediately rewarding temptations to instead do what is best for science in the long-run’. How about forgoing the immediately rewarding temptation of publishing yet more stuff on this topic?

References

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

Credé, M. & Tynan, M. C. (2021) Should Language Acquisition Researchers Study “Grit”? A Cautionary Note and Some Suggestions. Journal for the Psychology of Language Learning, 3 (2), 37 – 44

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

Duckworth, A. L. (2013) Is It Really Self-control: A Critical Analysis of the “Marshmallow Test” Society of Personality and Social Psychology Connections November 10, 2013 https://spsptalks.wordpress.com/2013/11/10/is-it-really-self-control-a-critical-analysis-of-the-marshmallow-test/

Duckworth, A. L., Tsukayama, E. & Kirby, T. A. (2013) Is it really self-control? Examining the predictive power of the delay of gratification response. Personality and Social Psychology Bulletin, 39, 843-855.

Duckworth, A. (2016) Grit: the power of passion and perseverance. New York: Scribner

Kohn, A. (2014) The Myth of the Spoiled Child. Boston: Da Capo Press

MacIntyre, P. & Khajavy, G. H. (2021) Grit in Second Language Learning and Teaching: Introduction to the Special Issue. Journal for the Psychology of Language Learning, 3 (2), 1-6. http://www.jpll.org/index.php/journal/article/view/86

Oxford, R. & Khajafy, G. H. (2021) Exploring Grit: “Grit Linguistics” and Research on Domain-General Grit and L2 Grit. Journal for the Psychology of Language Learning, 3 (2), 7 – 35

Resnick, B. (2018) The “marshmallow test” said patience was a key to success. A new replication tells us s’more. Vox, June 6, 2018. https://www.vox.com/science-and-health/2018/6/6/17413000/marshmallow-test-replication-mischel-psychology

Watts, T.W., Duncan, G.J. & Quan, H. (2018) Revisiting the Marshmallow Test: A Conceptual Replication Investigating Links Between Early Delay of Gratification and Later Outcomes. Psychological Science 29 (7): 1159-1177.

Always learning

In an earlier post , I explored the use of the phrase ‘Always learning’ as a promotional tagline by Pearson. Pearson’s use of the phrase peaked in the early years of the 2010s at a time when the company, facing growing criticism for the length and aggressivity of its tentacles in US education (Ravitch, 2012; Sellar et al, 2016), was particularly keen to fashion ‘its image as a socially responsible edu-business’. Not coincidentally, ‘lifelong learning’, the big idea evoked by ‘Always learning’, saw a resurgence of interest around the same time, as the United Nations published their Sustainable Development Goals in 2015. The fourth of these was:

‘Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.’

This was an extension of the earlier (2000) UN Millennium Development Goal, which aimed for universal primary education. It had been recognised that this was not sufficient to break global cycles of poverty. For that, not only universal secondary education, but also post-secondary (lifelong) learning, were needed, too. The goal was criticised for being vague, over-ambitious and unrealisable, but it was so obviously a ‘good thing’ that it could do nobody any harm to be associated with it.

Lifelong learning, democracy and human capital

The idea of lifelong education may be vague, but its history can be traced back to at least Confucius who said that ‘life is limited, while learning is limitless’ (Guo-Dong, 1994). Plato advocated lifelong learning for the highest ranking members of society. Comenius promoted a more democratic version of lifelong learning, as did Condorcet during the French Revolution (Matheson & Matheson, 1996). More recent incarnations of the idea are often traced back to John Dewey (Fleming, 2011), who saw a close connection between education and democracy, and believed that learning should continue past school ‘irrespective of age’ (Dewey, 1916: 55). The UNESCO report (Faure, 1972), which did so much to establish the idea of lifelong learning in contemporary educational discourse, was very much in the democratic Dewey tradition.

In more recent discourse, the democratic veneer remains visible, but a human capital approach to lifelong learning is now clearly privileged (Fleming, 2011). Supported by international bodies like the OECD and the EU, current discourses prioritize the needs of the marketplace, and place the emphasis on learning as an individualized responsibility (Olssen, 2006). References abound to the rapidly changing nature of our contemporary world, especially the world of work, where only lifelong learning can offer the adaptability and flexibility needed for our occupational, political and ecological survival. Notions of a fuller life and self-actualization have not gone away, but interest is much more squarely centred on the part that lifelong learning can play in the development of human capital. A recent (2021) article from Pearson entitled ‘New research shows employers see lifelong learning as the ‘new normal’ as UK Government releases skills data’ https://plc.pearson.com/en-US/news/new-research-shows-employers-see-lifelong-learning-new-normal-uk-government-releases-skills is typical in this respect. In a similar vein, MOOC provider, FutureLearn (2022), has recently brought out a report into the ‘future of learning’ in which ‘lifelong learning’ is seen as ‘critical to upskilling the workforce of the future’.

Like so many other words I have looked at on this blog, ‘lifelong learning’ ‘has all the trappings of what might be termed a ‘good idea’ — it is bedecked with hurrah words and emotive terms, liberally dispersed by its proponents, and this gives it an air of conceptual solidity, together with making it more readily popular’ (Matheson & Matheson). Meaning little more than learning that is not confined to school, the best way of understanding the term is perhaps to look at what people actually do with it.

Lifelong learning and English language teaching

In the world of English language teaching, one of the early uses of the term ‘lifelong learning’ was in the title of a plenary IATEFL presentation, ‘Developing learner autonomy – preparing learners for lifelong learning’ (Dam, 2002). It was an interesting, but hardly contentious, lecture, arguing that (1) lifelong learning is necessary because schools can’t teach everything, (2) that learner autonomy is necessary for lifelong learning, so (3) our educational focus should be more on learning and less on teaching. Precisely what should be learnt in the long life of learning is left unspecified, and whether that learning should literally continue till death do us part remained equally unclear. Leni Dam was invoking the fashionable term of ‘lifelong learning’ to sell the idea of ‘learner autonomy’. But it really wasn’t needed: even month-long learning would be enough to justify the encouragement of learner autonomy.

There is, however, no disputing the potential of the term ‘lifelong learning’ in selling ideas. I recently came across the lovely phrase ‘premature ultimate’ (try googling it!) – ‘a concept or term that provokes such reverence and contains such connotative potency that its invocation tends to silence any further discussion on a matter’ (Brookfield, 1986). Great for selling, in other words, as on the website of the wonderfully named ‘Enjoy TEFL’ , ‘the Global Number 1 Accredited TEFL and Mindfulness Provider’, which manages to pack ‘lifelong learning’, ‘21st century’, ‘creativity’ and ‘innovation’ into just two lines. Their current promotion offers two free mindfulness courses when you buy a 120 / 180 hour TEFL course.

Linking ‘lifelong learning’ and ‘21st century skills’ is standard practice. The Lifelong Learning Programme 2007 – 2013 of the EU had rather vague objectives, but the desirable skills that were listed were largely indistinguishable from other lists of C21 skills / global skill / soft skills: communication competencies, digital competencies, social and emotional skills, and so on (Kaplan, 2016). Coupling the two concepts means that anything loosely connected with the latter can be promoted by association with the former. Two examples. Creativity and lifelong learning are associated in an article by Daniel Xerri (2017) that seeks to ‘mobilise students’ creative thinking’ and to show ‘how the English language classroom can serve as an incubator for an awareness of the need to ensure inclusive and equitable quality education, and to promote lifelong learning opportunities for all’. Xerri is certainly interested in using ‘creativity’ tasks to promote awareness of the first part of the UN’s SDG, but the ‘lifelong learning’ bit is not explored at all. In contrast, Reinders et al (2022) explore in some depth what they mean by ‘lifelong learning’, but the bottom line is the promotion of the use of digital tools in language learning. ‘Lifelong learning’ (or ‘lifewide learning[1]’, as they call it) is just one reason for advocating the use of digital technologies.

Competing with ‘Enjoy TEFL’ for the prize of the crudest invocation of ‘lifelong learning’ is Darren Nicholls, a product manager for Pearson. A promo for some new Pearson proficiency tests describes them as ‘web-based tests [that] first stream students into the appropriate class and then monitor their progress over an extended period of time. Both tests are hosted on a new platform, Test Hub, which supports lifelong learning by bringing together all proficiency assessments under one roof’. Lifelong learning would seem to mean digital homework.

Lifelong learning and CPD

I have often heard myself (and many others) saying that a good teacher is one who never stops learning. It’s the kind of wisdom of online memes. Once you stop learning you start dying, Albert Einstein didn’t actually say, but let’s not worry about attributional details. ‘Enjoy TEFL’ tries to sell its courses by appealing to the same sentiment, and they are not alone. The blurb for an IATEFL Poland webinar says ‘Being networked is of key importance to all professionally active people in the process of lifelong learning …’ A joint LTSIG and TDSIG conference in Istanbul in 2012 waxed lyrical: ‘This is an age of lifelong learning, or ‘perpetual beta’, of learning anywhere, any place, any time’. Professional development is a lifelong obligation and, for those who are super-keen, JALT (the Japanese Association of Language Teachers) has a ‘Lifelong Language Learning Special Interest Group’ which organises events and a regular newsletter.

All well and good, you may be thinking, but pause a moment to think about the way in which the discourse of lifelong learning ‘orientates education to the enterprise society where the learner (or the teacher as learner) becomes an entrepreneur of him / herself’ (Olssen, 2006). Never mind that increasing numbers of teachers are on zero-hours contracts or fail to take home the minimum wage, a commitment to lifelong professional development is expected. Where better place to start than next week’s IATEFL conference, with its free, daily mindfulness workshops? If you’re based in the UK and working at one of the many language schools that pays the minimum wage, you’ll only need to clock up about 100 hours of teaching to afford it.

References

Brookfield, S. (1986) Understanding and Facilitating Adult Learning. Hoboken, NJ: Jossey – Bass

Dam, L. (2002) Developing learner autonomy – preparing learners for lifelong learning. In Pulverness, A. (Ed.) IATEFL 2002 York Conference Selections. Whitstable, Kent: IATEFL

Dewey, J. (1916) Democracy and education. New York: Macmillan.

Faure, E. (1972) Learning to be: The world of education today and tomorrow. Paris: UNESCO.

Fleming, T. (2011) Models of Lifelong Learning: An Overview. In M. London (Ed.). Oxford Handbook of Lifelong Learning (pp. 29-39). New York: Oxford University Press.

FutureLearn (2022) The Future of Learning Report 2022. London: FutureLearn https://www.futurelearn.com/info/thefutureoflearning

Guo-Dong, X. (1994) Lifelong education in China: new policies and activities. International Review of Education, 40, (3-5)

Jackson, N. J. (Ed.) (2011) Learning for a complex world: A lifewide concept of learning, development and achievement. AuthorHouse Publishing. Available at: https://www.lifewideeducation.uk/learning-for-a-complex-world.html

Kaplan, A. (2016) Lifelong Learning: Conclusions From A Literature Review. International Online Journal of Primary Education, 5 (2): pp. 43 – 50

Matheson, D. & Matheson, C. (1996) Lifelong Learning and Lifelong Education: a critique. Research in Post‐Compulsory Education, 1 (2): pp. 219-236, DOI: 10.1080/1359674960010207

Olssen, M. (2006) Understanding the mechanisms of neoliberal control: lifelong learning, flexibility and knowledge capitalism. International Journal of Lifelong Education, 25 (3): pp. 213-230.

Ravitch, D. (2012) The United States of Pearson? http://dianeravitch.net/2012/05/07/the-united-states-of-pearson-2/

Reinders, H., Dudeney, G., & Lamb, M. (2022) Using Technology to Motivate Learners. Oxford: Oxford University Press

Sellar, S., Hogan, A. & Lingard, B. (2016) Always Learning. Education International https://www.ei-ie.org/en/item/21091:always-learning

Xerri, D. (2017) Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. In Maley, A. & Peachey, N. (Eds.) Integrating global issues in the creative English language classroom: With reference to the United Nations Sustainable Development Goals. London: British Council, pp. 49 – 56


[1] ‘Lifewide learning’ is not a term made up by Reinders et al. The idea has been around for over 20 years, piggy-backing on lifelong learning, and referring to the fact that learning takes place in a variety of different environments and situations. For more information, see Jackson (2011). And, if you really have nothing better to do, check out ‘lifedeep learning’. I thought, at first, it was a joke, but it’s been written about in all seriousness.

There’s a video on YouTube from Oxford University Press in which the presenter, the author of a coursebook for primary English language learners (‘Oxford Discover’), describes an activity where students have a short time to write some sentences about a picture they have been shown. Then, working in pairs, they read aloud their partner’s sentences and award themselves points, with more points being given for sentences that others have not come up with. For lower level, young learners, it’s not a bad activity. It provides opportunities for varied skills practice of a limited kind and, if it works, may be quite fun and motivating. However, what I found interesting about the video is that it is entitled ‘How to teach critical thinking skills: speaking’ and the book that is being promoted claims to develop ‘21st Century Skills in critical thinking, communication, collaboration and creativity’. The presenter says that the activity achieves its critical thinking goals by promoting ‘both noticing and giving opinions, […] two very important critical thinking skills.’

Noticing (or observation) and giving opinions are often included in lists of critical thinking skills, but, for this to be the case, they must presumably be exercised in a critical way – some sort of reasoning must be involved. This is not the case here, so only the most uncritical understanding of critical thinking could consider this activity to have any connection to critical thinking. Whatever other benefits might accrue from it, it seems highly unlikely that the students’ ability to notice or express opinions will be developed.

My scepticism is not shared by many users of the book. Oxford University Press carried out a scientific-sounding ‘impact study’: this consisted of a questionnaire (n = 198) in which ‘97% of teachers reported that using Oxford Discover helps their students to improve in the full range of 21st century skills, with critical thinking and communication scoring the highest’.

Enthusiasm for critical thinking activities is extremely widespread. In 2018, TALIS, the OECD Teaching and Learning International Survey (with more than 4000 respondents) found that ‘over 80% of teachers feel confident in their ability to vary instructional strategies in their classroom and help students think critically’ and almost 60% ‘frequently or always’ ‘give students tasks that require students to think critically.’ Like the Oxford ‘impact study’, it’s worth remembering that these are self-reporting figures.

This enthusiasm is shared in the world of English language teaching, reflected in at least 17 presentations at the 2021 IATEFL conference that discussed practical ideas for promoting critical thinking. These ranged from the more familiar (e.g. textual analysis in EAP) to the more original – developing critical thinking through the use of reading reaction journals, multicultural literature, fables, creative arts performances, self-expression, escape rooms, and dice games.

In most cases, it would appear that the precise nature of the critical thinking that was ostensibly being developed was left fairly vague. This vagueness is not surprising. Practically the only thing that writers about critical thinking in education can agree on is that there is no general agreement about what, precisely, critical thinking is. Lai (2011) offers an accessible summary of a range of possible meanings, but points out that, in educational contexts, its meaning is often rather vague and encompasses other concepts (such as higher order thinking skills) which also lack clarity. Paul Dummett and John Hughes (2019: 4) plump for ‘a mindset that involves thinking reflectively, rationally and reasonably’ – a vague definition which leaves unanswered two key questions: to what extent is it a skill set or a disposition? Are these skills generic or domain specific?

When ‘critical thinking’ is left undefined, it is impossible to evaluate the claims that a particular classroom activity will contribute to the development of critical thinking. However, irrespective of the definition, there are good reasons to be sceptical about the ability of educational activities to have a positive impact on the generic critical thinking skills of learners in English language classes. There can only be critical-thinking value in the activity described at the beginning of this post if learners somehow transfer the skills they practise in the activity to other domains of their lives. This is, of course, possible, but, if we approach the question with a critical disposition, we have to conclude that it is unlikely. We may continue to believe the opposite, but this would be an uncritical act of faith.

The research evidence on the efficacy of teaching generic critical thinking is not terribly encouraging (Tricot & Sweller, 2014). There’s no shortage of anecdotal support for classroom critical thinking, but ‘education researchers have spent over a century searching for, and failing to find evidence of, transfer to unrelated domains by the use of generic-cognitive skills’ (Sweller, 2022). One recent meta-analysis (Huber & Kuncel, 2016) found insufficient evidence to justify the explicit teaching of generic critical thinking skills at college level. In an earlier blog post https://adaptivelearninginelt.wordpress.com/2020/10/16/fake-news-and-critical-thinking-in-elt/ looking at the impact of critical thinking activities on our susceptibility to fake news, I noted that research was unable to find much evidence of the value of media literacy training. When considerable time is devoted to generic critical thinking training and little or no impact is found, how likely is it that the kind of occasional, brief one-off activity in the ELT classroom will have the desired impact? Without going as far as to say that critical thinking activities in the ELT classroom have no critical-thinking value, it is uncontentious to say that we still do not know how to define critical thinking, how to assess evidence of it, or how to effectively practise and execute it (Gay & Clark, 2021).

It is ironic that there is so little critical thinking about critical thinking in the world of English language teaching, but it should not be particularly surprising. Teachers are no more immune to fads than anyone else (Fuertes-Prieto et al., 2020). Despite a complete lack of robust evidence to support them, learning styles and multiple intelligences influenced language teaching for many years. Mindfulness, growth mindsets, grit are more contemporary influences and, like critical thinking, will go the way of learning styles when the commercial and institutional forces that currently promote them find the lack of empirical supporting evidence problematic.

Critical thinking is an educational aim shared by educational authorities around the world, promoted by intergovernmental bodies like the OECD, the World Bank, the EU, and the United Nations. In Japan, for example, the ‘Ministry of Education (MEXT) puts critical thinking (CT) at the forefront of its ‘global jinzai’ (human capital for a global society) directive’ (Gay & Clark, 2021). It is taught as an academic discipline in some universities in Russia (Ivlev et al, 2021) and plans are underway to introduce it into schools in Saudi Arabia. https://www.arabnews.com/node/1764601/saudi-arabia I suspect that it doesn’t mean quite the same thing in all these places.

Critical thinking is also an educational aim that most teachers can share. Few like to think of themselves as Gradgrinds, bashing facts into their pupils’ heads: turning children into critical thinkers is what education is supposed to be all about. It holds an intuitive appeal, and even if we (20% of teachers in the TALIS survey) lack confidence in our ability to promote critical thinking in the classroom, few of us doubt the importance of trying to do so. Like learning styles, multiple intelligences and growth mindsets, it seems possible that, with critical thinking, we are pushing the wrong thing, but for the right reasons. But just how much evidence, or lack of evidence, do we need before we start getting critical about critical thinking?

References

Dummett, P. & Hughes, J. (2019) Critical Thinking in ELT. Boston: National Geographic Learning

Fuertes-Prieto, M.Á., Andrés-Sánchez, S., Corrochano-Fernández, D. et al. (2020) Pre-service Teachers’ False Beliefs in Superstitions and Pseudosciences in Relation to Science and Technology. Science & Education 29, 1235–1254 (2020). https://doi.org/10.1007/s11191-020-00140-8

Gay, S. & Clark, G. (2021) Revisiting Critical Thinking Constructs and What This Means for ELT. Critical Thinking and Language Learning, 8 (1): pp. 110 – 147

Huber, C.R. & Kuncel, N.R. (2016) Does College Teach Critical Thinking? A Meta-Analysis. Review of Educational Research. 2016: 86 (2) pp.:431-468. doi:10.3102/0034654315605917

Ivlev, V. Y., Pozdnyakov, M. V., Inozemtsez, V. A. & Chernyak, A. Z. (2021) Critical Thinking in the Structure of Educational Programs in Russian Universities. Advances in Social Science, Education and Humanities Research, volume 555: pp. 121 -128

Lai, E.R. 2011. Critical Thinking: A Literature Review. Pearson. http://images.pearsonassessments.com/images/tmrs/CriticalThinkingReviewFINAL.pdf

Sweller, J. (2022) Some Critical Thoughts about Critical and Creative Thinking. Sydney: The Centre for Independent Studies Analysis Paper 32

Tricot, A., & Sweller, J. (2014) Domain-specific knowledge and why teaching generic skills does not work. Educational Psychology Review, 26, 265- 283.

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

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

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

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

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

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

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

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

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

References

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

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

In the latest issue of ‘Language Teaching’, there’s a ‘state-of-the-art’ article by Frank Boers entitled ‘Glossing and vocabulary learning’. The effect of glosses (‘a brief definition or synonym, either in L1 or L2, which is provided with [a] text’ (Nation, 2013: 238)) on reading comprehension and vocabulary acquisition has been well researched over the years. See Kim et al. (2020) for just one recent meta-analysis.

It’s a subject I have written about before on this blog (see here), when I focussed on Plonsky ad Ziegler (2016), a critical evaluation of a number of CALL meta-analyses, including a few that investigated glosses. Plonsky and Ziegler found that glosses can have a positive effect on language learning, that digital glosses may be more valuable than paper-based ones, and that both L1 and L2 glosses can be beneficial (clearly, the quality / accuracy of the gloss is as important as the language it is written in). Different learners have different preferences. Boers’ article covers similar ground, without, I think, adding any new takeaways. It concludes with a predictable call for further research.

Boers has a short section on the ‘future of glossing’ in which he notes that (1) ‘onscreen reading [is] becoming the default mode’, and (2) that ‘materials developers no longer need to create glosses themselves, but can insert hyperlinks to online resources’. This is not the future, but the present. In my last blog post on glossing (August 2017), I discussed Lingro, a digital dictionary tool that you can have running in the background, allowing you to click on any word on any website and bring up L1 or L2 glosses. My reservation about Lingro was that the quality of the glosses left much to be desired, relying as they did on Wiktionary. Things would be rather different if it used decent content – sourced, for example, from Oxford dictionaries, Robert (for French) or Duden (for German).

And this is where the content for the Google Dictionary for Chrome extension comes from. It’s free, and takes only seconds to install. It allows you to double-click on a word to bring up translations or English definitions. One more click will take you to a more extensive dictionary page. It also allows you to select a phrase or longer passage and bring up translations generated by Google Translate. It allows you to keep track of the items you have looked up, and to download these on a spreadsheet, which can then be converted to flashcards (e.g. Quizlet) if you wish. If you use the Safari browser, a similar tool is already installed. It has similar features to the Google extension, but also offers you the possibility of linking to examples of the targeted word in web sources like Wikipedia.

Boers was thinking of the provision of hyperlinks, but with these browser extensions it is entirely up to the reader of a text to decide how many and which items to look up, what kind of items (single words, phrases or longer passages) they want to look up, how far they want to explore the information available to them, and what they want to do with the information (e.g. store / record it).

It’s extraordinary that a ‘state-of-the-art article’ in an extremely reputable journal should be so out of date. The value of glossing in language learning is in content-focussed reading, and these tools mean that any text on the web can be glossed. I think this means that further research of the kind that Boers means would be a waste of time and effort. The availability of free technology does not, of course, solve all our problems. Learners will continue to benefit from guidance, support and motivation in selecting appropriate texts to read. They will likely benefit from training in optimal ways of using these browser extensions. They may need help in finding a balance between content-focussed reading and content-focussed reading with a language learning payoff.

References

Boers, F. (2022). Glossing and vocabulary learning. Language Teaching, 55 (1), 1 – 23

Kim, H.S., Lee, J.H. & Lee, H. (2020). The relative effects of L1 and L2 glosses on L2 learning: A meta-analysis. Language Teaching Research. December 2020.

Nation, I.S.P. (2013). Learning Vocabulary in Another Language. Cambridge: Cambridge University Press

Plonsky, L. & Ziegler, N. (2016). The CALL–SLA interface: insights from a second-order synthesis. Language Learning & Technology 20 / 2: 17 – 37

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

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

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

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

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

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

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

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

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

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

References

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

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

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

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

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

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

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

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

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

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

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

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

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

There’s a wonderful promotional video for Pearson English https://www.youtube.com/watch?v=b6o1s8U88N8 that packs as many clichéd slogans and images into one minute as you could ever wish for. Here’s the script:

Great things happen when you dare to dream / Learning is a journey filled with challenge, wonder and discovery / Educators not only inspire the future they also define it / We partner with the learning community to change futures / It’s our passion / Together we can inspire / Together we can empower / Together we can achieve / Change is happening all around us, faster than ever / Let’s empower change / There’s an exciting future ahead / Expect great things / Pearson English / Dare to learn, dare to change / Pearson always learning

How futures will be changed, what exactly can be inspired or empowered, what great things we can expect, what we might dare to learn or change – all these minor details are left unanswered. It is a wonderful example of advertising language, aka bullshit, defined by philosopher Harry Frankfurt (2005) as discourse that is only intended to persuade, without any concern for truth. It’s language where meanings are not shared, but where emotional responses are desired.

Pearson refers to its slogan ‘Always learning’ as their ‘brand tagline’. It is, they say, ‘Short, bold, and memorable, “Always Learning” encapsulates our learners and ourselves. It highlights Pearson’s commitment to constantly be discovering, learning and improving ourselves. And it describes what we enable our learners to do–to keep learning, whenever, wherever and however it suits them, throughout every stage of their lives’. The company provides detailed advice to its employees about how the slogan can be used: when, where, when not, colour combinations, good and bad examples of use, translations, etc. All of this makes for fascinating reading, which, strangely, is available online (at least, for the time being!).

Bullshit is a wise approach in advertising ELT products. If you get too specific / meaningful, you run the risk of coming out with bullshit of the non-philosophical kind. Macmillan English, for example, has the new slogan ‘Advancing learning’ and says: As technology opens new doors for teachers and students, we use our expertise to create products that suit different learning styles and design innovative new tools for teachers and students.

With ELT conference season getting underway in some parts of the world, slogans, clichés and buzzwords are vying for our attention in the marketing of these events. There are ELT conferences of a commercial, predatory kind (‘guaranteed publication of your work in the conference proceedings’) where the slogans are clearly bullshit (in the philosophical sense). The upcoming ‘4th International Conference on Modern Research in Education, Teaching and Learning’ (22 – 24 April in Barcelona) has the marvellous slogan ‘The only of all English language teaching conference’ and can be attended for only €320 (much cheaper if you just want to listen without presenting).

But for conferences organised by teachers’ associations, it would be inaccurate and inappropriate to describe their choice of slogans as bullshit. This doesn’t mean, however (as an entertaining blog post at ELT Rants, Reviews and Reflections in 2015 described them), that they are not ‘buzzword-heavy word salads [that] are rinsed, re-used, and repeated ad nauseum’. Here’s a small current selection for you to take your pick from. The resemblance, in many cases, to the language of the Pearson promo video is striking.

ELT in the digital era and beyond: innovation, engagement, and resilience (ThaiTESOL)

The hybrid transition: emotional, social and educational impacts on language learning (TESOL Kuwait)

Connecting teachers, empowering learners (BBELT)

Innovating changes: a world of diversity (TESOL Spain)

Translanguaging and multilingualism in language teaching (TESOL Arabia)

Inspiring collaboration (BELTA)

For me, the standout slogan is definitely TESOL Arabia, since it is the only one that seems to be about something specific. But perhaps I’m wrong. Both translanguaging and multilingualism can mean quite a few different things. When you put the terms together, my thoughts turn first to questions of social justice, and the idea of a conference in which social justice is discussed in the Hyatt Regency hotel in Dubai is fairly surreal. As in most of these examples, conferences for ELT teachers tend to opt for broad themes which aim to include almost everyone in the field (Raza, 2018) and will usually index innovation, excellence, empowerment, and / or wellbeing.

A good slogan will include words that are themselves sloganized (Schmenk et al., 2019). ‘Innovation’ and ‘empowering’ are good examples here. Neither can truly be understood without familiarity with extensive co-texts which confer connotational meaning and rhetorical force. ‘Change’ (for ‘innovation’) and ‘helping’ (for ‘empowering’) don’t quite have the same heft, even though they basically mean the same.

It’s important that buzzwords don’t mean too much, but the ‘key processing features of successful slogans are simplicity, memorability and emotionality’ (Pavlenko, 2019: 146). By ‘emotionality’, Pavlenko means words that carry an upbeat / positive message. In this sense, TESOL Kuwait’s ‘emotional, social and educational impacts’ all sound rather neutral and academic. I think that ‘engagement, diversity and outcomes’ might resonate better. Similarly, ‘hybrid’ still needs to shake off some negative associations: ‘digital’ sounds more positively modern. Hats off to ThaiTESOL, whose ‘the digital era and beyond’ sounds positively visionary.

Even though slogans shouldn’t mean too much, they only work as slogans ‘as if their meaning were obvious’ (Schmenk et al., 2019: 4). In their exploration of sloganization in language education discourse, Schmenk et al (2019) look at ‘communicative language teaching’, ‘learner autonomy’, ‘innovation’, ‘multiple intelligences’, ‘intercultural / transcultural language learning’, ‘input’, ‘language commodification’ and ‘superdiversity’. In this blog, I’ve considered ‘innovation’, ‘resilience’, ‘translanguaging’ and ‘multilingualism’, among others. These buzzwords come and go – the field of language teaching is as keen on current trends as any other field – and they can usually be grouped into broader trends, which academics like to call ‘turns’. There’s the ‘social turn’ (Block, 2003), the ‘intercultural turn’ (Thorne, 2010), the ‘multilingual turn’ (May, 2013), the ‘critical turn’ (Dasli & Diáz, 2017), the ‘emotional turn’ (White, 2018), and these are just for starters. If you’re quick, you won’t be too late to register for the 2nd International Conference on Linguistic, Literary and Pedagogical Turns at the University of Wah. The conference doesn’t have a slogan, but my suggestion would be ‘The Turn Turn’.

Schmenk et al (2019: 3) note that language education is an inherently interdisciplinary field so it is not surprising to find so many of its current trends drawn from other disciplines. This has not always been the case. If we go back 30 / 40 years, the hot topics included corpora, task-based learning, and lexical approaches. Now, in the choice of slogans, ELT conferences are not dissimilar from other professional conferences in sales and marketing, management and leadership – see for example this website offering advice about organising such events.

Slogans and buzzwords are, of course, a marketing tool for ELT conferences and publishers, but they also play an important role in academic branding – the personal brand you construct for yourself as an academic. Aneta Pavlenko (2019: 1488 – 151) offers a useful set of strategies for this kind of academic branding, but similar strategies can also be used by ELT freelancers

  • Adopt a slogan / buzzword (simple, memorable and positive)
  • Link it to your work (easiest if it was either your idea in the first place or you were one of the first to import the idea into language education)
  • Institutionalize the slogan by organising conferences, courses, journals, supervising dissertations, and so on
  • Recycle the slogan endlessly (especially in the titles of publications)
  • Keep things pretty vague so you can’t be criticised too much
  • Frame the phenomenon in question with words like ‘radical’, ‘unprecedented’, ‘hugely complex’, ‘tremendously important’

Quoting the work of Michael Billig (2013), Pavlenko (2019: 160) suggests that we should not necessarily be asking ourselves what slogans and buzzwords mean. A better question is: what is the person who is using these words attempting to do with them?

My favourite ELT slogan is an anti-slogan slogan. It is Bo Cai Zhong Chang (‘assimilating merits of different teaching approaches for our own use’) which was used in China to advocate for a ‘methodological approach appropriate to the specific sociopolitical realities of the country’ (Feng & Feng, 2001). China has a long history of powerful slogans, of course, with ‘Dare to think, dare to act’ being the key phrase during the Great Leap Forward. Did the people at Pearson have this in mind when they came up with ‘Dare to learn, dare to change’?

References

Billig, M. (2013) Learn to Write Badly: How to Succeed in the Social Sciences. Cambridge: Cambridge University Press

Block, D. (2003) The Social Turn in Second Language Acquisition. Edinburgh: Edinburgh University Press

Dasli, M. & Diáz, A. R. (Eds.) (2017) The Critical Turn in Language and Intercultural Communication Pedagogy. New York: Routledge

Feng, A. & Feng, A. (2001) ‘Bo Cai Zhong Chang’ – A slogan for effective ELT methodology for College English education. English Language Teaching, 1: 1 – 22

Frankfurt, H. G. (2005) On Bullshit. Princeton: Princeton University Press

May. S. (Ed.) (2013) The multilingual turn: Implications for SLA, TESOL and Bilingual education. New York: Routledge

Pavlenko, A. (2019) Superdiversity and Why It Isn’t: Reflections on Terminological Innovation and Academic Branding. In Schmenk, B., Bredibach, S. & Küster, L. (Eds.) Sloganization in Language Education Discourses. Bristol: Multilingual Matters. pp. 142 – 168.

Raza, K. (2018) The Alignment of English Language Teacher Association Conference Themes to Research Agendas: An Investigation of TESOL International Association and IATEFL. In A. Elsheikh et al. (Eds.), The Role of Language Teacher Associations in Professional Development, Second Language Learning and Teaching. Cham: Springer pp. 117 – 129

Schmenk, B., Bredibach, S. & Küster, L. (Eds.) (2019) Sloganization in Language Education Discourses. Bristol: Multilingual Matters.

Thorne, S. L. (2010) The ‘Intercultural Turn’ and Language Learning in the Crucible of the New Media. In Helm, F. & Guth, S. (Eds.) Telecollaboration 2.0 for Language and Intercultural Learning. Bern: Peter Lang. pp. 139 – 164

White C.J. (2018) The Emotional Turn in Applied Linguistics and TESOL: Significance, Challenges and Prospects. In: Martínez Agudo J. (Eds) Emotions in Second Language Teaching. Cham: Springer

You have probably heard the following joke, or a version of it. What do we call a person who speaks three languages? A trilingual. And a person who speaks two languages? A bilingual. And someone who only speaks one language? An American. For the joke to work, even mildly, the listener has to buy in to the idea that multilingualism / plurilingualism is a ‘good thing’, and that too many Americans are monolingual.
Not everybody would share these views. Some would prefer the US (and other countries of immigration) to be more of a language graveyard than less of one. Negativity about multilingualism can be extreme, as in the wrath of those on Twitter who found a Coca Cola advertisement profoundly un-American, supportive of communism and terrorism. The advert in question showed a multicultural bunch of people sharing a Coke in perfect harmony while singing a multilingual rendition of ‘America the Beautiful’. To make things even worse, the commercial was shown at that homage to all things American, the Super Bowl.
Enthusiasm for multilingualism is, in part, a liberal reaction to the reactionary monolingualism of the ‘if-you-can’t-speak-our-language-go-back-to-your-own-fucking-country’ variety. Countering the post- 9/11 rise in monolingual linguistic prescriptivism in some countries (Cameron, 2013), tolerant multilingualism indexes visions of perfectly harmonious communities and the rhetoric of human rights and autonomy (Gramling, 2016: 205). It values diversity for its own sake.
It is also, in part, a reaction (see, for example, the Wikipedia entry or Maher, 2017) to a number of clearly widespread myths and misconceptions (e.g. that multilingual societies are less harmonious than monolingual ones or that bilingually raised children are cognitively disadvantaged). Going further than mere rebuttals, advocates of multilingualism argue, with some evidence, that it is good for critical and creative thinking, beneficial for problem-solving and decision-making, makes us more open to new ideas, more tolerant, more embracing of divergent thinking, and it can help stave off dementia. What is there not to like?
Most enthusiasts of multilingualism will list and expand on all the advantages of multilingualism that I have already mentioned, but many will also be interested in its market potential. Linguanomics, the title of a book by Gabrielle Hogan-Brun (2017), is the exploration of the economic aspects of multilingualism, the links between linguistic diversity and economic growth, and the ways in which linguistic capital may be converted into monetary capital. Citing Hogan-Brun, a blog post (Hardach, 2018; see also Hardach, 2021) for the World Economic Forum suggests that companies which invest more in languages do better in export markets; that countries with better language skills have higher GDP; and, therefore, countries should do more to tap the ‘vast, linguistic resource [of] migrant families’. Diversity has become human capital. Multilingualism is not just an end in itself, but a tool ‘in global collaborations to make the world a better place’ (Stein-Smith, 2021b) primarily through economic growth. In this framing, becoming multilingual (i.e. learning another language) is acquiring the ultimate 21st century skill (Stein-Smith, 2021a), so long, of course, as the language has value in the market place. English, for example.
Like all 21st century skills, multilingualism appears to have a readily obvious meaning, but does not, in fact, lend itself easily to a simple definition. Perhaps the defining feature of all 21st century skills is precisely the lack of precision, allowing the idea to be embraced by different people, from critical theorists to investment bankers, for different reasons. The European Commission (2007:6) defines the term as: ‘the ability of societies, institutions, groups and individuals to engage, on a regular basis, with more than one language in their day-to-day lives’. It leaves unanswered the key questions of what a language is, which languages are being referred to, and in which aspects of people’s day-to-day lives. But answers of a sort can be found when we look at the reasons for the European policy of multilingualism. In addition to the importance of diversity and respect for identities, the policy is intended (1) on a collective basis, to contribute to European unity (reflecting the EU’s motto ‘United in Diversity’) and (2) on an individual basis, to develop human capital and job mobility.
Can a policy of multilingualism be both a celebration of diversity and a tool for linguanomics – the development of human capital through languages? Problems arise when we look for the answer to the question of which language. Are we differentiating languages and dialects, and, if so, how? When the European Commission (2005: 4) says that it would like all European citizens to have ‘practical skills in at least two languages in addition to his or her mother tongue’, it’s fairly clear that this means ‘foreign languages’. And if part of the purpose of learning ‘foreign languages’ is to develop human capital, the language of choice is likely to be English most of the time. A particular kind of English. Closely related is the question of what is meant by ‘mother tongue’. If your home language is not the national language of the country in which you live, you’re unlikely to get much help from European states in developing your competencies in it. In practice, when development of human capital is weighed against diversity, the former takes precedence every time. Multilingualism in this European context is overridingly concerned with languages associated with nation states and is tied ‘to a future anterior of successful language learning among new citizens’ […] it ‘fulfils all the characteristics of neoliberal self-making: horizontal, voluntaristic, entrepreneurial, opportunity-rich, privatizable, decentralized, team-oriented, and, at turns hopeful or mute about structural poverty and other forms of socio-economic precaritization’ (Gramling, 2016: 204). In other words, interest in diversity may only be skin-deep: advocacy of multilingual policies may, in fact, be mostly about ‘targeting the anxiety within the [white, privileged, monolingual] majority about social and linguistic pluralism’ (McNamara, 2011: 38).
‘Language’, ‘diversity’ and ‘multilingualism’ are all strategically deployable shifters (Moore, 2015): their meanings shift in relation to the purposes for which the terms are being used. Multilingualism can stand in opposition to the bigotry of people in MAGA caps, but it can also stand in opposition to ‘unassimilated’ monolingual, migrant populations who haven’t learnt the language of the ‘host nation’. This is all rather problematic for those who do not want their espousal of multilingualism to be associated with xenophobia or a neoliberal agenda, and for those who want to dissociate diversity from human capital (Flores, 2013). Multilingualism, therefore, needs to be disambiguated, so that the multilingualism that is oriented towards social justice is not appropriated by those whose main interest in language learning is linguanomics (Katznelson & Bernstein, 2017).
This, I think, is what is behind the so-called ‘multilingual turn’ in applied linguistics, a turn that tries to bring social justice to the fore. In an attempt at terminological smash-and-grab, critical applied linguists set about reclaiming the term (May, 2013; Conteh & Meier, 2014). There are differences in interpretation between them (Meier, 2017), but the common denominator is a desire to redefine ‘language’ – not as a fixed and largely territorial system owned by native-speakers, but as a dynamic, complex, social, deterritorialized practice owned by its users. There is ample evidence to indicate that various forms of linguistic intermixing are more characteristic of everyday spoken communication than the orderly use of what we might call ‘monolanguages’ – separate, individual, named languages. The multilingualism of the multilingual turn contends that lingualism (Block, 2013) – the belief in the existence of monolanguages – is contrary to the evidence, and must be dispensed with in order to get away from the social injustice of native-speaker norms, of accentism, and linguistic prejudice.
In this light, the term ‘multilingual’ is problematic. It denotes countability and plurality. If we want or need to distance ourselves from lingualism – the idea of languages as bounded entities (e.g. English, Hebrew, Xhosa), ‘language’ needs to become a verb: ‘languaging’ or ‘translanguaging’ (see my previous post). The multilingual turn has led us to translanguaging and ‘few voices in applied linguistics have found fault with this positive counter-distinction of translanguaging over multilingualism’ (Gramling, 2021: 29). It is translanguaging, rather than multilingualism, that is now being offered as a, even the, theory of language (Li Wei, 2018).
For a strong critique of the idea that named languages (like English) do not exist, you could do worse than read a recent post by Geoff Jordan. Or you could simply try asking someone who’s about to take a TOEFL exam what they think of the idea (Gramling, 2021: 26). Even if we cannot clearly define the boundaries of what constitutes a named language like English, we cannot simply disinvent it. Our lives can be shaped by language exams, our online interactions are shaped by our choice of named language, and many of us invest a significant part of our identity in a named language. You may go along with Li Wei (2021) in disapproving of lingualism, but it won’t be going away any time soon. Quite how we are supposed to dispense with lingualism also remains less than clear. Perhaps Li Wei might begin by trying to get rid of the PGCE in Languages, or the MAs in TESOL or French at his own university, or its language proficiency requirements for students from countries that are not ‘majority English-speaking’. I suspect, though, that his institution’s linguanomic dispositive of multilingualism might prevent that happening.
Lingualism is at the heart of much English language learning, of English medium instruction, and of Li Wei’s own university (UCL) where nearly half the student body has paid to benefit from the linguistic capital that is on sale there. Lingualism may be (but is not necessarily) ‘indifferent to social justice, migration, asylum, refuge, immigration, decoloniality, or liberation from the strictures of monolingualism’ (Gramling, 2021: 66), but multilingualism of the translanguaging kind is unlikely to make much of a dent in our monolingualising world, either. It certainly isn’t going to help anyone who has to take a gate-keeping language test (Cameron, 2013). For all the noise about translanguaging in TESOL, it’s worth noting (Gramling, 2021: 70) that the overwhelming majority of current research into multilingualism comes, not from TESOL or applied linguistics, but from computational engineers and Natural Language Processing specialists. Compared to multilingual linguanomics, the ‘multilingual turn’ is a very niche affair. Most people have never heard of it, and never will.
Academic handbooks on multilingualism stretch to over a thousand pages, and there are countless journals devoted to the topic. Attempts have been made to condense the topic to 130 pages (Maher, 2017), and even 15 pages (Cenoz, 2015), but multilingualism is a discursive construct, a category in the process of continuous reinvention (Gramling, 2021). Discourses about monolingualism and multilingualism are what Deborah Cameron (2013) has called discourses of ‘verbal hygiene’ – the normative practices through which people attempt to improve languages or regulate their use. Such discourses, whether coming from xenophobes, neo-liberals, or those with more liberal perspectives, are:
linked to other preoccupations which are not primarily linguistic, but rather social, political and moral. The logic behind verbal hygiene depends on a tacit, common-sense analogy between the order of language and the larger social order; the rules or norms of language stand in for the rules governing social or moral conduct, and putting language to rights becomes a symbolic way of putting the world to rights (Cameron, 2013: 61).
Cameron adds that verbal hygiene is a response to the anxieties of a specific moment and place, and that we should be wary of assuming that preoccupations about, say, multilingualism and monolingualism will have the same symbolic meanings in different times and places. With that in mind, I know I need to be careful about the way I react to the writings of Li Wei, Ofelia García, Nelson Flores, or Guadalupe Valdés. Their professional worlds of the ‘multilingual turn’ in bilingual and immersion education in mostly English-speaking countries hardly intersect at all with my own professional world of EFL teaching in central Europe, where rejection of lingualism is not really an option.

References
Block, D. (2013) Moving beyond ‘Lingualism’: Multilingual embodiment and Multimodality in SLA. In May. S. (Ed.) (2013) The multilingual turn: Implications for SLA, TESOL and Bilingual education. New York: Routledge. pp. 54 – 77
Cameron, D. (2013) The one, the many, and the Other: Representing multi- and mono-lingualism in post-9/11 verbal hygiene. Critical Multilingualism Studies, 1 (2): 59 – 77
Cenoz, J. (2013) Defining multilingualism. Annual Review of Applied Linguistics, 33: 3 – 18
Conteh, J. & Meier, G. (Eds.) (2014) The multilingual turn in languages education: Opportunities and challenges. Bristol: Multilingual Matters
European Commission. (2007) Final report: High level group on multilingualism. Luxembourg: Office for Official Publications of the European Communities
European Commission (2005) Communication from the Commission to the Council, the European Parliament, the Economic and Social Committee, and the Committee of the Regions. A New Framework Strategy for Multilingualism, COM(2005) 596 final. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52005DC0596
Flores, N. (2013) The Unexamined Relationship Between Neoliberalism and Plurilingualism: A Cautionary Tale. TESOL Quarterly, 47 (3): 500- 520
Gramling, D. (2021) The Invention of Multilingualism. Cambridge: CUP
Gramling, D. (2016) The Invention of Monolingualism. New York: Bloomsbury
Hardach, S. (2018) Speaking more than one language can boost economic growth. https://www.weforum.org/agenda/2018/02/speaking-more-languages-boost-economic-growth/
Hardach, S. (2021) Languages are Good for Us. London: Apollo Books
Hogan-Brun, G. (2017) Linguanomics: What is the Market Potential of Multilingualism? New York: Bloomsbury
Katznelson, N. & Bernstein, K. (2017) Rebranding Bilingualism: The Shifting Discourses of Language Education Policy in California’s 2016 Election. Linguistics and Education, 40: 11 – 26
Li Wei. (2021) Translanguaging as a Political Stance: Implications for English Language Education. ELT Journal, ccab083, https://doi.org/10.1093/elt/ccab083
Li Wei. (2018) Translanguaging as a Practical Theory of Language. Applied Linguistics, 39 (1): 9 – 30
Maher, J. C. (2017) Multilingualism: A very short introduction. Oxford: OUP
May. S. (Ed.) (2013) The multilingual turn: Implications for SLA, TESOL and Bilingual education. New York: Routledge
McNamara, T. (2011) Multilingualism in Education: A poststructuralist critique. The Modern Language Journal, 104 (1): 430 – 441
Meier, G. S. (2017) The multilingual turn as a critical movement in education: assumptions, challenges and a need for reflection. Applied Linguistics Review, 8 (1): 131-161
Moore, R. (2015) From revolutionary monolingualism to reactionary multilingualism: Top-down discourses of linguistic diversity in Europe, 1794-present. Language & Communication, 44: 19 – 30
Stein-Smith, K. (2021a) Multilingualism as a Global Competency: Skills for a 21st Century World. Saarbrücken: LAP Lambert Publishing
Stein-Smith, K. (2021b) Multilingualism for Global Solutions and a Better World. Journal of Language Teaching and Research, 12 (5): 671-677