Pedagogy before technology, OK?

Unconditional calls for language teachers to incorporate digital technology into their teaching are common. The reasons that are given are many and typically include the fact that (1) our students are ‘digital natives’ and expect technology to be integrated into their learning, (2) and digital technology is ubiquitous and has so many affordances for learning. Writing on the topic is almost invariably enthusiastic and the general conclusion is that the integration of technology is necessary and essential. Here’s a fairly typical example: digital technology is ‘an essential multisensory extension to the textbook’ (Torben Schmidt and Thomas Strasser in Surkamp & Viebrock, 2018: 221).

 

Teachers who are reluctant or fail to embrace technology are often ‘characterised as technophobic, or too traditional in their teaching style, or reluctant to adopt change’ (Watson, 2001: 253). (It’s those pesky teachers again.)

Claims for the importance of digital technology are often backed up by vague references to research. Michael Carrier, for example, in his introductory chapter to ‘Digital Language Learning and Teaching’ (Carrier et al. 2017: 3) writes that ‘research results […] seem to show conclusively that the use of educational technology adds certain degrees of richness to the learning and teaching process […] at the very least, digital learning seems to provide enhanced motivation for learners’.

Unfortunately, this is simply not true. Neither in language learning / teaching, nor in education more generally, is there any clear evidence of the necessary benefits of introducing educational technology. In the broader context, the ‘PISA analysis of the impact of Information Communication Technology (ICT) on reading, mathematics, and science (OECD, 2015: 3) in countries heavily invested in educational technology showed mixed effects and “no appreciable improvements”’ (Herodotou et al., 2019). Educational technology can or might  ‘add certain degrees of richness’ or ‘provide enhanced motivation’, but that is not the same as saying that it does or will. The shift from can to will, a piece of modal legerdemain used to advocate for educational technology, is neatly illustrated in a quote from the MIT’s Office of Digital Learning, whose remit is to improve learning and teaching across the university via digital learning: ‘Digital Learning technologies can enable students to grasp concepts more quickly [etc….] Digital technologies will enable this in new and better ways and create possibilities beyond the limits of our current imagination’ (quoted by Carrier, 2017: 1).

Before moving on, here’s another example. The introduction to Li Li’s ‘New Technologies and Language Learning’ (Li, 2017: x) states, with a cautious can, that one of the objectives of the book is ‘to provide examples of how technologies can be used in assisting language education’. In the next paragraph, however, caution is thrown to the wind and we are told, unequivocally, that ‘technology is beneficial for language learning’.

Pedagogy before technology

Examples of gratuitous technology use are not hard to find. Mark Warschauer (who, as the founding director of the Digital Learning Lab at the University of California, Irvine, could be fairly described as an edtech enthusiast) describes one example: ‘I remember observing a beginners’ French class a number of years ago, the teacher bragged about how engaged the learners were in creating multimedia in French. However, the students were spending most of their time and energy talking with each other in English about how to make PowerPoints, when, as beginning learners, they really needed to be spending time hearing as much French as possible’ (quoted in the Guardian, May 2014).

As a result, no doubt, of having similar experiences, it seems that many people are becoming a little more circumspect in their enthusiasm for edtech. In the same Guardian article as Warschauer’s recollections, Russell Stannard ‘says the trick is to put the pedagogy first, not the technology. “You’ve got to know why you’re using it. Teachers do need to learn to use new technology, but the driving force should always be the pedagogy behind it’. Nicky Hockly, Gavin Dudeney and Mark Pegrum (Hockly et al., 2013: 45) concur: ‘Content and pedagogy come before technology. We must decide on our content and pedagogical aims before determining whether our students should use pens or keyboards, write essays or blogs, or design posters or videos’. And Graham Stanley (2013: 1) in the introduction to his ‘Language Learning With Technology’ states that his ‘book makes a point of putting pedagogy at the forefront of the lesson, which is why content has been organised around specific learning content goals rather than specific technologies’.

But, Axel Krommer, of the Friedrich-Alexander University of Erlangen-Nürnberg, has argued that the principle of ‘pedagogy before technology’ is ‘trivial at best’. In a piece for the Goethe Institute he writes ‘a theory with which everyone agrees and whose opposite no-one believes true is meaningless’, although he adds that it may be useful as ‘an admonitory wake-up call when educational institutions risk being blinded by technological possibilities that cause them to neglect pedagogical principles that should really be taken for granted’. It was this piece that set me thinking more about ‘pedagogy before technology’.

Pedagogy before technology (on condition that there is technology)

Another person to lament the placing of technology before pedagogy is Nik Peachey. In an opinion piece for the Guardian, entitled ‘Technology can sometimes be wasted on English language teaching’, he complains about how teachers are left to sort out how to use technology ‘in a pedagogically effective way, often with very little training or support’. He appears to take it as given that technology is a positive force, and argues that it shouldn’t be wasted. The issue, he says, is that better teacher training is needed so that teachers’ ‘digital literacies’ are improved and to ensure that technological potential is fulfilled.

His position, therefore, cannot really be said to be one of ‘pedagogy before technology’. Like the other writers mentioned above, he comes to the pedagogy through and after an interest in the technology. The educational use of digital technology per se is never seriously questioned. The same holds true for almost the entirety of the world of CALL research.

A Canadian conference ‘Pedagogy b4 Technology’ illustrates my point beautifully.

There are occasional exceptions. A recent example which I found interesting was an article by Herodotou et al (2019), in which the authors take as their starting point a set of OECD educational goals (quality of life, including health, civic engagement, social connections, education, security, life satisfaction and the environment), and then investigate the extent to which a variety of learning approaches (formative analytics, teachback, place-based learning, learning with robots, learning with drones, citizen inquiry) – not all of which involve technology – might contribute to the realisation of these goals.

Technology before pedagogy as policy

Some of the high school English teachers I work with have to use tablets in one lesson a week. Some welcome it, some accept it (they can catch up with other duties while the kids are busy with exercises on the tablet), others just roll their eyes at the mention of this policy. In the same school system, English language learning materials can only be bought if they come in digital versions (even if it is the paper versions that are actually used). The digital versions are mostly used for projecting pages onto the IWBs. Meanwhile, budgets and the time available for in-service training have been cut.

Elsewhere, a chain of universities decides that a certain proportion of all courses must be taught online. English language courses, being less prestigious than major subjects, are one of the first to be migrated to platforms. The staff, few of whom have tenure or time to spare, cope as best as they can, with some support from a department head. Training is provided in the mechanics of operating the platform, and, hopefully before too long, more training will become available to optimize the use of the platform for pedagogical purposes. An adequate budget has yet to be agreed.

The reasons why so many educational authorities introduce such policies are, at best, only superficially related to pedagogy. There is a belief, widely held, that technology cannot fail to make things better. In the words of Tony Blair: ‘Technology has revolutionised the way we work and is now set to transform education. Children cannot be effective in tomorrow’s world if they are trained in yesterday’s skills’. But there is also the potential of education technology to scale education up (i.e. increase student numbers), to reduce long-term costs, to facilitate accountability, to increase productivity, to restrict the power of teachers (and their unions), and so on.

In such circumstances, which are not uncommon, it seems to me that there are more pressing things to worry about than teachers who are not sufficiently thinking about the pedagogical uses to which they put the technology that they have to use. Working conditions, pay and hours, are all affected by the digitalisation of education. These things do get talked about (see, for example, Walsh, 2019), but only rarely.

Technology as pedagogy

Blended learning, described by Pete Sharma in 2010 as a ‘buzz word’ in ELT, remains a popular pedagogical approach. In a recent article (2019), he enthuses about the possibilities of blended learning, suggesting that teachers should use it all the time: ‘teaching in this new digital age should use the technologies which students meet in their everyday lives, such as the Internet, laptop, smartphone and tablet’. It’s also, he claims, time-efficient, but other pedagogical justifications are scant: ‘some language areas are really suited to be studied outside the classroom. Extensive reading and practising difficult phonemes, for instance’.

Blended learning and digital technology are inseparable. Hockley (2018) explains the spread of blended learning in ELT as being driven primarily by ‘the twin drivers of economics (i.e. lower costs) and increasingly accessible and affordable hardware and software’. It might be nice to believe that ‘it is pedagogy, rather than technology, that should underpin the design of blended learning programmes’ (McCarthy, 2016, back cover), but the technology is the pedagogy here. Precisely how it is used is almost inevitably an afterthought.

Which pedagogy, anyway?

We can talk about putting pedagogy before technology, but this raises the question of which particular pedagogy we want to put in the driving seat. Presumably not all pedagogies are of equal value.

One of the most common uses of digital technology that has been designed specifically for language learning is the IWB- or platform-delivered coursebook and its accompanying digital workbook. We know that a majority of teachers using online coursebook packages direct their students more readily to tasks with clear right / wrong answers (e.g. drag-and-drop or gap-fill grammar exercises) than they do to the forum facilities where communicative language use is possible. Here, technology is merely replicating and, perhaps (because of its ease of use), encouraging established pedagogical practices. The pedagogy precedes the technology, but it’s probably not the best pedagogy in the world. Nor does it make best use of the technology’s potential. Would the affordances of the technology make a better starting point for course design?

Graham Stanley’s book (2013) offers suggestions for using technology for a variety of purposes, ranging from deliberate practice of grammar and vocabulary to ways of facilitating opportunities for skills practice. It’s an eclectic mix, similar to the range of activities on offer in the average coursebook for adults or teenagers. It is pedagogy-neutral in the sense that it does not offer a set of principles of language learning or teaching, and from these derive a set of practices for using the technology. It is a recipe book for using technological tools and, like all recipe books, prioritises activities over principles. I like the book and I don’t intend these comments as criticism. My point is simply that it’s not easy to take pedagogical principles as a starting point. Does the world of ELT even have generally agreed pedagogical principles?

And what is it that we’re teaching?

One final thought … If we consider how learners are likely to be using the English they are learning in their real-world futures, technology will not be far away: reading online, listening to / watching online material, writing and speaking with messaging apps, writing with text, email or Google Docs … If, in designing pedagogical approaches, we wish to include features of authentic language use, it’s hard to see how we can avoid placing technology fairly near the centre of the stage. Technologically-mediated language use is inseparable from pedagogy: one does not precede the other.

Similarly, if we believe that it is part of the English teacher’s job to develop the digital literacy (e.g. Hockly et al., 2013), visual literacy (e.g. Donaghy, 2015) or multimodal literacy of their students – not, incidentally, a belief that I share – then, again, technology cannot be separated from pedagogy.

Pedagogy before technology, OK??

So, I ask myself what precisely it is that people mean when they say that pedagogy should come before technology. The locutionary force, or referential meaning, usually remains unclear: in the absence of a particular pedagogy and particular contexts, what exactly is being said? The illocutionary force, likewise, is difficult to understand in the absence of a particular addressee: is the message only intended for teachers suffering from Everest Syndrome? And the perlocutionary force is equally intriguing: how are people who make the statement positioning themselves, and in relation to which addressee? Along the lines of green-washing and woke-washing, are we sometimes seeing cases of pedagogy-washing?

REFERENCES

Carrier, M., Damerow, R. M. & Bailey, K. M. (2017) Digital Language Learning and Teaching: Research, theory, and practice. New York: Routledge

Donaghy, K. (2015) Film in Action. Peaslake, Surrey: DELTA Publishing

Herodotou, C., Sharples, M., Gaved, M., Kukulska-Hulme, A., Rienties, B., Scanlon, E. & Whitelock, D. (2019) Innovative Pedagogies of the Future: An Evidence-Based Selection. Frontiers in Education, 4 (113)

Hockly, N. (2018) Blended Learning. ELT Journal 72 (1): pp. 97 – 101

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

Li, L. (2017) New Technologies and Language Learning. London: Palgrave

McCarthy, M. (Ed.) (2016) The Cambridge Guide to Blended Learning for Language Teaching. Cambridge: Cambridge University Press

OECD (2015) Students, Computers and Learning: Making the Connection, PISA. Paris: OECD Publishing

Sharma, P. (2010) Blended Learning. ELT Journal, 64 (4): pp. 456 – 458

Sharma, P. (2019) The Complete Guide to Running a Blended Learning Course. Oxford University Press English Language Teaching Global Blog 17 October 2019. Available at: https://oupeltglobalblog.com/2019/10/17/complete-guidagogyde-blended-learning/

Stanley, G. (2013) Language Learning with Technology. Cambridge: Cambridge University Press

Surkamp, C. & Viebrock, B. (Eds.) (2018) Teaching English as a Foreign Language: An Introduction. Stuttgart: J. B. Metzler

Walsh, P. (2019) Precarity. ELT Journal, 73 (4): pp. 459–462

Watson, D. M. (2001) Pedagogy before Technology: Re-thinking the Relationship between ICT and Teaching. Education and Information Technologies 6:4: pp.251–26

The Unlearned Lessons of Programmed Learning

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

A brief description

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

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

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

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

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

Enthusiasm and uptake

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

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

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

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

Lessons to be learned

1 Shaping attitudes

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

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

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

2 Returns on investment

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

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

3 Research and theory

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

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

4 Content

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

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

5 Motivation

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

The unlearned lessons

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

References

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

 

 

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

 

 

 

 

 

More research needed: part 2

In my last post, I looked at shortcomings in edtech research, mostly from outside the world of ELT. I made a series of recommendations of ways in which such research could become more useful. In this post, I look at two very recent collections of ELT edtech research. The first of these is Digital Innovations and Research in Language Learning, edited by Mavridi and Saumell, and published this February by the Learning Technologies SIG of IATEFL. I’ll refer to it here as DIRLL. It’s available free to IATEFL LT SIG members, and can be bought for $10.97 as an ebook on Amazon (US). The second is the most recent edition (February 2020) of the Language Learning & Technology journal, which is open access and available here. I’ll refer to it here as LLTJ.

In both of these collections, the focus is not on ‘technology per se, but rather issues related to language learning and language teaching, and how they are affected or enhanced by the use of digital technologies’. However, they are very different kinds of publication. Nobody involved in the production of DIRLL got paid in any way (to the best of my knowledge) and, in keeping with its provenance from a teachers’ association, has ‘a focus on the practitioner as teacher-researcher’. Almost all of the contributing authors are university-based, but they are typically involved more in language teaching than in research. With one exception (a grant from the EU), their work was unfunded.

The triannual LLTJ is funded by two American universities and published by the University of Hawaii Press. The editors and associate editors are well-known scholars in their fields. The journal’s impact factor is high, close to the impact factor of the paywalled reCALL (published by the University of Cambridge), which is the highest-ranking journal in the field of CALL. The contributing authors are all university-based, many with a string of published articles (in prestige journals), chapters or books behind them. At least six of the studies were funded by national grant-awarding bodies.

I should begin by making clear that there was much in both collections that I found interesting. However, it was not usually the research itself that I found informative, but the literature review that preceded it. Two of the chapters in DIRLL were not really research, anyway. One was the development of a template for evaluating ICT-mediated tasks in CLIL, another was an advocacy of comics as a resource for language teaching. Both of these were new, useful and interesting to me. LLTJ included a valuable literature review of research into VR in FL learning (but no actual new research). With some exceptions in both collections, though, I felt that I would have been better off curtailing my reading after the reviews. Admittedly, there wouldn’t be much in the way of literature reviews if there were no previous research to report …

It was no surprise to see the learners who were the subjects of this research were overwhelmingly university students. In fact, only one article (about a high-school project in Israel, reported in DIRLL) was not about university students. The research areas focused on reflected this bias towards tertiary contexts: online academic reading skills, academic writing, online reflective practices in teacher training programmes, etc.

In a couple of cases, the selection of experimental subjects seemed plain bizarre. Why, if you want to find out about the extent to which Moodle use can help EAP students become better academic readers (in DIRLL), would you investigate this with a small volunteer cohort of postgraduate students of linguistics, with previous experience of using Moodle and experience of teaching? Is a less representative sample imaginable? Why, if you want to investigate the learning potential of the English File Pronunciation app (reported in LLTJ), which is clearly most appropriate for A1 – B1 levels, would you do this with a group of C1-level undergraduates following a course in phonetics as part of an English Studies programme?

More problematic, in my view, was the small sample size in many of the research projects. The Israeli virtual high school project (DIRLL), previously referred to, started out with only 11 students, but 7 dropped out, primarily, it seems, because of institutional incompetence: ‘the project was probably doomed […] to failure from the start’, according to the author. Interesting as this was as an account of how not to set up a project of this kind, it is simply impossible to draw any conclusions from 4 students about the potential of a VLE for ‘interaction, focus and self-paced learning’. The questionnaire investigating experience of and attitudes towards VR (in DIRLL) was completed by only 7 (out of 36 possible) students and 7 (out of 70+ possible) teachers. As the author acknowledges, ‘no great claims can be made’, but then goes on to note the generally ‘positive attitudes to VR’. Perhaps those who did not volunteer had different attitudes? We will never know. The study of motivational videos in tertiary education (DIRLL) started off with 15 subjects, but 5 did not complete the necessary tasks. The research into L1 use in videoconferencing (LLTJ) started off with 10 experimental subjects, all with the same L1 and similar cultural backgrounds, but there was no data available from 4 of them (because they never switched into L1). The author claims that the paper demonstrates ‘how L1 is used by language learners in videoconferencing as a social semiotic resource to support social presence’ – something which, after reading the literature review, we already knew. But the paper also demonstrates quite clearly how L1 is not used by language learners in videoconferencing as a social semiotic resource to support social presence. In all these cases, it is the participants who did not complete or the potential participants who did not want to take part that have the greatest interest for me.

Unsurprisingly, the LLTJ articles had larger sample sizes than those in DIRLL, but in both collections the length of the research was limited. The production of one motivational video (DIRLL) does not really allow us to draw any conclusions about the development of students’ critical thinking skills. Two four-week interventions do not really seem long enough to me to discover anything about learner autonomy and Moodle (DIRLL). An experiment looking at different feedback modes needs more than two written assignments to reach any conclusions about student preferences (LLTJ).

More research might well be needed to compensate for the short-term projects with small sample sizes, but I’m not convinced that this is always the case. Lacking sufficient information about the content of the technologically-mediated tools being used, I was often unable to reach any conclusions. A gamified Twitter environment was developed in one project (DIRLL), using principles derived from contemporary literature on gamification. The authors concluded that the game design ‘failed to generate interaction among students’, but without knowing a lot more about the specific details of the activity, it is impossible to say whether the problem was the principles or the particular instantiation of those principles. Another project, looking at the development of pronunciation materials for online learning (LLTJ), came to the conclusion that online pronunciation training was helpful – better than none at all. Claims are then made about the value of the method used (called ‘innovative Cued Pronunciation Readings’), but this is not compared to any other method / materials, and only a very small selection of these materials are illustrated. Basically, the reader of this research has no choice but to take things on trust. The study looking at the use of Alexa to help listening comprehension and speaking fluency (LLTJ) cannot really tell us anything about IPAs unless we know more about the particular way that Alexa is being used. Here, it seems that the students were using Alexa in an interactive storytelling exercise, but so little information is given about the exercise itself that I didn’t actually learn anything at all. The author’s own conclusion is that the results, such as they are, need to be treated with caution. Nevertheless, he adds ‘the current study illustrates that IPAs may have some value to foreign language learners’.

This brings me onto my final gripe. To be told that IPAs like Alexa may have some value to foreign language learners is to be told something that I already know. This wasn’t the only time this happened during my reading of these collections. I appreciate that research cannot always tell us something new and interesting, but a little more often would be nice. I ‘learnt’ that goal-setting plays an important role in motivation and that gamification can boost short-term motivation. I ‘learnt’ that reflective journals can take a long time for teachers to look at, and that reflective video journals are also very time-consuming. I ‘learnt’ that peer feedback can be very useful. I ‘learnt’ from two papers that intercultural difficulties may be exacerbated by online communication. I ‘learnt’ that text-to-speech software is pretty good these days. I ‘learnt’ that multimodal literacy can, most frequently, be divided up into visual and auditory forms.

With the exception of a piece about online safety issues (DIRLL), I did not once encounter anything which hinted that there may be problems in using technology. No mention of the use to which student data might be put. No mention of the costs involved (except for the observation that many students would not be happy to spend money on the English File Pronunciation app) or the cost-effectiveness of digital ‘solutions’. No consideration of the institutional (or other) pressures (or the reasons behind them) that may be applied to encourage teachers to ‘leverage’ edtech. No suggestion that a zero-tech option might actually be preferable. In both collections, the language used is invariably positive, or, at least, technology is associated with positive things: uncovering the possibilities, promoting autonomy, etc. Even if the focus of these publications is not on technology per se (although I think this claim doesn’t really stand up to close examination), it’s a little disingenuous to claim (as LLTJ does) that the interest is in how language learning and language teaching is ‘affected or enhanced by the use of digital technologies’. The reality is that the overwhelming interest is in potential enhancements, not potential negative effects.

I have deliberately not mentioned any names in referring to the articles I have discussed. I would, though, like to take my hat off to the editors of DIRLL, Sophia Mavridi and Vicky Saumell, for attempting to do something a little different. I think that Alicia Artusi and Graham Stanley’s article (DIRLL) about CPD for ‘remote’ teachers was very good and should interest the huge number of teachers working online. Chryssa Themelis and Julie-Ann Sime have kindled my interest in the potential of comics as a learning resource (DIRLL). Yu-Ju Lan’s article about VR (LLTJ) is surely the most up-to-date, go-to article on this topic. There were other pieces, or parts of pieces, that I liked, too. But, to me, it’s clear that ‘more research is needed’ … much less than (1) better and more critical research, and (2) more digestible summaries of research.

More research needed

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

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

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

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

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

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

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

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

2 Adopt a sceptical attitude from the outset

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

3 Know what you are measuring

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

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

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

5 Privilege longitudinal studies over short-term projects

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

6 Don’t forget the content

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

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

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

8 Enough already of higher education contexts

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

9 Be critical

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

More research?

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

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

References

Bates, A. W. (2019). Teaching in a Digital Age Second Edition. Vancouver, B.C.: Tony Bates Associates Ltd. Retrieved from https://pressbooks.bccampus.ca/teachinginadigitalagev2/

ICF Consulting Services Ltd (2015). Literature Review on the Impact of Digital Technology on Learning and Teaching. Edinburgh: The Scottish Government. https://dera.ioe.ac.uk/24843/1/00489224.pdf

Lai, J.W.M. & Bower, M. (2019). How is the use of technology in education evaluated? A systematic review. Computers & Education, 133(1), 27-42. Elsevier Ltd. Retrieved January 14, 2020 from https://www.learntechlib.org/p/207137/

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

Lillejord S., Børte K., Nesje K. & Ruud E. (2018). Learning and teaching with technology in higher education – a systematic review. Oslo: Knowledge Centre for Education https://www.forskningsradet.no/siteassets/publikasjoner/1254035532334.pdf

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

Lynch, J. (2017). How AI Will Destroy Education. Medium, November 13, 2017. https://buzzrobot.com/how-ai-will-destroy-education-20053b7b88a6

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

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

Sosa Neira, E. A., Salinas, J. and de Benito Crosetti, B. (2017). Emerging Technologies (ETs) in Education: A Systematic Review of the Literature Published between 2006 and 2016. International Journal of Emerging Technologies in Education, 12 (5). https://online-journals.org/index.php/i-jet/article/view/6939

Winkler, R. & Söllner, M. (2018): Unleashing the Potential of Chatbots in Education: A State-Of-The-Art Analysis. In: Academy of Management Annual Meeting (AOM). Chicago, USA. https://www.alexandria.unisg.ch/254848/1/JML_699.pdf

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