Universidad Nebrija

Este trabajo analiza “Online Translation Use in Spanish as a Foreign Language Essay Writing: Effects on Fluency, Complexity and Accuracy” de Kent Fredholm y discute si las tecnologías de traducción automàtica en línea como Traductor de Google ayudan a los estudiantes a mejorar sus habilidades de expresión escrita en lengua extranjera.

This paper analyses Kent Fredholm’s “Online Translation Use in Spanish as a Foreign Language Essay Writing: Effects on Fluency, Complexity and Accuracy” and discusses whether the use of online translation technology such as Google Translate enhances students’ writing skills in a foreign language.

Fecha de recepción: 21 enero de 2015

Fecha de aceptación: 4 marzo de 2015

It is often assumed that pedagogical practice is enhanced by technology. This popular assumption is put to the test by Fredholm in his article Online Translation Use in Spanish as a Foreign Language Essay Writing: Effects on Fluency, Complexity and Accuracy. He discusses whether the use of online technology tools such as Google Translate improves high school students’ essay writing in Spanish. The author concludes that using technology in the foreign language (FL) classroom does not automatically enhance students` writing skills. He is one of a growing number of linguists and academics who believe technology does not ameliorate language learning unless it is accompanied by a substantial change in the teaching/learning paradigm (McCarthy 2004; Somers, Gaspari & Niño 2006; Niño 2008; Steding 2009; Karabulut et al. 2012; Larson-Guenette 2013).

While some readers may criticize Fredholm for being a latter-day Luddite, it is undeniable that much of what he says in this article is true: there are no technological short-cuts to learning a foreign language and so no “free lunch”. More often than not educational authorities believe that there is a free lunch. They take the view that more technology in the classroom equals more learning taking place. However, teachers are understandably reluctant to embrace this digitalised teaching pedagogy when, for example, savvy-technology students use Google Translate to simply turn essays written in their L1 into their L2 and then give it to the teacher as homework. Students regularly use online translation tools to cheat on their homework assignments and so their writing skills get worse rather than better. Thus, many teachers feel conflicted about the notion of technology enhanced learning (McCarthy 2004; Somers, Gaspari & Niño 2006; Steding 2009; Karabulut et al. 2012; Larson-Guenette 2013). When online tools such as Google Translate are used to translate entire paragraphs, one cannot speak meaningfully of any language improvement as these students just substitute their own effort with the work done by the online translator.

Kent Fredholm is more than aware of the fact that “machine translation is already here and it will not go away” (McCarthy 2004). His article focuses on differences found between the texts two groups of students produced when helped or not by online translators (OT). Group A produced texts with Internet access, B had no access. The author compared groups A and B for gains in the following categories: (1) fluency, (2) complexity, (3) morphological, syntactic and lexical-pragmatic accuracy.

Category 1, fluency, is measured in this study by the number of words in students’ texts. Even if the author chooses to use composition rate (the length of texts produced during a certain amount of time) as the measure of fluency, there is no indication that the exact time each student dedicated to text production was measured. Instead, there was a certain approximate amount of time allotted for the task, but as the author recognizes, "the pupils in the present study did not all use the same amount of time to write their essays". Common sense would suggest that using OT facilitates the writing process and saves both time and effort, making students produce longer texts in a shorter time. However, we cannot confirm this hypothesis by the evidence provided in the present study as the time was not taken into consideration.

Category 2, lexical complexity, was found to hold in the essays written with and without using OT, with a slight tendency to be higher in OT-aided writing. The latter conclusion may be relevant for pedagogical purposes provided that students dedicate some effort to the unfamiliar words suggested by OT.

In Category 3, finally, there were significant differences between the groups observed in terms of the mistake types more frequent in each of the two groups. The author states that online group made more mistakes concerning verb mood while offline group made more mistakes concerning noun/adjective and noun/article agreement. In particular, Fredholm suggests that OT can help students get insights in more difficult Spanish clause and sentence structures.

Summarising, although overall effect of Google Translate on students’ FL writing performance may be negligible, it is worth keeping in mind that students can “beat the machine” in certain tasks and learn from it in others, and it should be also taken into account that each OT has its strong and weak points (Hampshire & Porta 2010). This may have pedagogical implications if appropriate tasks are assigned to students in a technology-friendly setting. For example, Google Translate could be useful in noticing exercises. In order to draw students’ attention to the kind of mistakes they may make, we provide them with a number of grammatical points that are likely to be problematic for Spanish students writing in English. For example, to discuss the grammar point “como” (“like” or “as”) the teacher can ask students to use Google to translate “trabaja como”, which will give as a result “works as”. Then students can be asked to continue typing the phrase by adding a profession (say, “camarera”, a waitress) or, for example, “loco” (crazy), which would produce “works like crazy”. This could be followed by a discussion where students intend to formulate a rule, just like in other data-driving learning (DDL) situations. Alternatively, students may be asked to edit their own work once they have written a composition draft (Kozlova & Presas 2013). In both cases, the look-up process is intentionally kept separate from the FL formulation process during the instruction period. While we do not intend to rule OT out of the language classroom completely (for OT use prevention see Steding 2009), we do propose to focus on either language or reference skills, not both at the same time.

To conclude, we believe that technology access does have a positive effect on students' writing. However, this effect should be evaluated in a wider context than that of a language classroom. Not only does technology provide easier access to information, facilitate students’ organization and motivate their learning, especially in case of at-risk students (Zheng et al. 2013: 285), but it also empowers students for their future professional life in the overall context of life-long learning.

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Karabulut, A., Levelle, K., Li, J., Suvorov, R. (2012). Technology for French learning: A mismatch between expectations and reality. CALICO Journal, 29(2): 341–366.

Kozlova, I., Presas, M. (2014). Cognitive aspects of problem solving using dictionaries in L2 writing. Scripta Manent, 9(1): 2-12. http://www.sdutsj.edus.si/ScriptaManent/2014_9_1/contents.html

Larson-Guenette, J. (2013). “It's just reflex now”: German Language Learners’ Use of Online Resources. Die Unterrichtspraxis/Teaching German, 46(1): 62–74.

McCarthy, B. (2004). Does online machine translation spell the end of take-home translation assignments? CALL-EJ Online, 6(1). http://callej.org/journal/6-1/mccarthy.html

Niño, A. (2008). Evaluating the use of machine translation post-editing in the foreign language class. Computer Assisted Language Learning, 21(1): 29-49.

Somers, H., Gaspari, F., Niño, A. (2006). Detecting inappropriate use of free online machine translation by language students – a special case of plagiarism detection. Proc. 11th EAMT Conference. 41-48. http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=F2C706923348F683EF904E1F7B735A8D?doi=10.1.1.117.7991&rep=rep1&type=pdf

Steding, S. (2009). Machine Translation in the Foreign Language Classroom : Detection, Reaction, Prevention. Unterrichtspraxis/Teaching German, 42(2): 178-189.

Zheng, B., Warschauer, M., Farkas, G. (2013). Digital Writing and Diversity: The Effects of School Laptop Programs on Literacy Processes and Outcomes. Journal of Educational Computing Research, 48(3): 267-299.