The criteria for evaluating the worth of any language learning software must include some assessment of its fitness for purpose. That is to say, does it facilitate learning? But how do you measure this? Short of empirically testing the software on a representative cross-section of learners, we need a rubric according to which the learning power of the item can be estimated. And this rubric should, ideally, be informed by our current understandings of how second languages are best learned, understandings which are in turn derived from the findings of researchers of second language acquisition (SLA).

This is easier said than done, of course, as there is (still) little real consensus on how the burgeoning research into SLA should be interpreted. This is partly because of the invisibility of most cognitive processes, but also because of the huge range of variables that SLA embraces: different languages, different aspects of language, different learners, different learning contexts, different learning needs, different learning outcomes, different instructional materials, and so on.  Generalizing from research context A to learning context B is fraught with risks.

There is also a tendency, inevitable perhaps, for advocates of particular learning methods or materials to cherry-pick the evidence in order to bolster their own cause.  I’m not sure I’ll be able to avoid this charge myself. But, in an attempt to be as impartial as possible, and in order to draw up a useable set of criteria for gauging the learning power of any new edtech tool, I’m going to borrow from a selection of ‘state of the art’ papers on SLA (see bibliography below). Following VanPatten and Williams (2007), for example, I’m going to draw up a list of ‘observations’ about SLA that have been culled from the research. On the basis of these, and inspired by Long (2011), I will then attempt to frame some questions that can be asked of any educational technology in order to predict its potential for facilitating learning.

 

Here, then, are the 10 observations:

1. The acquisition of an L2 grammar follows a ‘natural order’ that is roughly the same for all learners, independent of age, L1, instructional approach, etc., although there is considerable variability in terms of the rate of acquisition and of ultimate achievement (Ellis 2008), and, moreover, ‘a good deal of SLA happens incidentally’ (VanPatten and Williams 2007).

 

2. ‘The learner’s task is enormous because language is enormously complex’ (Lightbown 2000).

 

3. ‘Exposure to input is necessary’ (VanPatten and Williams 2007).

 

4. ‘Language learners can benefit from noticing salient features of the input’ (Tomlinson 2011).

 

5. Learners benefit when their linguistic resources are stretched to meet their communicative needs (Swain 1995).

 

6. ‘There is clear evidence that corrective feedback contributes to learning’ (Ellis 2008).

 

7. Learners can learn from each other during communicative interaction (Swain et al. 2003).

 

8. Fluency is an effect of having a large store of memorized sequences or chunks (Nattinger & DeCarrico 1992; Segalowitz 2010).

 

9. Learning, particularly of words, is aided when the learner makes strong associations with the new material (Sökmen 1997).

 

10. All things being equal, the more time (and the more intensive the time) spent learning and using the language, the better (Muñoz 2012).

 

On the basis of these observations, the following questions can be formulated:

1.  ADAPTIVITY: Does the software assume that learning is linear, incremental, uniform, predictable and intentional? Or does it accommodate the often recursive, stochastic, incidental, and idiosyncratic nature of learning, e.g. by revisiting material, by adapting to the user’s learning history, by allowing the users to set their own learning paths and goals?

 

2. COMPLEXITY: Does the software address the complexity of language, including its multiple interrelated sub-systems (e.g. grammar, lexis, phonology, discourse, pragmatics)?

 

3. INPUT: Is material provided for reading and/or listening, and is this input rich, comprehensible, and engaging? Are there means by which the input can be made more comprehensible? And is there a lot of input (so as to optimize the chances of repeated encounters with language items, and of incidental learning)?

 

4. FOCUS ON FORM: Are there mechanisms whereby the user’s attention is directed to features of the input and/or mechanisms that the user can enlist to make features of the input salient?

 

5. OUTPUT: Are there opportunities for language production? Are there means whereby the user is pushed to produce language at or even beyond his/her current level of competence?

 

6. FEEDBACK: Does the user get focused feedback on their comprehension and production, including feedback on error?

 

7. INTERACTION: Is there provision for the user to collaborate and interact with other users (whether other learners or proficient speakers) in the target language?

 

8. CHUNKS: Does the software encourage/facilitate the acquisition and use of formulaic language?

 

9. PERSONALIZATION: Does the software encourage the user to form strong personal associations with the material?

 

10. INVESTMENT: Is the software sufficiently engaging/motivating to increase the likelihood of sustained and repeated use?

 

This list is very provisional: consider it work in progress. But it does replicate a number of the criteria that have been used to evaluate educational materials generally (e.g. Tomlinson 2011) and educational technologies specifically (e.g. Kervin and Derewianka 2011). At the same time, the questions might also provide a framework for comparing and contrasting the learning power of self-access technology with that of more traditional, teacher-mediated classroom instruction.

Any suggestions for amendments and improvements would be very welcome!

 

To see other posts by Scott Thornbury, try Who ordered the McNuggets?, Writing by numbers: The myth of coursebook creativity and Intersubjectivity: Is there an app for that?

References:

Ellis, R. 2008. The Study of Second Language Acquisition (2nd edn). Oxford: Oxford University Press.

Kervin, L. & Derewianka, B. (2011) ‘New technologies to support language learning’, in Tomlinson, B. (ed.) Materials Development in Language Teaching (2nd edn). Cambridge: Cambridge University Press.

Lightbown, P.M. (2000) ‘Classroom SLA research and second language teaching’. Applied Linguistics, 21/4, 431-462.

Long, M.H. (2011) ‘Methodological principles for language teaching’. In Long, M.H. & Doughty, C. (eds) The Handbook of Language Teaching, Oxford: Blackwell.

Muñoz, C. (ed.) (2012). Intensive Exposure Experiences in Second Language Learning. Bristol: Multilingual Matters.

Nattinger, J.R. & DeCarrico, J.S. (1992). Lexical Phrases and Language Teaching. Oxford: Oxford University Press.

Segalowitrz, N. (2010) Cognitive Bases of Second Language Fluency. London: Routledge.

Sökmen, A.J. (1997) ‘Current trends in teaching second language vocabulary,’ in Schmitt, N. and McCarthy, M. (Eds.) Vocabulary: Description, Acquisition and Pedagogy. Cambridge: Cambridge University Press.

Swain, M. (1995) ‘Three functions of output in second language learning’, in Cook, G., & Seidlhofer, B. (eds) Principle and Practice in Applied Linguistics: Studies in Honour of H.G.W. Widdowson. Oxford: Oxford University Press.

Swain, M., Brooks, L. & Tocalli-Beller, A. (2003) ‘Peer-peer dialogue as a means of second language learning’. Annual Review of Applied Linguistics, 23: 171-185.

Tomlinson, B. (2011) ‘Introduction: principles and procedures of materials development,’ in Tomlinson, B. (ed.) Materials Development in Language Teaching (2nd edn). Cambridge: Cambridge University Press.

VanPatten, B. & Williams, J. (eds) 2007. Theories in Second Language Acquisition: An Introduction. Mahwah, NJ: Lawrence Erlbaum.

 

Scott Thornbury reads stuff about language learning and teaching.

 

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