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This paper reports on the results of a process-oriented longitudinal study focusing on the use of online translation resources by translation trainees during a specific human translation (HT) or post-editing (PE) task. It focuses on how students’ resource dominance changes over the four semesters of training: human translators’ and post-editors’ online resource use is also compared, as are students’ research strategies in terms of (1) the types of resources, (2) the frequency of resource use and (3) the time spent on resource consultation at the beginning and the end of their training.

Si le processus de postédition (PE) s’effectue en plusieurs étapes, il commence invariablement par la détection d’un problème, comme en attestent les modèles de compétence en PE. Dans un contexte didactique, si l’enseignement de la PE met l’accent sur cette phase du processus, faut-il en tenir compte lors de l’évaluation, quel que soit le produit fini ? Le cas échéant, comment reconnaître des détections qui n’ont pas conduit à une modification visible dans le produit fini (dénommées « simples détections ») et surtout, quel serait l’impact d’une telle méthode d’évaluation sur l’étudiant et sur la charge de travail de l’évaluateur ? Pour répondre à ces questions, nous avons mené une étude quasi expérimentale avec 15 étudiants effectuant une tâche de PE « retour » (du néerlandais, langue maternelle, au français, langue étrangère) tout en enregistrant leur processus avec un logiciel de saisie de frappes. Nos résultats montrent que les scores tenant compte de ces simples détections sont significativement plus élevés que les scores ne tenant compte que du produit fini. La différence est non seulement significative, mais elle permet aussi, selon le contexte, de passer de l’échec à la réussite. Par conséquent, pour l’étudiant, cette approche a une grande importance, tout comme pour l’évaluateur qui a désormais accès à un pan de compétence resté invisible jusqu’à présent. Par ailleurs, la méthode de travail s’avère relativement simple sans être trop chronophage, selon le temps disponible et le nombre d’étudiants à évaluer.

En aquest article descrivim un instrument de diagnòstic per avaluar la pràctica de la post-edició. Tot i que hi ha exemples d'aquests instruments a l'abast, rara vegada es fan servir els estudis empírics com a base per a avaluar-lo. Esperem que la nostra eina pugui ajudar a seleccionar professionals de la traducció o alumnat de traducció adequats per a projectes de post-edició amb la detecció dels coneixements, les competències o les actituds importants per fer aquesta feina i que fins ara  faltaven en el comportament dels aspirants a fer-la. In the present article, we provide an outline of a diagnostic tool for testing post-editing performance. The tool is hoped to facilitate the identification of suitable translators/translation students for post-editing projects by flagging knowledge, skills or attitudes relevant to post-editing that is/are found to be lacking in candidates' post-editing behaviour. En el presente artículo perfilamos una herramienta de diagnóstico para evaluar la práctica de la posedición. No es habitual que se utilicen estudios empíricos como base para su evaluación, a pesar de disponer de ejemplos de tales instrumentos. Esperamos que nuestra herramienta ayude a seleccionar profesionales de la traducción o alumnado de traducción adecuado para proyectos de posedición con la detección de conocimientos, competencias o  actitudes importantes para este trabajo que no se encontraban hasta ahora en el comportamiento de los aspirantes a desempeñarlo.

This paper explores the practical prospects for using artificial intelligence technologies in professional English-speaking translator education. At the online conference ‘Translation Skills in Times of Artificial Intelligence’ (DingTalk platform, January 2022), the teachers of higher education institutions in China prioritized the translator’s competencies necessary for successful professional activity during the digital transformation of social and economic business relations. The educators also evaluated the demand for online services used in the education of English–Chinese interpreters. The survey results showed that the use of artificial intelligence technologies in educational practices could have a significant impact on the development of key competencies of future translators. Using a competency-based approach to interpreter training and considering the need to develop abilities, knowledge, and skills required for successful professional translation activity, the author developed the pedagogical concept of the online educational course ‘Simultaneous and asynchronous translation in a digital environment.’

The present study examines how proficiency in the second language (L2) affects language learners’ ability to post-edit texts that are machine-translated from the learners’ native language (L1) to L2. More specifically, the study investigates how L2 proficiency level affects the degree to which Korean learners of English can discern the accuracy of L1-to-L2 machine-translated (MT) text and whether it affects the level of errors (word, phrase, clause, sentence) that are corrected in the post-editing process. Fifty-nine Korean university students’ proficiency was measured using a cloze test and a writing test. They were then given a source text (Korean) and a machine-translated text (English) and were asked to detect and correct as many errors as they can. The overall results of the study showed that L2 proficiency does have a significant effect on how language learners post-edit machine-translated output. With increasing proficiency, the number of corrections increased especially above the word-level, and significant group differences could be found in post-editing patterns of the MT text. The findings have important pedagogical implications for integrating MT activities in L2 classrooms with learners of different proficiency levels.

This research fundamentally examines how machine-generated translations of veterinary texts might be post-edited. Given the specialized terminology and knowledge required in veterinary texts, their translations must be conducted by an expert translator with a background in translations of veterinary texts or medical science. Proficiency in translation technologies is also essential for an effective post-editing process. Predictably, the primary audience for veterinary texts consists mainly of professionals in veterinary medicine, including academics and veterinarians. Nevertheless, additional target groups, including an intermediate readership, i.e. veterinary students, pet owners or even farmers without veterinary expertise (laymen), still seek information for specific circumstances. In this study, a specialized text from the Merck Veterinary Manual or MCV (Abdul-Aziz et al., 2016) was randomly selected, and the raw translation output was generated using Google Translate. Analysis revealed that Google Translate's initial translations were done in a sophisticated language, primarily targeting professionals. Based on this finding, it can be said that despite utilizing neural MT systems, Google Translate may tend to overlook the potential variability of other target audiences or groups. Therefore, unlike a human translator, who likely possesses contextual knowledge in advance, Google Translate might fail to adapt translations for distinct audience groups. The fact that the raw outputs of the MCV from Google Translate adhere to a semantic or literary translation, primarily targeting professionals, suggests that light post-editing may suffice for this audience most of the time because they possess prior knowledge or experience in veterinary medicine. In contrast, non-experts may require full post-editing to thoroughly comprehend the text.

This study aimed to investigate the impact of post-editing with machine translation (MT) in reading classes on students’ performance and perspectives across different English proficiency levels. Eighty-one students participated in the study and they were divided into two groups: 39students in the lower proficiency group and 42 students in the higher proficiency group. The research addressed two main questions: firstly, it explored how MT usage affects learners with varying English proficiency levels; secondly, it examined whether learners’ perspectives on MT use in reading classes differ based on their proficiency. Both quantitative and qualitative analyses were conducted using exam scores and questionnaire data. To address the first research question, pre- and post-reading test scores were analyzed. The findings revealed a substantial enhancement in reading comprehension for both groups. Moreover, there was a significant difference between the two groups. Regarding the second research question, a pre- and post-questionnaire was conducted. Both low and high proficiency groups acknowledged numerous advantages associated with MT use, with the low proficiency group exhibiting improvements across all aspects evaluated. Convenience and reduced burdens received the highest scores in both groups, positively influencing their active class participation. The research emphasized the advantages of incorporating machine translators into English reading classes, shedding light on positive outcomes for L2 reading.