Posts Tagged ‘bots’

I came across this course description the other day. The course motto is ‘Honour the Learner’.

Discussions and assigned work covered in the curriculum includes multiple intelligence, positive deviance, brain science during stressful situations, how people learn, PBL, Failing Forward, Bloom’s Taxonomy, de-escalation, cognitive load and courageous conversations, with the interwoven golden threads of leadership theory and emotional intelligence.

I love the idea of positive deviance and the interwoven golden threads!

The description is of a coaching course for police professionals in Ontario. ‘The intense, week-long program follows a robust agenda that embraces a modified PBL-approach rather than a traditional, lecture-based format’. Participants write a personal mission statement and, in the process, they have ‘the opportunity to reflect on their own contributions and commitment to the effective, efficient and values-based delivery of policing’. As opposed to violence-based, for example.

The course began in 2017 and has been considered a success. But what sort of real impact has it had? And how has it adapted to going online? Is there anything people involved in language teaching can learn about coaching from the Ontario Police approach?

‘Coach’ (as in ‘life coach’) is, of course, a slightly tricky word. There are people who think it reflects an important reality in our lives, and others who struggle to take the word seriously. The former will write blog posts or give talks about coaching, the latter probably won’t read them.

The cause of coaching is not really helped by the lack of any broadly recognised certification. By people who think they can charge more just by claiming they are ‘coaches’. In the language teaching world, as elsewhere, some coaches are attempting to set up little trademarked enclaves, sprinkled with acronyms, pyramids and lightbulb illustrations, in order to differentiate just anyone who claims to be a coach from ‘proper coaches’ with certificates.

If you want to be certified, it’s not always easy to choose from the possibilities out there. I have recently read ‘Neurolanguage Coaching: Brain Friendly Language Learning’ by Rachel Paling. I’m normally very suspicious of anything with a ‘brain-friendly’ label. Worse still, I collocate ‘neuro’ more strongly with ‘bollox’ than with ‘language’. So it was an intriguing read. Without wanting to give too much away, I can tell you that it’s all to do with motivation (the limbic system, no less), being non-judgemental of the coachee, and breaking down language into manageable chunks: ‘from present tenses to future, to conditional etc.’ The key, continues the author, ‘is to start with grammar that gets the learner speaking the fastest. In English this would necessarily be the verbs ‘to be’, ‘to have’ and the impersonal ‘there is’ and ‘there are’, and the formulation of questions and negatives of these. Then it would be a step-by-step building the language: introducing present continuous as the real present and the present simple as the facts and habits tense’. (Paling, 2017: 83) And, hey pesto, it’s as simple as that, when you’ve mastered the necessary skills. To get a firmer understanding of this trademarked approach to language coaching, you’d probably have to follow one of the many courses that are certified by Efficient Language Coaching® (online, prices on request).

The International Language Coaching Association (https://internationallanguagecoaching.com/) would seem to be a competitor to Neurolanguage Coaching®. They, too, run courses: $450 for the Foundation Course, but the price includes ‘12 month membership in the pioneering ILCA community’. Rather a lot for 4 live sessions and 4 supplementary study videos. I suppose if you were really keen, you could do both. But times are tight, and instead of splashing out, I invested in ‘Coaching for Language Learning’ by Emmanuelle Betham, another self-published book (only $18.73 on Kindle). The author’s skills, according to LinkedIn, include, besides life coaching, Neuro Linguistic Programming, Mindfulness, and Clean Language. Again, I was intrigued.

As with ‘Neurolanguage Coaching’, there were quite a few slogans in ‘Coaching for Language Learning (CFLL)’, not a lot of awareness of SLA research (the work of Krashen seems to be the limit of the reading informing the CFLL approach), and a crude stereotyping of teachers and trainers as ‘informative’, and coaches as ‘transformative’. But, unlike Rachel Paling, Emmanuelle Betham seems to think that grammar instruction (even when delivered through coaching questions) is less helpful. Instead, learners need to learn to think in English, and the best way of doing that is by having mindful conversations with their coach. Nevertheless, there is a section on ‘coaching grammar rules’. Some standard teaching activities are also recommended. Running dictations can be used. The English language is not melodious like Roman languages. If you’re struggling to make sense of all this, you’re not alone. CFLL, you see, is ‘a new paradigm that needs to be appreciated in practice, as defined in its context, and which cannot be comprehended within the wisdom of previous hypotheses’ (Betham, 2018 – 2020: 45). What’s more, CFLL is primarily interested in ‘what works’: the concepts in the book ‘are not to be agreed or disagreed with, they are just examples of visualizations that have worked well for some learners in practice before’ (Betham, 34). You see, ‘truth is relative […] the rationale for our new paradigm, CFLL rests on the assumption that we are free to interpret and construct our own truth’ (Betham, 35). It’s all heady stuff.

Coming down to ground, the most useful thing I’ve read about language teaching and coaching is ‘From English Teacher to Learner Coach’ by Daniel Barber and Duncan Foord (2014). If coaching is ultimately about helping people to become more autonomous … in combination with education, it’s all about learner autonomy. At least, that was the message I took from this book. It’s very cheap, and it also comes in a ‘Student’s Book’ version, which is very handy if you want your students to try out a pile of suggestions for becoming more autonomous learners. I thought the suggestions were good and plentiful, but it all seemed to be more about learner autonomy than about language coaching. Perhaps it’s not unreasonable to claim they are the same thing?

But could AI do away with real-life coaches altogether? I’m very interested in the idea of coaching bots. How easy / hard would it be to fool people that they were chatting with a real-life coach, rather than an algorithm? It wouldn’t be too hard to load up a corpus of coaching conversational strategies, hedges and questions and automate a linkage between key words produced by the coachee (e.g. stress, frustration, work, COVID, resisting arrest) and a range of conversation prompts. Computers are getting better and better at doing empathy. How long before a coachbot passes the Turing test? Maybe this is what the Ontario Police are toying with?

There are, of course, plenty of coaching apps out there. Things like HabitBull, Coach.me, Symbifly, Mindsail … Mostly for sport, health and getting rich. They’re cheaper than paying for a coach, but the bonding experience is a bit different. Would they work with language learners or teachers? Somehow, I doubt it, but you never know. Do gamification and coaching fit together?

I’m not sure what I was hoping to learn from my exploration of coaching. I’m not sure what questions I was looking for answers to. Perhaps I needed a coach to guide me? But I have learned from Emmanuelle Betham that learning is a seed and I am a gardener. Or something like that.

Barber, D. & Foord, D. (2014) From English Teacher to Learner Coach.

Betham, E. (2018 – 2020) An Introduction to Coaching for Language Learning.

Paling, R. (2017) Neurolanguage Coaching: Brain Friendly Language Learning.

Chatbots

Posted: December 1, 2016 in ed tech
Tags: , , , , , , , ,

 

Here’s a conversation I had recently with Cleverbot.

cleverbot

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

Cleverbot: Are you talking to yourself?

User: No, I’m asking you a question.

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

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

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

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

Cleverbot: What is your question?

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

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

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

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

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

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

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

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

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

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

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

 

 

About two and a half years ago when I started writing this blog, there was a lot of hype around adaptive learning and the big data which might drive it. Two and a half years are a long time in technology. A look at Google Trends suggests that interest in adaptive learning has been pretty static for the last couple of years. It’s interesting to note that 3 of the 7 lettered points on this graph are Knewton-related media events (including the most recent, A, which is Knewton’s latest deal with Hachette) and 2 of them concern McGraw-Hill. It would be interesting to know whether these companies follow both parts of Simon Cowell’s dictum of ‘Create the hype, but don’t ever believe it’.

Google_trends

A look at the Hype Cycle (see here for Wikipedia’s entry on the topic and for criticism of the hype of Hype Cycles) of the IT research and advisory firm, Gartner, indicates that both big data and adaptive learning have now slid into the ‘trough of disillusionment’, which means that the market has started to mature, becoming more realistic about how useful the technologies can be for organizations.

A few years ago, the Gates Foundation, one of the leading cheerleaders and financial promoters of adaptive learning, launched its Adaptive Learning Market Acceleration Program (ALMAP) to ‘advance evidence-based understanding of how adaptive learning technologies could improve opportunities for low-income adults to learn and to complete postsecondary credentials’. It’s striking that the program’s aims referred to how such technologies could lead to learning gains, not whether they would. Now, though, with the publication of a report commissioned by the Gates Foundation to analyze the data coming out of the ALMAP Program, things are looking less rosy. The report is inconclusive. There is no firm evidence that adaptive learning systems are leading to better course grades or course completion. ‘The ultimate goal – better student outcomes at lower cost – remains elusive’, the report concludes. Rahim Rajan, a senior program office for Gates, is clear: ‘There is no magical silver bullet here.’

The same conclusion is being reached elsewhere. A report for the National Education Policy Center (in Boulder, Colorado) concludes: Personalized Instruction, in all its many forms, does not seem to be the transformational technology that is needed, however. After more than 30 years, Personalized Instruction is still producing incremental change. The outcomes of large-scale studies and meta-analyses, to the extent they tell us anything useful at all, show mixed results ranging from modest impacts to no impact. Additionally, one must remember that the modest impacts we see in these meta-analyses are coming from blended instruction, which raises the cost of education rather than reducing it (Enyedy, 2014: 15 -see reference at the foot of this post). In the same vein, a recent academic study by Meg Coffin Murray and Jorge Pérez (2015, ‘Informing and Performing: A Study Comparing Adaptive Learning to Traditional Learning’) found that ‘adaptive learning systems have negligible impact on learning outcomes’.

future-ready-learning-reimagining-the-role-of-technology-in-education-1-638In the latest educational technology plan from the U.S. Department of Education (‘Future Ready Learning: Reimagining the Role of Technology in Education’, 2016) the only mentions of the word ‘adaptive’ are in the context of testing. And the latest OECD report on ‘Students, Computers and Learning: Making the Connection’ (2015), finds, more generally, that information and communication technologies, when they are used in the classroom, have, at best, a mixed impact on student performance.

There is, however, too much money at stake for the earlier hype to disappear completely. Sponsored cheerleading for adaptive systems continues to find its way into blogs and national magazines and newspapers. EdSurge, for example, recently published a report called ‘Decoding Adaptive’ (2016), sponsored by Pearson, that continues to wave the flag. Enthusiastic anecdotes take the place of evidence, but, for all that, it’s a useful read.

In the world of ELT, there are plenty of sales people who want new products which they can call ‘adaptive’ (and gamified, too, please). But it’s striking that three years after I started following the hype, such products are rather thin on the ground. Pearson was the first of the big names in ELT to do a deal with Knewton, and invested heavily in the company. Their relationship remains close. But, to the best of my knowledge, the only truly adaptive ELT product that Pearson offers is the PTE test.

Macmillan signed a contract with Knewton in May 2013 ‘to provide personalized grammar and vocabulary lessons, exam reviews, and supplementary materials for each student’. In December of that year, they talked up their new ‘big tree online learning platform’: ‘Look out for the Big Tree logo over the coming year for more information as to how we are using our partnership with Knewton to move forward in the Language Learning division and create content that is tailored to students’ needs and reactive to their progress.’ I’ve been looking out, but it’s all gone rather quiet on the adaptive / platform front.

In September 2013, it was the turn of Cambridge to sign a deal with Knewton ‘to create personalized learning experiences in its industry-leading ELT digital products for students worldwide’. This year saw the launch of a major new CUP series, ‘Empower’. It has an online workbook with personalized extra practice, but there’s nothing (yet) that anyone would call adaptive. More recently, Cambridge has launched the online version of the 2nd edition of Touchstone. Nothing adaptive there, either.

Earlier this year, Cambridge published The Cambridge Guide to Blended Learning for Language Teaching, edited by Mike McCarthy. It contains a chapter by M.O.Z. San Pedro and R. Baker on ‘Adaptive Learning’. It’s an enthusiastic account of the potential of adaptive learning, but it doesn’t contain a single reference to language learning or ELT!

So, what’s going on? Skepticism is becoming the order of the day. The early hype of people like Knewton’s Jose Ferreira is now understood for what it was. Companies like Macmillan got their fingers badly burnt when they barked up the wrong tree with their ‘Big Tree’ platform.

Noel Enyedy captures a more contemporary understanding when he writes: Personalized Instruction is based on the metaphor of personal desktop computers—the technology of the 80s and 90s. Today’s technology is not just personal but mobile, social, and networked. The flexibility and social nature of how technology infuses other aspects of our lives is not captured by the model of Personalized Instruction, which focuses on the isolated individual’s personal path to a fixed end-point. To truly harness the power of modern technology, we need a new vision for educational technology (Enyedy, 2014: 16).

Adaptive solutions aren’t going away, but there is now a much better understanding of what sorts of problems might have adaptive solutions. Testing is certainly one. As the educational technology plan from the U.S. Department of Education (‘Future Ready Learning: Re-imagining the Role of Technology in Education’, 2016) puts it: Computer adaptive testing, which uses algorithms to adjust the difficulty of questions throughout an assessment on the basis of a student’s responses, has facilitated the ability of assessments to estimate accurately what students know and can do across the curriculum in a shorter testing session than would otherwise be necessary. In ELT, Pearson and EF have adaptive tests that have been well researched and designed.

Vocabulary apps which deploy adaptive technology continue to become more sophisticated, although empirical research is lacking. Automated writing tutors with adaptive corrective feedback are also developing fast, and I’ll be writing a post about these soon. Similarly, as speech recognition software improves, we can expect to see better and better automated adaptive pronunciation tutors. But going beyond such applications, there are bigger questions to ask, and answers to these will impact on whatever direction adaptive technologies take. Large platforms (LMSs), with or without adaptive software, are already beginning to look rather dated. Will they be replaced by integrated apps, or are apps themselves going to be replaced by bots (currently riding high in the Hype Cycle)? In language learning and teaching, the future of bots is likely to be shaped by developments in natural language processing (another topic about which I’ll be blogging soon). Nobody really has a clue where the next two and a half years will take us (if anywhere), but it’s becoming increasingly likely that adaptive learning will be only one very small part of it.

 

Enyedy, N. 2014. Personalized Instruction: New Interest, Old Rhetoric, Limited Results, and the Need for a New Direction for Computer-Mediated Learning. Boulder, CO: National Education Policy Center. Retrieved 17.07.16 from http://nepc.colorado.edu/publication/personalized-instruction