Maha Al-Harthi

This article introduces the Saudi Learner Translation Corpus (SauLTC), an innovative multi-version English–Arabic parallel corpus featuring part-of-speech tagging. We describe the corpus parameters and compilation process and explain how textual processing and sentence alignment are conducted. The participants include 366 student translators, 48 instructors, and 23 alignment verifiers. The corpus provides access to two target versions of every ST to allow the detection of the changes in the translation and revision processes from the initial to the final draft. The translations were collected over three years, yielding 5,160,386 tokens. The metadata of 23 sentence alignment verifiers were added to the analysis as a unique variable to investigate individual differences in the manual verification process. This unidirectional corpus can be used to identify student translators’ strategies and errors in translation and analyze the efficacy of instructors’ feedback. Furthermore, it is accessible via an application and a website. It provides translation teachers and researchers with a database that can help develop corpus-based and corpus-driven teaching materials.

This study adopted a corpus-based, contrastive approach to lexical complexity in the academic writing of first language (L1) and second language (L2) postgraduates. Lexical complexity scores were extracted using the Lexical Complexity Analyzer from the Corpus of Arab Proficient Users of English (CAPUE), consisting of Saudi academics’ dissertations in applied linguistics. To investigate the potential differences between this corpus and native speakers’ corpus, the lexical complexity of writing material from the CAPUE and Corpus of English Native Speakers (CENS) were compared. The computational system employed 25 lexical complexity measures to investigate differences in the two groups’ lexical density, sophistication, and variation. The results revealed similar lexical density in the writing of both groups; however, the texts by L1 researchers were more lexically complex for most measures of sophistication and variation. The results have implications for teaching English for academic purposes and highlights areas with inappropriate lexical choices. These findings call for the design of pedagogical interventions to enhance the lexical complexity development of L2 postgraduates.