effect of technology on sla

8/10/2019 Effect of Technology on SLA

1/45

Elizabeth Hanson-SmithProfessor emeritus, Calif State Univ, Sacramento, USAComputers for EducationCommand Performance Language Institute

http://webpages.csus.edu/~hansonsm

[email protected]

The Effect of Technology on

Second Language Acquisition(and vice versa)
http://www.geocities.com/ehansonsmi/http://www.geocities.com/ehansonsmi/


2/45

Topics- What are the problems facing CALL researchers?

- What is SLA?

- Are there any solutions?


3/45

Methodsare fundamental ways of working to bring

about a change in the learner's cognitive processesMediaare the means by which the method is deliveredto the learner

Media attributes are the delivery methods which aparticular medium offers (e.g., zooming in video)

de Lisle's summary of Clarkes (1994) Media Will NeverInfluence Learning:

Instructional Methods differ from Instructional Media


4/45

"there is no single media attribute that serves aunique cognitive effect for some learning task,

[so]

the attributes must be proxies for someother variables that are instrumental in learninggains" (Clarke, 1994, p. 22).


5/45

Media are like the delivery truck

we are grateful to UPS, but thecontent of the box isn't theirs.


6/45

De Lisle's summary of Clarke:

The learning effects demonstrated aredue [not to the delivery method, but] to

superior Instructional methods being builtinto Computer Based learning situations.


7/45

In brief, my claim is that media research is atriumph of enthusiasm over substantiveexamination of structural processes in

learning and instruction.(Clarke, 1994, p. 27)


8/45

What is SLA? - Definition(s)

Krashen's Input Model

Graph constructed at Gliffy.com


9/45

The above is admittedly a very simple version,based on Stevick's illustration (1980, p. 270).Krashen by 1981 has a much more elaboratedversion (see especially p. 101) that takes intoaccount the impact of learning on acquisition,though clearly he never strayed from theidea that input is primary to the process of

SLA.


10/45


An Interactionist Model

Based on Chapelle, 1998, Fig. 2, p. 23 (see also, Swain, 1985).



11/45


Stevick's Levertov Machine



12/45

The "Rheostat" in Stevick's model turns up attentionand hence acquisition and output capabilities. Socialforces are important: How learners feel about schooland learning, and also the reactions of others duringcommunication. What we acquire and what we learn

interact with each other. Reactions to our output aidboth acquisition and learning. (Stevick, 1980, pp.270-279.)


13/45

What is SLA? - Plato's ProblemorHow do we we acquire so much

knowledge on the basis of so littleinformation?


14/45

Landauer & Dumais (2004): "A typical American seventhgrader knows the meaning of 10-15 words today that shedidn't know yesterday" (p. 2). Most of these words musthave been acquired through reading because themajority of English words are used only in print, and shehas already acquired the full complement of oral

vocabulary; however, she has acquired less than one wordthrough direct instruction since yesterday.

About one word for every twenty paragraphs read in aschool text goes from wrong to right on a daily

vocabulary test. Yet the typical seventh grader wouldhave read fewer than 50 paragraphs since yesterday.How did she acquire these words she didn't encounter?


15/45

Plato's solution for this "mystery ofexcessive knowledge"is that people are bornwith most of their knowledge and need onlyhints or contemplation to retrieve it.


16/45

What is SLA?Latent Semantic Analysis (LSA)

A general theory of "acquired similarity and knowledgerepresentation" (Landauer & Dumais (2004): p. 1).

Landauer and Dumais used the Grolier Encyclopedia, an electronic

text for young students, to analyze 30,473 articles with a mean textlength of 151 words. (Some articles were only one sentence long, e.g.,"Constantinople; see Istanbul," and longer articles were cut off at

2,000 characters.) The words were placed into a matrix, each columnrepresenting an article, and each row one of 60,768 word-types that

appeared in at least 2 articles. Each cell contained the frequency withwhich a word appeared in that article:


17/45

Word/

Article1 2

.. ..

30,000

x x x x x x x x

x x x x x x x x

x x x x x x x x

x x x x x x x x

x x x x x x x x

x x x x x x x x

60,000 x x x x x x x x

Table based on Landauer & Dumais, Figure 2, p. 13


18/45

Latent Semantic Analysis 2

The computer is then able to determine logrithmically whatwords (i.e., strings of characters) appear in what contexts(i.e., with other words/strings), but even more importantly,what words might appear in similar contexts.

When given the synonym portion of the TOEFL, themachine approximated the average scores of EFL applicantsto U.S. colleges. The model got 64.4% correct, and the

students got 64.5% (Landauer & Dumais, p. 14).


19/45

This is all without the computer understanding thewords tested semantically, andwithout being able to use grammar/syntax cues.

"A substantial portion of the information needed to

answer common vocabulary test questions can beinferred from the contextual statistics of usagealone" (Landauer & Dumais, 2004, pp. 2-3)


20/45

The machine acquired knowledge aboutsynonymity "from the kinds of experience onwhich a human relies"(Landauer & Dumais, p. 15).

That is, the hundreds of billions of neuralnetworks in the brain can exploit both indirectinference and co-occurrence relations, both

within and beyond a particular text.


21/45

Several observations by Landauer & Dumais:

- ...weak local constraints [e.g., in the search forsynonymity] can combine to produce strong inductiveeffects (p. 6)

- ...the effects of constraints [which may be very weakin themselves] may emerge only in very large naturallygenerated ensembles. In other words, experiments withminiature or concocted subsets of language may not besufficient to reveal or assess the forces that holdconceptual knowledge together. (p. 6)


22/45

(To learn a language, you need masses of inputdata as encountered naturally by people.)

- Knowledge comes not just from an immediate stimulusor direct experience with something, e.g., encounteringa word, but "with everything else ever experienced." (p.11)


23/45

What is SLA? - LSA 4

The LSA model accounts for other aspects of humanknowledge:

First- through fifth-graders learn about 10words a day, despite learning only about oneword a week by direct instruction. (p. 17)


24/45

This is possible because:

A late grade school child will have read about 3.8 millionwords. The direct learningeffect is calculated at .0007words per word encountered X 70 (the approximate

number of words in a paragraph). The indirect effectis .15 words per word encountered.

An average student reads 50 paragraphs daily,

amounting to 10 new words/day learned. (p. 22)


25/45

What is SLA? - LSA 5

Landauer & Dumais (2004):

Expert readers "get more" out of what they read.There is "inductive power inherent in the possession of

large bodies of old knowledge." (p. 31)

By the end of secondary school, a knowledge of100,000 words is probably a low estimate.


26/45

The expert reading her 2 millionth paragraph has a.56 probablility of correct extrapolation whenencountering a new term in, say, an academic journal,while the novice encountering only his second sample

of a similar context has a .14 probability of correctmeaning: he is about 1/4 as able to read for meaning.

There is "inductive power inherent in the possessionof large bodies of old knowledge." (p. 31)


27/45

Is the medium the message? Back in 1994, Clarke told usno, it was not. If you drill and grill on the computer, it'sno different than doing it in the classroom. You can clickfor animation or zoom for details, but these are delivery,

not content or methods.

- Only superior methods can produce better learning.

Therefore,

- CALL researchers are in fact investigating methods.


28/45

Does CALL provide us with superiormethods of delivering instruction?

Or superior quantities of natural language?

Or something else?


29/45

A 4-year-old, when asked what she was fishingfor behind the TV, replied "the mouse."(Carr, 2008, C7)

Another 4-year-old asked to see the movie shehad just viewed on broadcast TV at thebabysitters' house. When told it wasn't on TVjust then, she asked, "Is it broken?"

(Carr, 2008, C7)


30/45

- You point, you click, you don't wait.- You don't have to allow others to selectwhat you read or listen to.


31/45

So possibly both method (in the largestsense) and input--and the methods of input--as well as motivational quality are all superior

in a CALL environment.


32/45

Putting together all these sources:

* "Methods" may in fact be seen as less importantthan the delivery of input--and howinput is delivered.

* Masses of input are more important than directinstruction. (Are we back to Krashen??)

* Authentic content is more important for indirectlearning than prepared texts with narrow foci.


33/45

* Human readers can readily disambiguate termsthrough local context, using their hundreds of billionsof parallel computational elements (Landauer & Dumais,p. 32); hence, concordancers should be important tools

in language input.

* Since humans are exposed to spoken language aswell as print, the newer forms of oral Web interaction,such as VoIP should become increasingly important forcommunication beyond classmates and teacher.


34/45

* Since, in language, learners can produce the same

events that they perceive--and receive feedback ontheir approximations (remembering Stevick's Levertovmachine)--opportunities for communicative productionare very important to expanding the knowledge base

and neural networks.

* Some degree of autonomy in the selection of mediaand learning goals appears to be useful both formotivation and in making inferences about content andlinguistic structures.


35/45

The media-rich, Internet-enhanced computer-based environment offers multipleopportunities to expand input and interactionfar beyond schoolroom walls.

Additionally, it offers the potential forlearner autonomy and motivation.


36/45

Taking into account these ideas, what can weconclude about the proper functions of CALL--and by extension what should be the scopeof CALL research?


37/45

* Content-based learning is important--itprovides the contextual clues that allowinferred induction to develop

* Authentic, extensive materials areimportant--they provide the large masses ofinformation necessary for inferential learning

* Learners need opportunities to directtheir own learning


38/45

* Opportunities for creative output andinteraction are important, e.g., in extensiveproject-based learning involving an authenticaudience--they allow learners to experiment

and refine hypotheses about what they arelearning

(see CALL Environments, Egbert & Hanson-Smith, eds., 2007, particularly Chapter 1)


39/45

Of lesser importance in SLA and hence inresearching CALL:

* Learning of discrete items, e.g., parts of

speech in decontextualized sentences

* Tests judging rote learning, e.g., lists ofvocabulary items


40/45

A significant problem is how to control the

variables when dealing with autonomouslearner choices, massive amounts ofauthentic materials (as in extensive readingand long-term projects), and multiple media

resources for both receptive and expressivecommunications--and often all of these atthe same time.


41/45

References

Berry, M. W. (1992). Large scale singular value computations.International Journal of Supercomputer Applications, 6(1), 13-49.

Carr, D. You want, you click (no waiting). 2008. New York Times,Business Day, 31 March, pp. C1 + C7.

Chapelle, C. A. (1998). Multimedia CALL: Lessons to be learnedfrom research on instructed SLA. Language Learning & Technology,2(1), 22-34. Available athttp://llt.msu.edu/vol2num1/article1/index.html.

Clarke, R. E. (1994). Media will never influence learning.Educational Technology Research and Development, 42(2), 21-30.
http://llt.msu.edu/vol2num1/article1/index.htmlhttp://llt.msu.edu/vol2num1/article1/index.html


42/45

References, cont.

de Lisle, P. (n.d.) Summary of Clarke (1994): "Media will neverinfluence Learning" (M.Ed. Project). Available athttp://hagar.up.ac.za/catts/learner/peterdl/ClarkeKozma.htm.

Egbert, J. & Hanson-Smith, E., eds. (2007). CALL Environments:Research, practice, and critical issues. Alexandria, VA: TESOL.

Krashen, S. (1981). Second language acquisition and secondlanguage learning. New York: Pergamon Press.

Landauer, T. K., & Dumais, S. T. (2004). A solution to Plato'sproblem: The Latent Semantic Analysis theory of acquisition,

induction and representation of knowledge. Available athttp://lsa.colorado.edu/papers/plato/plato.annote.html.
http://hagar.up.ac.za/catts/learner/peterdl/ClarkeKozma.htmhttp://lsa.colorado.edu/papers/plato/plato.annote.htmlhttp://lsa.colorado.edu/papers/plato/plato.annote.htmlhttp://hagar.up.ac.za/catts/learner/peterdl/ClarkeKozma.htm


43/45

References, cont.

Stevick, E. W. 1980. The Monitor Model and the LevertovMachine. In E. Stevick, ed., Teaching languages: A way and ways,pp. 267-282. Rowley, MA: Newbury House.

Swain, M. (1985). Communicative competence: some roles of

comprehensible input and comprehensible output in itsdevelopment. In S. M. Gass & C. G. Madden, eds., Input in secondlanguage acquisition,pp. 235-253). Rowley, MA: Newbury House.


44/45

*Notes:

A free software version of the program used toanalyze large matrices by Landauer and Dumais isavailable fromhttp://www.netlib.org/svdpack/index.html

(see Berry 1992).University-affiliated researchers may obtain aresearch-only license and complete software toreplicate Landauer & Dumais' work in LSA by

contacting Susan Dumais at the Information SciencesResearch Bellcore, Morristown, NJ 07960.
http://www.netlib.org/svdpack/index.htmlhttp://www.netlib.org/svdpack/index.html


45/45

An outline of this paper may be viewed athttp://tesol-tech-sla.wikispaces.com/

Links to my other papers and work in software andWebware design are found at my homepage:

http://webpages.csus.edu/~hansonsm
http://tesol-tech-sla.wikispaces.com/http://www.geocities.com/ehansonsmihttp://www.geocities.com/ehansonsmihttp://tesol-tech-sla.wikispaces.com/http://tesol-tech-sla.wikispaces.com/http://tesol-tech-sla.wikispaces.com/http://tesol-tech-sla.wikispaces.com/http://tesol-tech-sla.wikispaces.com/

effect of technology on sla

Documents