I’ve been reading a bit about the hype cycle lately as I’ve been putting together my literature review for my dissertation. And since my research is all about the ‘hype’ and the ‘hyper’ of language learning and teaching with technology (in the middle-school context) it seems only fitting to have a look at the hype of the hype cycle.
The hype cycle is attributed to Gartner Technologies who now annually produce a hype cycle of trends in technology, social media, and so on. It’s been used in a variety of ways and the book Mastering the hype cycle: How to choose the right innovation at the right time by J. Fenn and M. Raskino is well worth a read. From the book:
As she wrote research reports about specific technologies, Jackie [a Gartner employee] realised that there was a common pattern that most, if not all, of them shared. Again and again, she saw a rapid initial rush of enthusiasm for a technology’s potential followed over time by a deeper understanding of what the technology could really achieve. She drew a graph showing the ups and downs of this recurring cycle, gave each stage a catchy name (“Peak of Inflated Expectations,” “Trough of Disillusionment,” and so on), and populated it with example technologies. In the two-page research report showing this graph, she added some advice for clients about how to make decisions at each stage, depending on how much risk they wanted to take. Her report appeared in January 1995, with the title “When to Leap on the Hype Cycle” (p. xiii).
The Gartner authors recognise and acknowledge that the hype cycle is nothing particularly new: many of the underlying phenomena reflected in the hype cycle have been observed, analyzed, applied and rediscovered over many years by many different researchers, academics, and practitioners (Fenn & Raskino, 2008, p. xiv). They recognise the work of Nikolai Kondratiev on economic prosperity and depression; Joseph Schumpeter’s cycles of “creative destruction;” Everett Rodgers’ analysis of how ideas spread (his famous categorisation of populations into “innovators,” “early adopters,” “early majority,” “late majority,” and “laggards”); and Geoffrey Moore’s identification of a “chasm” between early adoption and mainstream adoption of many technologies and new ideas.
The hype cycle’s particular contribution is in highlighting the challenge of adopting an innovation during the early stages of the innovation’s life cycle. The hype cycle is also, we believe the only model of its type that has moved beyond an abstract concept and been used in earnest as a working management decision tool, tracking thousands of innovations over more than a decade. It’s a simple and highly visual way to represent the cycle of overenthusiasm, dashed expectations, and eventual maturity. But it’s more than descriptive – it’s also predictive… (Fenn & Raskino, 2008, p. xv)
The hype cycle for emerging technologies in 2008, when I conducted my fieldwork, looked like this:
Of course, this has had me thinking of parallels in educational technologies and language learning. It’s easy to think of examples of new technologies that have gone through a hype cycle in the Languages context such as the “language lab” (especially in the tertiary context) and “learning objects” (for K-12). It’s also easy to apply the above hype cycle of emerging technologies to education more broadly (indeed, this has been done by many as a quick Flickr search reveals) and to Languages as well (I haven’t been able to find any specific models, and would love some references). The vertical axis on the chart is quite interesting – it represents “visibility”. In doing so, the hype cycle isn’t necessarily about use of technologies (in this case), but rather awareness or perception of. In other words, what people are talking about and think are going to be “the next big thing”. The hype. Rather fitting for my research, given the phenomenological slant, right?
Fenn and Raskino give a few overly examples in their book, such as Amazon’s stock prices, changing stock prices in China, and the frequency of the term “business model” in articles archived by Factiva. Each follow the cycle quite closely.
This lead me to try a similar exercise with the term “computer assisted language learning” and Google Scholar (http://scholar.google.com). Now this type of search may be problematic in that Google Scholar does not reference all of the CALL journals and only has records of publications available digitally (perhaps a library catalogue search is the next step!) but it does incorporate a very wide range of journal databases and when we’re considering visibility (accessible, easy to find articles) then Google Scholar is probably not a bad tool. The resulting chart looked like this:
The chart begins at 1970 because no results were returned via Google Scholar for articles or books before then. I know they exist, but they are not visible via the search engine. A search on terms such as “language learning” and “technology” together may prove more fruitful, but those terms are also too generic to be very useful: a word like “technology” brings up everything from institutions that teach Languages (e.g. MIT) to retail brochures. To put “language learning and technology” as an exact phrase is also too restrictive as authors may have used more specialised terminology such as “language learning and ICTs” or written it in a different way such as “technology and language learning.” Hence although use of the term “CALL” is quite hotly debated (some say that it should be “Technology Enhanced Language Learning” or just “Language Learning”), I found it a very useful indeed for conducting this search because it is a unique identifier. The term CALL may well be out-dated but I agree with Levy and Hubbard (2005) in that its purpose is to identify the field and not necessarily to define it. The term increases the searchability and findability of the field as a concept.
At first glance, the line graph appears to fit the cycle somewhat and the dip around 2000 (a “trough of disillusionment”?) is reflected in the literature with authors questioning CALL’s identity as a discipline and the need for a more explicit research agenda (Chapelle, 1997; Davies, 2001). However, this in turn sparked many more articles on the issue of CALL’s identity, and retrospective pieces that have done much to define and (re)imagine CALL as a field (e.g. Levy & Hubbard, 2005; Salaberry, 2001), accounting for much of the upward trend. Perhaps the graph charts visibility of the term “CALL” rather than visibility of the use of technology for learning and teaching Languages, but to my mind the two are very much related and so it serves both purposes. But the hype cycle is certainly not pronounced (there’s no real “peak of inflated expectations”), and I fear that I’m making the data fit the model rather than using a more grounded approach.
What the above chart shows to me, really, is that the field of CALL and the associated (talking of and visibility of) use of technology is still emerging. 800 ‘hits’ from Google Scholar for articles published in 2009 is tiny, relatively speaking. The field may be growing in momentum and visibility but it is nowhere near the “plateau of productivity.” Indeed, not one teacher or student I interviewed during my field work actually referred to “CALL”, no documents from the schools reference it, and in our second interview, I had to define the terminology in my questions. The same went for my questions about “emerging technologies,” many of which I thought were mainstream but, as it turned out, were not at all visible to my teacher and student participants. So one interpretation is that the field of CALL is still at the beginning of the hype cycle and we are only now seeing the “peak of of inflated expectations.” The hype has barely begun, especially in K-12.
This begs the question, how long does a technology need to be emerging before it is no longer defined as such? How long does a field need to be emerging before it is no longer defined as such? Will the field of CALL ever emerge from perpetual beta? Will I get to see the (K-12) plateau of productivity?
My research project is only one contribution towards the field, emerging or not. Hopefully it doesn’t fall into the “trough of disillusionment” but rather is an attempt to build up that “slope of enlightenment.” In any case, it is a chance to explore the hype and increase visibility and thought about language learning and technology, at least for my participants. It would be interesting to apply the hype cycle to other aspects of CALL, and to chart emerging technologies for Languages education against it, as in Martin’s chart above. It would also be interesting to compare CALL-visibility in the tertiary context to that of K-12. Is anyone up for the challenge?
Chapelle, C. (1997). CALL in the year 2000: Still in search of research paradigms? Language Learning & Technology, 1(1), 19-43.
Davies, G. (2001). New technologies and languagelLearning: A suitable subject for research? In A. Chambers & G. Davies (Eds.) ICT and language learning: a European perspective (pp. 13-27). Lisse, The Netherlands: Swets & Zeitlinger Publishers.
Fenn, J. (1995). When to leap on the hype cycle. Gartner Group, http://www.gartner.com
Fenn, J., & Raskino, M. (2008). Mastering the hype cycle: how to choose the right innovation at the right time. Boston: Harvard Business Press.
Levy, M., & Hubbard, P. (2005). Why call CALL “CALL”? Computer Assisted Language Learning, 18(3), 143-149.
Salaberry, M. R. (2001). The use of technology for second language learning and teaching: A retrospective. The Modern Language Journal, 85, 39-56.