Hostname: page-component-848d4c4894-5nwft Total loading time: 0 Render date: 2024-06-02T09:26:30.659Z Has data issue: false hasContentIssue false
  • English
  • Français

Technological disruption in foreign language teaching: The rise of simultaneous machine translation

Published online by Cambridge University Press:  13 September 2018

Scott A. Crossley
Scott A. Crossley*
Affiliation:
Department of Applied Linguistics/ESL, Georgia State University, USAscrossley@gsu.edu
Get access Rights & Permissions [Opens in a new window]

Extract

The fear of technology replacing jobs can be traced back to Aristotle, who, before great technological advances existed, ventured that machines may one day end the need for human labor (Campa 2014). In the current era, there is overwhelming evidence of technological unemployment. This evidence comes in the form of jobs that were once common, but have largely been replaced by technology such as switchboard operators, travel agents, booth cashiers, bank tellers, and typists. These jobs still exist, but their numbers have declined sharply because they were easily replaced by technology. Statistical models indicate future job losses in these areas will continue with booth cashiers at an 84% risk of losing their jobs, travel agents at a 10% risk, and typists at an 81% risk (Frey & Osborne 2013). These, generally, entry level positions do not require specialized training or advanced degrees, which may explain some of the job losses. However, current trends indicate that training and advanced degrees do not necessarily offer protection against technological unemployment, with most analysts predicting that technology will soon replace lawyers (Markoff 2011), pharmacy technicians, and accountants (Frey & Osborne 2013). Unemployment in career sectors such as these will have adverse effects not only on the workers, but also on the systems that support them. When the need for lawyers, pharmacists, and accountants collapses, what will happen to law schools, colleges of pharmacy, and accounting departments that train specialists in these fields? What will happen to the support systems that depend on these jobs or the scholars that move these fields forward through research activities?

Type
First Person Singular
Information
Language Teaching , Volume 51 , Issue 4 , October 2018 , pp. 541 - 552
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Belmechri, F. & Hummel, K. (1998). Orientations and motivation in the acquisition of English as a second language among high school students in Quebec City. Language Learning 48.2, 219– 244.Google Scholar
Benson, M. J. (1991). Attitudes and motivation towards English: A survey of Japanese freshmen. RELC Journal 22.1, 34–48.Google Scholar
Bhatt, R. M. (2001). World Englishes. Annual Review of Anthropology 30.1, 527–550.Google Scholar
Bialystok, E., Craik, F. M., Klein, R. & Viswanathan, M. (2004). Bilingualism, aging, and cognitive control: Evidence from the Simon task. Psychology and Aging 19.2, 290–303.Google Scholar
Campa, R. (2014). Technological growth and unemployment: A global scenario analysis. Journal of evolution and technology 24.1, 86–103.Google Scholar
Choi, S. K., Kim, T. W., Yuh, S. H., Jung, H. M., Sim, C. M. & Park, S. K. (1999). English-to-Korean Web Translator: FromTo/Web-EK. Machine Translation Summit VII.Google Scholar
Crystal, D. (2012). English as a global language. Cambridge University Press.Google Scholar
Costa, A., Hernández, M., Costa-Faidella, J. & Sebastián-Gallés, N. (2009). On the bilingual advantage in conflict processing: Now you see it, now you don't. Cognition 113.2, 135–149.Google Scholar
Dörnyei, Z. (2009). The L2 motivational self-system. In Dörnyei, Z. & Ushioda, E. (eds.), Motivation, language identity and the L2 self. Bristol, UK: Multilingual Matters, 9–42.Google Scholar
Dörnyei, Z. & Csizér, K. (2002). Some dynamics of language attitudes and motivation: Results of a longitudinal nationwide survey. Applied Linguistics 23.4, 421–462.Google Scholar
Frey, C. B. & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation. Retrieved from http://acikistihbarat.com/Dosyalar/effect-of-computerisation-on-employment-report-acikistihbarat.pdf.Google Scholar
Gardner, R. C. & Lambert, W. E. (1959). Motivational variables in second-language acquisition. Canadian Journal of Psychology/Revue canadienne de psychologie 13.4, 26–72.Google Scholar
Gardner, R. C. (1985). Social psychology and second learning: The role of attitudes and motivation. London: Edward Arnold.Google Scholar
Gardner, R. C. & MacIntyre, P. D. (1991). An instrumental motivation in language study. Studies in second Acquisition 13.1, 57–72.Google Scholar
Gehring, J., Auli, M., Grangier, D., Yarats, D. & Dauphin, Y. (2017). Convolutional sequence to sequence learning. arXiv:1705.03122v3 [cs.CL]Google Scholar
Godsey, M. (2015). The deconstruction of the K-12 teacher. The Atlantic. Retrieved from http://www.theatlantic.com/education/archive/2015/03/the-deconstruction-of-the-k-12-teacher/388631/.Google Scholar
Hampshire, S. & Salvia, C. P. (2010). Translation and the internet: Evaluating the quality of free online machine translators. Quaderns: revista de traducció 17, 197–209.Google Scholar
Henry, A. (2017). L2 motivation and multilingual identities. Modern Language Journal 101.3, 548–565.Google Scholar
Kuenzi, J. J. (2008). Science, technology, engineering, and mathematics (STEM) education: Background, federal policy, and legislative action. Congressional Research Service Report RL33434.Google Scholar
Lukmani, Y. M. (1972). Motivation to learn and language proficiency. Language Learning 22.2, 261–273.Google Scholar
Markoff, J. (2011). Armies of expensive lawyers replaced by cheaper software. The New York Times, 4 March.Google Scholar
Masgoret, A. M. & Gardner, R. C. (2003). Attitudes, motivation, and L2 learning: A meta–analysis of studies conducted by Gardner and associates. Language Learning 53.1, 123–163.Google Scholar
Papineni, K., Roukos, S., Ward, T. & Zhu, W. J. (2002). BLEU: A method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 311–318.Google Scholar
Pinker, S. (2007). The language instinct (1994/2007). New York: Harper Perennial Modern Classics.Google Scholar
Richards, J. C. & Rogers, T. (2014). Approaches and methods in language teaching: A description and analysis (3rd edn.). New York: Cambridge University Press.Google Scholar
Rotman, D. (2013). How technology is destroying jobs. MIT Technology Review. Retrieved from https://www.technologyreview.com/s/515926/how-technology-is-destroying-jobs.Google Scholar
Salim, M., Ibrahim, N. & Hassan, H. (2012). Language for tourism: A review of literature. Procedia-Social and Behavioral Science 66, 136–143.Google Scholar
Savoy, J. & Dolamic, L. (2009). How effective is Google's translation service in search? Communications of the ACM 52.10, 139–143.Google Scholar
Shaaban, K. A. & Ghaith, G. (2000). Student motivation to learn English as a foreign language. Foreign Language Annals 33.6, 632–644.Google Scholar
Taguchi, T., Magid, M. & Papi, M. (2009). The L2 motivational self system among Japanese, Chinese and Iranian learners of English: A comparative study. In Dörnyei, Z. & Ushioda, E. (eds.), Motivation, language identity and the L2 self. Bristol: Multilingual Matters, 66–97.Google Scholar
Thompson, A. S. (2017). Language learning motivation in the United States: An examination of language choice and multilingualism. Modern Language Journal 101.3, 483–500.Google Scholar
Ushioda, E. & Dörnyei, Z. (2017). Beyond global English: Motivation to learn languages in a multicultural world: Introduction to the special issue. Modern Language Journal 101.3, 451–454.Google Scholar
Watters, P. & Patel, M. (1999). Semantic processing performance of internet machine translation systems. Internet Research 9.2, 153–160.Google Scholar