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Avances tecnológicos en las herramientas lexicográfica= s y sus repercusiones en la enseñanza del Español de los Negocios

 

Technological progress in lexicographic tools and its impact on Spanish for Business teaching<= span lang=3DEN-US style=3D'font-family:"Verdana",sans-serif;mso-ansi-language:EN= -US'>

 

 

Elisabeth Kölbl

Universidad de Ciencias Económicas y Empresariales de Viena

elisabeth.koelbl@wu.ac.at

 

Pilar Pérez Cañizares

Universidad de Ciencias Económicas y Empresariales de Viena

pperezca@wu.ac.at

 

Johannes Schnitzer

Universidad de Ciencias Económicas y Empresariales de Viena

johannes.schnitzer@wu.ac.at

 

RESUMEN

En un tiempo muy breve, la mayor oferta y mejora de las herramientas lexicográficas digitales (diccionarios, traductores, etc.) han cambiado los hábitos de uso de estos recursos por parte de los aprendientes de lenguas extranjeras. Con el objetivo de averiguar cuáles de estos recursos se usan = con mayor frecuencia y cuáles ofrecen mejores resultados, se diseñó una prueba = en la que se pidió a estudiantes universitarios de Español de los Negocios que tradujeran dos textos, del español al alemán y viceversa, y que grabaran el proceso de traducción. Los datos de 67 informantes de lengua materna alemana muestran un uso cada vez más frecuente de traductores automáticos en detrim= ento del diccionario bilingüe. Los usuarios de traductores, además, son los que mejores resultados obtienen en las tareas y también los que menos tiempo invierten. La difusión cada vez más generalizada de estas herramientas tiene implicaciones en el aula de lenguas extranjeras: los docentes deben enseñar= su manejo y adaptar las tareas a este nuevo contexto.

 

<= span class=3DSpellE>Palabras= clave: lexicografía; estudios de usuarios; recursos lexicográficos; Español de los Negocios; traductores automáticos=

ABSTRACT

Of late, both the availability and the quality of digital lexicographic tools (dictionaries, trans= lation apps, etc) have risen rapidly, prompting foreign <= span class=3DSpellE>language learners to adapt their use of such resources. In order to establish which resources are now <= span class=3DSpellE>the most frequently used and which produce the best results, 67 Ge= rman-speaking students of Business Spanish were = asked to translate two texts, one from Spanish into German and one in the other direction, and to record their use of resources in= doing so. The data obtained show an increasing use of translation apps at the expense of bilingual dictionaries. They also indicate = that app users tend to produce more accceptable translati= ons and to spend less time on producing them. These results have clear implications = for the foreign language classroom; teachers= must explain how best to use translation = apps and adapt learning tasks to this new context.<= /p>

 

Keywords: lexicography; user study; lexicographic resources; = Business Spanish; free online machine translation

 

 

 <= /p>

1. Introducción

Respecto al ámbito de los recursos lexicográficos y su uso en el aula de lenguas extranjeras, no pare= ce necesario volver a insistir en los grandes cambios que se han producido dur= ante los últimos años. La aparición de nuevas herramientas gracias a soluciones tecnológicas ha dado paso casi inmediato a su adopción por parte de los usuarios, que cuentan así con nuevas posibilidades a la hora de solucionar = problemas lexicográficos. También los hábitos de búsqueda han cambiado a una velocidad vertiginosa. Sirva como ejemplo de ello la evolución que se ha producido en= la propia institución de los autores de este artículo, que resumimos a continuación.

En un primer es= tudio publicado en el año 2016 y que se centraba en tareas de aprendizaje típicas del Españ= ol de los Negocios, pudimos constatar un predominio del diccionario electrónico bilingüe para resolver una duda lexicográfica. En aquel momento se registró también un uso absolutamente secundario del diccionario impreso, así como u= no marginal de buscadores genéricos, buscadores de traducciones, enciclopedias= o programas de traducción automática. Otras herramientas (glosarios específic= os, diccionarios monolingües, bases de datos terminológicos, etc.) prácticament= e no se consultaban (Gromann y = Schnitzer, 2016).

Tres años más t= arde, se realizó un estudio que intentaba contrastar el comportamiento de estudia= ntes y profesores en tanto que usuarios de recursos lexicográficos (Pérez Cañiza= res y Schnitzer, 2019). En esta ocasión, se apreció= entre los estudiantes de Empresariales una marcada pérdida de importancia del diccionario bilingüe unida a un ligero aumento en la popularidad de traduct= ores automáticos y de Google, así como un uso disparado de Linguee (que en ese momento ya era una combina= ción de diccionario y de buscador de traducciones).

Finalmente, este artículo presenta los resultados de un estudio llevado a cabo a lo largo de 2020 y 2021. Estos muestran un claro predominio de traductores automáticos,= que se utilizan con una frecuencia bastante mayor que el diccionario bilingüe o= los buscadores de traducciones.

Aunque los tres estudios difieren en cuanto a objetivos concretos y condiciones de las prue= bas respectivas, sus resultados son un claro indicio de que, en muy pocos años,= el comportamiento de los estudiantes universitarios respecto al uso de recursos lexicográficos ha cambiado radicalmente. Sin duda, la mayor oferta de recur= sos y también su calidad creciente han sido determinantes en esta evolución, así como la curiosidad por parte de los usuarios a la hora de descubrir nuevas posibilidades y su difusión rápida en contextos educativos.

La aparición de nuevos recursos y que tanto docentes como aprendientes conozcan de su existencia no implica, sin embargo, que estos sean utilizados de manera adecuada. En primer lugar, la simple selección del recurso más apropiado en medio de una oferta tan variada ya supone problemas. Además, los docentes se ven desbordados cuando tienen que recomendar o enseñar el uso de este tipo = de herramientas, puesto que se enfrentan a ello, en el mejor de los casos, des= de el autoaprendizaje. Estudios previos apuntan a que incluso pueden estar en desventaja respecto a los propios estudiantes (Pérez Cañizares y Schnitzer, 2019).

En el pasado, u= na de las tareas de los docentes de lenguas era enseñar cómo usar el diccionario.= Hoy en día, la gama de recursos es bastante más amplia, pero contrasta con la escasez de indicaciones para seleccionar y manejarlos correctamente. No nos constan estudios por parte de la lexicografía sobre cómo proceder ante una situación de necesidad lexicográfica concreta. La ausencia de trabajos de e= ste tipo explica a su vez que no existan, de momento, recomendaciones didácticas par= a su uso en el aula de lenguas extranjeras.

En definitiva, = la solución de este problema no puede ser inmediata, sino que debe pasar por varias fases: primero, establecer cuál es el uso óptimo de los recursos disponibles para resolver cada tipo de problema; después, mostrar a los usuarios los recursos y entrenarlos en su manejo y en las estrategias de búsqueda más adecuadas.

Y es precisamen= te en este contexto donde se sitúa nuestro estudio. Para recabar los datos, se procedió a confrontar a un grupo de estudiantes universitarios de Español de los Negocios con dos tareas del ámbito profesional (véase sección 3.1). El objetivo de estas tareas era observar cómo intentaban solucionarlas y anali= zar con qué recurso(s) y con qué estrategia(s) se consiguen los mejores resulta= dos. A partir de este análisis debería ser posible formular las indicaciones y recomendaciones pertinentes para optimizar el uso de estos recursos.

Por lo tanto, l= as preguntas de investigación a las que pretendemos contestar con nuestro estu= dio son las siguientes:

 

·      =             &nb= sp; qué tipo de herramienta se usa y con qué frecuencia;

·      =             &nb= sp; si es posible establecer perfiles de usuari= os y, en caso afirmativo, cuáles son;

·      =             &nb= sp; qué resultados se consiguen (respecto a la corrección de la traducción y al tie= mpo invertido);

·      =             &nb= sp; de qué forma se usan los traductores automáticos (p. ej. buscando solo palabra= s, frases, párrafos o la traducción del texto entero).

 

El objetivo final del estudio consiste en= sacar, a base de datos actuales, las conclusiones pertinentes para elaborar una he= rramienta didáctica específica y orientada a las necesidades de los aprendientes. Por motivos que se explicarán a continuación (ver apartado 3), el enfoque de es= te estudio es léxico-terminológico y no se tomarán en consideración aspectos gramaticales, aunque, parcialmente, se puedan resolver con las mismas herramientas.

 

 

2. Estado de la cuestión<= /p>

Resumir el esta= do de la investigación en el campo que aquí nos ocupa es una tarea que precisa al= gunas observaciones previas para poder valorar correctamente las similitudes y diferencias entre los resultados de los distintos estudios. Es cierto que la investigación del uso de herramientas lexicográficas es una de las subdisciplinas tradicionales de la lexicografía, por lo que la literatura s= obre el tema es amplísima. Sin embargo, esta extensión se reduce ostensiblemente= si se toman en cuenta los parámetros concretos que caracterizan este trabajo. Primero, nos situamos en el campo de la enseñanza de los lenguajes de especialidad (con sus condiciones didácticas específicas); segundo, nos referimos a las lenguas alemana y española, mucho menos estudiadas que el inglés, que es, con mucha diferencia, la que más atención recibe (Carreres = et al., 2017: 99); y, finalmente, focalizamos en el uso de las herramientas más modernas. Hay que ser muy prudente a la hora de relacionar y comparar los resultados de un estudio sobre el uso de traductores automáticos publicado = hace tan solo unos pocos años con los de un estudio actual.

 A partir del año 2016 se producen mejoras significativas en los traductores automáticos. En efecto, ese año Google Translate revolucionó su funcionamiento lanzando una traducción automática basada en redes neuronales (cf. Lee, 2021: 2), y un año después se presentó DeepL. Teniendo en cuenta que la difusi= ón de las nuevas tecnologías entre los usuarios no es inmediata y que la realización y publicaci= ón de estudios empíricos requiere un tiempo considerable, podemos concluir que se= rán relevantes los trabajos publicados a partir del año 2018 en los que empieza= a reflejarse este avance (p. ej.  Zha= ng y Torres-Hostench 2019: 159). <= /p>

Una constatación general que queda reflejada en prácticamente toda la literatura sobre el te= ma, independientemente de sus condiciones y su orientación específica, es el ma= sivo incremento del uso de los traductores automáticos para resolver dudas lingüísticas entre los aprendientes de lenguas extranjeras. Ya en 2016, o s= ea en el mismo año que antes hemos indicado como referencia, Cassany califica = el traductor como «recurso más popular … en situa= ciones de lectura en L2 y de escritura en L1/L2»= (2016: 7) entre preuniversitarios españoles. Dos años después, Ducar y Schocket hablan incluso de una «omnipresence of GT ([google translate] in L2 student = work» (2018: 779), refiriéndose a un contexto = estadounidense, = pero seguramente extrapolable a muchos otros países (occidentales).

Con la mejora d= e los traductores automáticos y su uso cada vez más frecuente ha cambiado también= la valoración que reciben como recurso en el aula de lenguas extranjeras. En 2= 005 Niño aún hablaba de un «arma de doble filo= » (2005: 2) y de= «la baja calidad lingüística a la que, sobre todo los traductores automáticos e= n línea, nos tienen acostumbrados»= (2005: 5). Act= ualmente, en cambio, se ven cada vez más sus posibilidades didácticas (p. ej., Enkin y Mejías Bikandi, 2= 016) y su potencial en la mejora de las producciones lingüísticas (O’Neill, 2019a). Algunos autores hablan incluso de un «giro traductológico en la enseñanza de segundas lenguas» (Carreres et al., 2017: 99). Sin embargo= , todo apunta a que una condición previa para que estas mejoras se produzcan de una manera satisfactoria es un entrenamiento adecuado tanto de los aprendientes= como de los propios docentes (O’Neill, 2019a: 60; Gianetti<= /span>, 2016: 11-15). Igual que ocurre con los diccionarios, sean estos electrónico= s o impresos, demasiadas veces se presupone una competencia intuitiva a la hora de usar e= ste tipo de recursos (Egido Vicente, 2018: 81) y po= co se ha hecho hasta la fecha para examinar de cerca las estrategias usadas por aprendices de una lengua en el uso de los programas de traducción automátic= a (Fredholm, 2021: 11).

En este context= o nos parece especialmente relevante averiguar cómo se usan en la práctica los traductores: ¿se traducen realmente textos enteros, sintagmas aislados o se usan directamente como diccionarios según indican algunos trabajos (Kol, Schcolnik y Spector-= Cohen, 2018: 54 y s.; Jiménez-Crespo, 2017: 4)? Si el uso es paralelo al de los diccionarios, los problemas que se presentan al estudiante serán, en gran medida, los mismos que se plantean también en el manejo de estos, en primer lugar, la elección equivocada del término equivalente en la lengua meta (Egido Vicente, 2018: 78). Tampoco se podrá aprovechar= buena parte de las ventajas del traductor, como la corrección gramatical, la mayor fluidez en la expresión escrita, etc. (Lee, 2021: 2). Además, el traductor automático soluciona a menudo dificultades lingüísticas que los usuarios ni siquiera detectan. Es por ello que, renunciando = a su uso, el usuario se priva de la posibilidad de obtener una solución frente a= dificultades lingüísticas que pasan desapercibidas – algo que en otros trabajos se const= ató como una importante fuente de errores (Gromann = y Schnitzer, 2016: 87).

Una herramienta= que combina las características de un diccionario bilingüe con la exposición de contextos de usos auténticos en varios idiomas son los buscadores de traducciones como Linguee o Reverso <= span class=3DSpellE>Context. Además de proporcionar equivalencias y o= tra información lexicográfica, estas herramientas suministran ejemplos de traducciones que contienen la palabra o expresión buscada. No compartimos la opinión de Buyse de que «al usuario casi se le = obliga a mirar el contexto en el que se encuentran las traducciones» (2014: 105), sino que pensamos que muchos usuarios solo se fijan en la prim= era parte en la que figuran las equivalencias. Sin embargo, no cabe duda de que= en principio son un buen instrumento que ofrece la posibilidad de ver usos rea= les en contexto. El único estudio que conocemos sobre la utilidad de esta herramienta arroja resultados ligeramente mejores para Linguee en comparación con diccionarios tradicionales y, sorprendentemente, también= con la combinación de Linguee y diccionario bilingüe (Buyse y Verlinde, 2013). <= /span>

Las investigaci= ones que comparan el uso de traductores automáticos y diccionarios en la enseñan= za de idiomas son mucho más abundantes. Sin embargo, aparte de las reservas ya= formuladas al principio de este apartado, adoptan perspectivas muy diferentes. Primero, encontramos trabajos que versan sobre las actividades de traducción en clas= e de lengua (p. ej. Fernández Guerra, 2014) o enfocan mediante cuestionarios el = uso de las distintas herramientas y, sobre todo, la valoración que reciben por parte de los estudiantes (p. ej. O’Neill, 2019b; Conde Noguerol, 2017). El segundo grupo de estudios valora los resultados conseguidos con o sin tradu= ctor automático en tareas realizadas por distintos grupos de estudiantes. Por lo tanto, estos serían los indicados para una comparación. Curiosamente, gran parte de esta literatura que investiga la influencia de traductores automát= icos se centra en muy diversas tareas o ejercicios de lengua, pero no en la traducción de textos. Así, para dar tan solo algunos ejemplos recientes, se enfoca la efectividad de los traductores automáticos para contestar pregunt= as de vocabulario (Omar, 2019) o para la redacción de diferentes tipos de texto (Chung y Ahn, 2021; Fredho= lm, 2021). No hemos encontrado trabajos que se basen en una tarea de traducción= de textos de especialidad. Es por ello que las posibilidades de relacionar los resultados propios con los de otros trabajo= s son bastante limitadas. En cualquier caso, la tónica general de la literatura existente sobre el tema indica que, hoy por hoy, si se compara la ayuda real que prestan traductores automáticos y diccionarios a los usuarios, son los primeros los que se revelan como más eficientes, especialmente en lo que se refiere a textos pertenecientes a ámbitos específicos (Lee, 2019: 170).

 

 

3. Contextualización del estudio= y metodología

El estudio se r= ealizó en el marco de una institución dedicada a la enseñanza de ENE (Español de l= os Negocios), la Universidad de Ciencias Económicas y Empresariales de Viena (= WU, Wirtschaftsuniversität Wien). Por lo tanto, los textos con los que trabajamos en nuestras asignaturas sue= len ser en su inmensa mayoría de temática económica.

 

3.1. Tareas – tipos de texto

De entre los distintos ámbitos temáticos escogimos, en primer lugar, la terminología corporativa, en forma de un orden del día de una junta general de accionist= as; en segundo lugar, la terminología comercial, en forma de un mensaje de corr= eo electrónico con un pedido de mercancía. El primer tipo de texto no se traba= ja en absoluto en nuestras clases; el segundo sí, pero en ambos casos la terminología no debería ser del todo desconocida. Al mismo tiempo, tratamos= de escoger textos que, en lo que se refiere a su grado de especialización, constituyeran un reto para nuestros estudiantes para «obligarles» precisamente a usar recursos lexicográficos. En nuestra opinión, los textos escogidos presentaban un alto grado de dificultad léxica, sin embargo, las tareas eran realizables a condición de usar adecuadamente los recursos lexicográficos disponibles. Las tareas (una traducción del español al alemá= n y otra del alemán al español; véase anexo 1) correspondían a situaciones real= es que en alguna ocasión se habían presentado a antiguos estudiantes de esta institución en su actividad profesional. Las tareas de traducción, además, = se contextualizaron describiendo la situación en la que surgieron y la finalid= ad concreta de cada una, tal y como se habían presentado en la realidad. =

 

3.2. Tareas – recopilación de datos

 =

La realización = de las tareas se documentó de manera electrónica, grabando en su totalidad las distintas consultas y la traducción. Para ello se utilizó la aplicación Steps Recorder,= que proporciona una captura de pantalla de cada paso en el proceso de búsqueda = y redacción. No hubo restricción alguna en cuanto al tipo de recurso utilizado, ni al ti= empo invertido en las tareas. Finalmente, hay que añadir que no hubo en ninguna ocasión consultas a recursos que no fueran electrónicos, habiendo desaparec= ido el diccionario impreso de nuestro contexto de enseñanza.<= /p>

Las primeras grabaciones se realizaron individualmente en las instalaciones de la universidad a principios del año 2020. Desafortunadamente, después de la participación de 32 personas, la crisis del coronavirus y las semanas de confinamiento imposibilitaron seguir con este sistema. La obtención de dato= s se vio interrumpida durante varios meses, puesto que nuestra intención era pod= er seguir con el mismo sistema de recogida de datos algunas semanas después. A principios del semestre de invierno 2020 decidimos cambiar de método de recogida de datos y, para ello, confeccionamos unas indicaciones para que l= os estudiantes realizaran el test individualmente e= n sus casas y nos hicieran llegar las tareas y las grabaciones. No hubo restricci= ones respecto a los recursos utilizables ni limitaciones de tiempo y también en = caso de que el test se realizara en casa quedaban registrados todos y cada uno de los pasos en el programa mencionado. Los da= tos, independientemente de en qué fase hayan sido obtenidos, son homogéneos y se pueden, por tanto, analizar conjuntamente. Esto se comprobó tomando como referencia el porcentaje de errores por sintagma en los individuos de ambos grupos. El test t de Studen= t mostró que no hay diferencia significativa entre los resultados de la prime= ra y la segunda fase para ninguna de las dos tareas (tarea 1 p=3D.182572; tarea 2 p=3D.106486), y es por ello que se procedió al análisis de los datos como m= uestra homogénea.

 

3.3. Participan= tes y análisis de los datos

 

De los 75 test = realizados, ocho no se pudieron valorar por ser incompletos o resultar las grabaciones defectuosas. Después de eliminarlos, nuestra muestra está formada por un to= tal de 67 tareas de traducción, realizadas por estudiantes universitarios de le= ngua materna alemana con un nivel de competencia en español B1+ / B2 del MCER. La franja de edad de los participantes (42 mujeres, 25 hombres) oscila entre l= os 20 y 23 años.

El análisis de = las traducciones se realizó de la manera siguiente: en un primer paso, los text= os se dividieron en sintagmas, según la forma en la que se había fragmentado el texto en las búsquedas. El resultado fue un total de 18 sintagmas para la primera parte y 15 para la segunda (véase anexo 2).

A continuación,= se analizaron las grabaciones de cada proceso de traducción. Para ello, se cuantificaron tanto las búsquedas como las consultas realizadas. Utilizamos aquí el término búsqueda para referirnos a la duda o pregunta que se quiere resolver; una misma búsqueda puede, sin embargo, dar lugar a varias = consultas, por ejemplo, cuando se usan varias herramientas para intentar encontrar la respuesta, o la misma de diferentes maneras. Además, se anotaron los recurs= os utilizados por cada estudiante en cada sintagma y se registraron los aciert= os y errores cometidos en cada caso.

 

 

4. resultados =

En la traducció= n de los 33 sintagmas analizados (18 pertenecientes al primer texto, 15 al segun= do) los 67 participantes realizaron, en total, 2688 consultas en distintas herr= amientas.  Esto significa un promedio de 40 consulta= s por estudiante. En aquellos casos en los que se tradujo el texto en su totalidad mediante un traductor automático, se asignó una consulta a cada uno de los sintagmas.

 

4.1. Número de consultas por herramienta

 

La tabla 1, que figura a continuación, muestra el reparto de las consultas entre las distin= tas herramientas y compara los porcentajes respectivos con los correspondientes= a los estudios de 2016 (Gromann y Schnitzer, 2016) y 2019 (Pérez Cañizares y Schnitzer, 2019= ) mencionados en la introducción.

 

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin;color:black; mso-themecolor:text1;mso-font-kerning:12.0pt;mso-fareast-language:DE'>201= 6

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin;color:black; mso-themecolor:text1;mso-font-kerning:12.0pt;mso-fareast-language:DE'>201= 9

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin;color:black; mso-themecolor:text1;mso-font-kerning:12.0pt;mso-fareast-language:DE'>202= 1

Diccionario bilingüe

92<= /span>

47<= /span>

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-fareast-font-family:Calibri;mso-bidi-font-family:Calibri;mso-bidi-the= me-font: minor-latin;color:black;mso-themecolor:text1;mso-font-kerning:12.0pt; mso-fareast-language:DE'>26

Traductor automático

1

4

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-fareast-font-family:Calibri;mso-bidi-font-family:Calibri;mso-bidi-the= me-font: minor-latin;color:black;mso-themecolor:text1;mso-font-kerning:12.0pt; mso-fareast-language:DE'>41,5

Lin= guee/Re= verso Context

2

32<= /span>

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-fareast-font-family:Calibri;mso-bidi-font-family:Calibri;mso-bidi-the= me-font: minor-latin;color:black;mso-themecolor:text1;mso-font-kerning:12.0pt; mso-fareast-language:DE'>22

Otros

4

16

<= span style=3D'font-size:10.0pt;line-height:106%;font-family:"Verdana",sans-ser= if; mso-fareast-font-family:Calibri;mso-bidi-font-family:Calibri;mso-bidi-the= me-font: minor-latin;color:black;mso-themecolor:text1;mso-font-kerning:12.0pt; mso-fareast-language:DE'>10,5

Tabla 1. Comparación de consultas realizadas en los diferentes recursos en 2016, = 2019 y 2021 (en porcentajes)

 

Se puede consta= tar una tendencia clara: en tan solo cinco años, los traductores automáticos han pasado de ser una herramienta absolutamente marginal a = constituir, con diferencia, el recurso más usado. Otra tendencia evidente es que este aumento se produce a costa del diccionario bilingüe tradicional, que ha pas= ado de una posición prácticamente de monopolio a ocupar un segundo lugar, casi = al mismo nivel que los buscadores de traducciones. Estos últimos, para el análisis, presentan la dificultad de que, con las grabaciones realizadas, n= o permiten determinar hasta qué punto los participantes consultaron realmente las traducciones que se dan como ejemplo de uso o se limitaron a la parte de diccionario bilingüe (esto último, obviamente, aumentaría el peso de los diccionarios bilingües). Volveremos sobre este punto en la sección 5.<= /o:p>

 

4.2. Perfiles de búsqueda de los usuarios

 

Después de regi= strar las consultas realizadas y constatar que la mayoría de los aprendientes aplicaba en sus búsquedas un patrón determinado, clasificamos a los partici= pantes en cuatro grupos según su comportamiento. En primer lugar, aparecen los llamados traductores, que muestran un uso predominante de traductores automáticos, es decir, de Google Translate o DeepL. A continuación, figura el grupo de los = que denominamos lexicógrafos, que usan predominante= mente diccionarios bilingües, en su inmensa mayoría Pons o Leo. Finalmente, están los usuarios de Linguee, un grupo que utiliza sobre todo buscadores de traducciones, es decir, Linguee o, en menor medida, Reverso Context. El criterio de pertenencia a un grupo determinado fue haber realizado más del 50% de las consultas en un recurso o una diferencia de uso de los recursos de, por lo menos, 20 puntos porcentua= les. De hecho, estos perfiles resultaron bastante marcados, puesto que solo en un único caso el recurso dominante no llegó al 50% de todas las búsquedas. Los estudiantes que no mostraron ninguna preferencia clara y que consultaron va= rios recursos con frecuencias comparables fueron clasificados como mixtos= . Una única persona tuvo un comportamiento diferenciado, cambiando radicalmente de estrategia según la dirección de la traducción: en concreto, usó Linguee para la traducción del español al alem= án y DeepL para la traducción del alemán al español. El reparto de los participantes en el estudio según los distintos perfiles de búsqueda se muestra en el gráfico 1.

 

3D"Chart,

Gráfico 1. Perfiles de búsqueda de los usuarios

 

Como se puede comprobar, predomina la traducción automática por encima del uso de diccionarios. Esta preferencia general por un tipo de recursos en particular está directamente ligada al factor tiempo. El uso de un traductor automátic= o, como es lógico, permite realizar la tarea más rápidamente, según se puede comprobar en el gráfico 2, que muestra el tiempo medio invertido en la traducción de los dos textos según el tipo de usuario (en minutos).

 

3D"Chart,

Gráfico 2. Tiempo medio de realización de las tareas (en minutos) según perfiles

 

4.3. Errores en= la traducción según uso de recursos

 

3D"Chart,
El criter= io más importante a la hora de comparar la ayuda efectiva que prestan las distintas herramientas usadas es, sin duda, la calidad de las traducciones realizadas= .

 

3D"Chart,

Gráfico 3. Media de errores por perfil de usuario 

 

En el gráfico 3= se presentan las medias de los errores léxicos totales, clasificados en: error= es cometidos tras una búsqueda específica (tonos oscuros) y errores sin búsque= da (tonos claros) según el tipo de usuario. Vemos que, por término medio, respecto a = la corrección de la traducción son los usuarios con perfil traductor los que consiguen los mejores resultados, a pesar de que en este cómputo solo se han tenido en cuenta los errores de selección léxica. Si a este tipo de err= or se añadieran otros, como por ejemplo los de morfología y selección de modo ver= bal, de concordancias o de orden sintáctico, el balance sería aún mucho peor para las demás herramientas. También se ve que entre los traductores el número de errores tras búsqueda es el que más se acerca al número total de errores, lo que significa que los programas de traducción ayudan a evitar errores en aspectos que los usuarios de diccionarios, de buscadores de traducciones o los que combinan recursos no consultan. En otras palabras, la traducción automática contribuye a evitar problemas que, con otras estrateg= ias de búsqueda, ni se perciben.

 

4.4. Formas de = uso de los traductores automáticos

 

Como hemos apun= tado ya en el apartado 2, a la hora de utilizar programas de traducción automáti= ca, los usuarios pueden proceder de maneras diferentes. A partir del análisis de nuestros datos hemos distinguido tres tipos de usos: la traducción de textos completos o de frases enteras; la traducción de sintagmas y, finalmente, la= de palabras aisladas. Es cierto que los límites entre estos tres grupos son bo= rrosos y que a menudo los rasgos característicos se combinan (por ejemplo, un estudiante que entra una frase entera en un programa de traducción, pero después verifica un sintagma concreto en otro, etc.). No obstante, es posib= le detectar comportamientos típicos que, al menos, indican tendencias. A la lu= z de los resultados hasta ahora expuestos sería esperable que aquellos estudiant= es que ingresan el texto completo (o frases enteras) en su programa de traducc= ión deberían ser tanto los más rápidos como los que mejores resultados consigan. Sin embargo, en contra de esta hipótesis intuitiva, esto no es así. La tabl= a 2 recoge los tiempos invertidos y los resultados conseguidos en nuestro test según la manera de usar los programas de traducción.

 

<= b>Estrategia

= Núm= ero

= Tie= mpo medio

= Med= ia de errores totales

Med= ia de errores tras búsqueda

Traduce frases o texto entero

15

19,9

4,6

4,3

Traduce sintagmas

4

25,5

5,5

3,5

Usa el traductor como diccionario =

6

29,3

5

1,8

 

Tabla 2. Distintos usos del traductor, tiempo invertido (en minutos) y media de errores totales y tras búsqueda

En esta tabla destaca, en primer lugar, el gran número de participantes que usan el progr= ama de traducción realmente como herramienta para traducir textos o, por lo men= os, frases enteras y el número relativamente bajo de ellos que lo usa como si se tratara de un diccionario electrónico. No es sorprendente que los primeros = sean mucho más rápidos que los otros dos grupos.

Respecto a la p= osible correlación entre la forma de usar el traductor y el número de errores, los datos con los que contamos no muestran más que una pequeña diferencia entre= los tres grupos, puesto que el número de errores totales es casi el mismo. A primera vista puede llamar la atención que la media de errores tras búsqued= a es mayor para los que traducen el texto entero (o frases enteras) y más reduci= da para los que lo usan como diccionario. Sin embargo, estos mejores resultados no = son atribuibles a búsquedas más exitosas, sino exclusivamente al menor número de búsquedas realizadas por aquellos estudiantes que usan el traductor como diccionario. No hemos podido detectar diferencias en cuanto a la tipología = de los errores o en cuanto a los sintagmas que los provocan.

 

4.5. Grado de dificultad de los sintagmas analizados

 

Fijándonos en l= os sintagmas que nuestros estudiantes han buscado en los respectivos recursos,= constatamos que el grado de dificultad que estos presentan es variable (para un listado exhaustivo, véase Anexo 3). El gráfico 4 muestra una clasificación de los sintagmas de acuerdo con este criterio. En primer lugar, hay un buen número= de estos (un 42%) que no ofrecen mayores dificultades y para los que cualquier herramienta ofrece una traducción satisfactoria. Un número igual de sintagm= as (otro 42%) produce una tasa de errores de entre un 10 y un 50% tras búsqueda, es decir, que los recursos consultados brindan una ayuda en función de la selección de la herramienta, la manera de usarla y la capacidad del estudia= nte de procesar la información encontrada. Por último, queda un 16% de sintagmas que acaban en error en más de la mitad de las ocasiones. Por distintas razo= nes, las herramientas al alcance de los aprendientes no dan una solución satisfactoria para traducir en este contexto sintagmas como, por ejemplo, <= i>consejeros o informe de gestión. Estos sintagmas pertenecen a un grupo que escapa incluso a las posibilidades de los programas de traducción que, en e= ste punto concreto y para el objetivo y el contexto situacional específico en la que se enmarca la tarea, no suministran la traducción adecuada.<= /span>

 

Gráfico 4. Clasi= ficación de los sintagmas según el grado de dificultad que supone su traducción

 

 

5. Conclusiones

Antes de extraer conclusiones de nuestro estudio, conviene recordar el contexto en el que se= ha realizado, así como la metodología usada. Solo de este modo será posible determinar su alcance y hasta qué punto sus resultados son extrapolables a otros grupos de usuarios.

En primer lugar= , el estudio se realizó con textos especializados del ámbito de los negocios y a partir de él no es posible saber si los resultados son generalizables para usuarios que se enfrenten a textos de lenguaje general o de otra especialid= ad. En segundo lugar, las lenguas analizadas han sido el español peninsular y el alemán. Es bastante probable que, con una combinación de lenguas diferente = y, quizás hasta con otras variedades<= span style=3D'font-size:11.0pt'>, cambie la situación. Finalmente, como in= put se proporcionaron textos enteros (aunque en el primero solo había que tradu= cir partes de un texto), lo que parece lógico cuando se trata de medir la eficiencia de un programa de traducciones.

Si ahora contra= stamos los resultados conseguidos con lo expuesto en el apartado 2, podemos confir= mar el incremento masivo y acelerado de los programas de traducción automática = que, de hecho, parece imparable. También hemos verificado la, en general, muy bu= ena calidad de las traducciones producidas que, por término medio, supera la conseguida por nuestros estudiantes con otras herramientas. Estos, en contr= a de lo que postulan otros estudios sobre el tema (Kol, Schcolnik y Spector-Cohen, 2018: 54), no usan los traductores automáticos como sustitutos de diccionarios, sino han pasado a usarlos mayoritariamente para traducir frases, párrafos o textos enteros. E= sta estrategia es más eficiente en cuanto al tiempo necesario para la traducció= n, sin repercutir, además, en los resultados conseguidos. En cuanto a la eficienci= a de los buscadores de traducciones, no podemos confirmar su mayor eficiencia respecto a los diccionarios (en nuestro estudio los resultados son ligerame= nte peores), pero admitimos que por una cuestión de metodología persiste una inseguridad sobre hasta qué punto realmente se han usado como tales y hasta= qué punto se han usado como diccionarios.

Los resultados = de nuestro estudio tienen dos tipos de implicaciones: lexicográficas (en un sentido amplio) y didácticas. Respecto a las primeras, pensamos que la tendencia que venimos observando desde hace bastante tiempo de combinar cada vez más recursos disponibles deberá no solo continuar, sino intensificarse.= Es deseable la combinación de programas de traducción con información lexicográfica (en el sentido tradicional), pero también enciclopédica, pues= to que esta última es la que muchas veces es necesaria para resolver problemas para los que los traductores no dan aún respuesta. El gran reto para el desarrollo de estas herramientas será conseguir una combinación, estructura= ción y presentación de una enorme cantidad de información que sea manejable para= el usuario.

Para los docent= es de Español de los Negocios, el segundo tipo de implicaciones es más urgente e inmediat= o. El análisis de los datos y los resultados apuntan a un replanteamiento del peso que deberían tener en el aula de lenguas extranjeras determinadas actividad= es clásicas (p. ej. la redacción o la lectura de ciertos tipos de textos). Se ha puesto= de manifiesto que, si alguna de estas necesidades comunicativas se presenta fu= era del aula, hay aplicaciones que dan una respuesta más rápida y de mayor cali= dad que la que podrían dar nuestros estudiantes con un dominio de B2 al final d= e su aprendizaje sin recurrir a estas herramientas. Y, efectivamente, su uso par= ece responder a las necesidades concretas del ámbito empresarial (Kölbl, 2020).

 Precisamente por esta razón debemos hacer hincapié en la necesidad de tematizar el empleo de los distintos recursos lexicográficos. Un manejo correcto de las herramientas - unido a la capacid= ad de hacer una valoración crítica respecto a las diferentes propuestas que of= rece un traductor y sus limitaciones - provocaría, sin duda, una mejora en la calidad de los textos producidos. Según los datos de este estudio, la traducción de un 42% de los sintagmas podría mejorar a partir de un uso competente de los recursos.

 Los grandes retos para los docentes y la didáctica de lenguas extranjeras consistirán en, primero, estar continuamen= te al día en la oferta y manejo de este tipo de herramientas. A continuación, hab= rá que encontrar una manera de transmitir esta experiencia de uso de una forma motivadora y, al mismo tiempo, eficiente. ¿Por qué la insistencia en la eficiencia? Porque mostrando el uso razonable de estas herramientas, enseña= mos a nuestros estudiantes a resolver situaciones de comunicación concretas. Co= mo esta es nuestra tarea, debe ser una parte integral de nuestros programas. S= in embargo, tanto docentes como aprendientes tienen que ser conscientes de que= un traductor automático puede ayudar a los usuarios a resolver estas necesidad= es comunicativas concretas, pero que su simple uso no implica automáticamente = ni el aprendizaje de una lengua ni el acercamiento a su cultura.

 

 

 

 

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Buyse, K., & Verlinde, S. (2013). Possible effects of free on line data driven lexicographic instruments on forei= gn language learning: The case of Linguee and the Interactive Language Toolbox. Proce= dia - Social and Behavioral Sciences, 95, 507–512. <= /a>https://doi.org/10.1016/j.sbspro.2013.10.675

Carreres, Á., Muñoz-Calvo, M., & Noriega-Sánchez, M. (2017). Translation in Spanish language teaching: the fifth skill/La traducción = en la enseñanza del español: la quinta destreza. Journal of Spa= nish Language Teaching, 4= (2), 99109.

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Ducar, C., & Schocket, = D. (2018). Machine translation and the L2 classroom: Pedagogi= cal solutions for making peace with Google translate. Foreign Language Annal= s, 51(4), 779795. https://doi.org/10.1111/flan.12366

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Enkin, E., & Mejías-Bikandi, E. (2016). Using Online Translators i= n the Second Language Classroom: Ideas for Advanced level Spanish. Latin Ameri= can Journal of Content & Language Integrated Learning, 9(1), 138158.

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Fernández Guer= ra, A. B. (2014). The usefulness of translation in foreign language learning: Students’ attitudes. International Journal of English Language & Translation Studies, 2(1), 153= 170.

Fredholm, K. (2021). Google Translate search strategies used by learners of Spanish L3: A complex lexico-morpho-syntactic weave of trial = and error. Estudios de Lingüíst= ica Aplicada, 72, 948. https://doi.org/10.22201/enallt.0185264= 7p.2021.72.926

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ANEXOS

Anexo 1 – Test

Texto 1 – Convocatoria de una junta general

Sie arbeiten in einem mittleren Unternehmen, dessen Geschäftsführer Aktionär einer spanischen Firma ist. Er= hat eine Einladung zur Hauptversammlung dieser Form erhalten. Sein Spanisch ist= ganz gut, er hat verstanden, wann und wo die Versammlu= ng stattfinden wird. Er bittet Sie jedoch, die Tagesordnung für ihn zu überset= zen und ihm zu sagen, welche Dokumente er von der Gesellschaft anfordern kann (diese Teile sind im Text grau hinterlegt).

[Usted trabaja en una empresa mediana, cuyo ger= ente es accionista de una empresa española y ha recibido la siguiente invitación= a una junta general de accionistas. Su jefe habla bien español y ha entendido, cuándo y dónde se celebrará la junta, pero le ha pedido que le traduzca el orden del día para saber qué documentos recibirá de la sociedad (las partes están marcadas en gris)].

 

Convocatoria de junta de accionistas

 

 

El Consejo de Administración de esta Sociedad, en uso de las facultades que le confieren = sus Estatutos Sociales, ha acordado convocar a los señores accionistas a Junta General de Accionistas, que se celebrará en XY, en el domicilio social, el = día XXX, a las 12.00 horas para tratar de los asuntos comprendidos en el siguie= nte:

 =

Orden del día:

 =

Examen y aprobación, en su caso, de las Cuentas Anuales y la gestión del Consejo de Administración del ejercicio 2017.=

Distribución del resultado.

Cese, renovación, nombramiento y/o ratificación de Consejeros.

Delegación de facultades.

Ruegos y preguntas.

Lectura y aprobación, si procediera, del Acta de la Junta.

 =

Los accionistas tienen derecho a obtener de la sociedad, de forma inmediata y gratuita, los documentos a que se refiere el punto Primero del Orden del Día, así como el= Informe de Gestión y el Informe d= e los Auditores de Cuentas.

 =

 =

XX, a xx de 2019, la Secretaria del Consejo de Administraci= ón.

 =

&nb= sp;

 

Texto= 2 – Pedido de mercancía

Sie arbeiten für einen österreichischen Weinimporteur, der weitere argentinische Weine in sein Angebot aufnehmen will. Sie werde= n gebeten, folgenden = Text ins Spanische zu übertragen.

 

[Usted trabaja en una empresa austríaca de importación de vinos, que quiere aumentar su oferta de vinos argentinos. Se= le ha pedido traducir el texto siguiente al español.]

 

 

Sehr geehrter Herr Sánchez!

 

Wie telefonisch besprochen, möchten wir unsere Produktpalette erweitern= und bitten Sie daher um die Übersendung von 500 Kisten zu 12 Flaschen Chardonnay Catena 2000 zum Gesamtpreis von US$ XXX.

<= span lang=3DEN-US style=3D'font-size:10.0pt;font-family:"Verdana",sans-serif;mso= -ansi-language: EN-US'>Versand per Schiff, CIF Hamburg.

Nach Erhalt einer Proforma-Rechnung werden = wir unsere Bank mit der Eröffnung eines Dokumentenakkreditivs zu ihren Gunsten beauftragen.

Hochachtungsvoll,

 

XY

Importabteilung

 

&nb= sp;

Versión en e= spañol

 

Estim= ado Sr. Sánchez:

 

Como hemos hablado por teléfono, nos gustaría ampliar nuestra gama de productos = y, por lo tanto, le pedimos que nos envíe 500 cajas de 12 botellas de Chardonn= ay Catena 2000 a un precio total de XXX dólares.

Envío= por barco, CIF Hamburgo.

Una v= ez recibida la factura proforma, daremos instrucciones a nuestro banco para que abra un crédito documentario a su favor.

Atent= amente,

=  

XY

Depar= tamento de Importación

 

 

AN= EXO 2 – LISTADO DE SINTAGMAS ANALIZADOS

 

Sintagmas texto 1<= /span>

Examen y aproba= ción de las Cuentas Anuales

en su caso

La gestión

Consejo de Administración

ejercicio =

Distribución del resultado

Cese,

renovación,

nombramiento

ratificación

Consejeros.

Delegación de facultades

Ruegos y pregun= tas

Lectura y aprob= ación

si procediera

Acta de la Junt= a

Informe de Gest= ión

Informe de los Auditores de Cuentas

 

Sintagmas text= o 2

Sehr geehrter Herr

Wie telefonisch besprochen

Produktpalette

erweitern

bitten Sie daher um die Übersendung

500 Kisten zu 12 Flaschen Chardonnay Catena 2000

zum Gesamtpreis von US$ XXX.

Versand per Schiff, CIF Hamburg.

Nach Erhalt einer Proforma-Rechnung

werden wir unsere Bank beauftragen

mit der Eröffnung

Dokumentenakkreditiv

zu Ihren Gunsten

Hochachtungsvol= l

Importabteilung=

 

Anexo 3 – Clasificación de los sint= agmas por grado de dificultad

 <= /span>

Categoría 1 - muy pocos errores tras búsqueda

N.° de búsque= das

Errores tras búsqueda

46

0

30

1

48

3

41

4

52

5

zum Gesamtpreis von US$ XXX.

41

1

bitten Sie daher um die Übersendung =

55

2

Hochachtungsvoll

39

2

Importabteilung

39

2

mit

48

3

Produktpalette

48

4

Nach Erhalt einer Proforma-Rechnung

58

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Dokumentenakkreditiv

64

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58

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61

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46

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38

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45

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44

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52

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54

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500 Kisten zu 12 Flaschen Chardonnay Catena

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Categoría 3 - más de un 50% de búsquedas acaba en e= rror

N.° de búsque= das

Errores tras búsqueda

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52

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21

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