SLA: How Meaning Is Negotiated Using Technology

Technology is taking the second language acquisition to a whole new different level.  Consider for instance, visiting the Google Translate website – Google’s free online language translation service.  The site instantly translates text and web pages to any desired target language that you want.  Although this automatic translation tool clearly has its own set of limitations (as will be explained later), you can’t deny that a lot of people find this useful one way or the other.

A product of innovation and technology, Google Translate is not the only thing that’s prominent when it comes to helping people in learning or understanding a new language.  Some of the related advancements in this arena include automated communication systems, online dictionaries, electronic talking machines, dictation programs that can transcribe speech, and a whole lot many more – innovations that can simulate the human speech and intelligence.  But the question of how accurate are these computerized programs to fully assist the learning needs of people remains to be an unfinished puzzle, something to  explore further by researchers in the future.  If the progress of technology has influenced the strategies in second language acquisition and learning that much, does it ever come across your mind if these computer-mediated programs are at par with the conventional human to human interaction? Or is the use of technology inSLAa far cry from it?

This is something that Carol Chapelle explored in her article entitled “Technology and Second Language Acquisition.”  Generally, the article tackled about the relationship of information and communication technology and second language acquisition (SLA) – how technology can help teachers design research and activity tasks for their students and how influential is the technology in helping the students learn a second language the easier way, with the introduction of such programs like the computer-assisted language learning (CALL) and computer-assisted second language research (CASLR).

Both CALL and CASLR require the students to work on their target language interactively with a computer.  This is primarily what the program is all about.  Surprisingly so, one of the goals of this project is to assess a number of hypotheses in SLA, for instance, testing if either the presence or the absence of grammar explanation involving any computer-mediated learning activity made a difference on the overall performance of the learner.

While it is true that both the CALL and the CASLR are at some point, reliable in the aspects of instructedSLA, there are some instances in which the teachers have to be wary in implementing either.  Chapelle emphasized that the choice of research task or classroom activity (to contextualize it) should depend on the goals that have to be achieved.  In the end, it is highly recommended for teachers to come up with learning strategies that will engage learners in interaction, so that they can make essential connections between form and meaning, between computer-mediated learning tasks and human-to-human context-embedded interaction.

Following that line of thinking, Chapelle highlighted some recommendations that can be made for learning materials.  First one – the key linguistic characteristics should be clear enough for students – as can be effectively done through modifications and repetitions.  And second – Chapelle promoted the idea of technology-supported pedagogy inSLA. This has something to do with a “support modified interaction between the learner and the computer by providing the learner with control when to request help, modify responses, and get access to repetition and review.”

The second recommendation given by Chapelle can be expounded this way: students can negotiate meaning best in a computer-mediated language learning if teachers can provide assistance whenever possible. “When a comprehension breakdown occurs,” Chapelle reiterated, “they [the learners] can stop the normal flow of comprehension to review, repeat or ask for help.” Tasks can be done with a combination of oral and written modes for a better comprehension.

Consider for instance, online language assistance programs such as online dictionaries or Google translate.  With the internet integrated in our lives, second language learning is easier with the help of readily accessible L2 technology, for example, looking up a foreign word in an online dictionary after you have stumbled upon it on any website.  Similarly, Google Translate may be touted as the free machine translation program with a high degree of accuracy, but there is still a need for assistance in terms of context, syntax and grammar checking that teachers and fellow learners can effectively provide.

Furthermore, the use of technology in learning or acquiring a new language is not only limited in the academic setting.  On the contrary, the influence of technology to a second language learner is much deeper in everyday, out-of-school contexts.  The power of technology is far-reaching both in formal and informal settings.  And this is why Chapelle’s recommendation for a technology-assisted language use and acquisition is deemed important.  Researchers and teachers alike should be fully aware of the consequences of their own teaching strategies and research tasks that have to do withSLA, knowing that technology can greatly change the linguistic input of the learners.  Such change in input, and how learners get to access new forms of this input, will in the end affect acquisition.

Computers may be good when it comes to solving big numbers, calculating a huge sum of money or even constructing blueprints for buildings and bridges.  But you can’t deny that creatingSLAtasks and programs that simulate human learning is still tough.  Translation is a good example for this – statistical learning algorithms can make educated guesses, but if the text is embedded with context it’s very difficult to figure out the rules of language or to translate the intended meaning into the target language.  Emotional recognition is another pressing problem, as in the context ofSLAcomputerized programs, it’s complicated to model emotion on a machine.  This is where Chapelle’s contention really comes in helpful – technology can makeSLAeasier and more accessible, but it’s essential that it is still guided so as to limit the possibilities of miscomprehension.

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