Developing the Academic Collocation List (ACL) – A corpus-driven and expert-judged approach

Abstract

This article describes the development and evaluation of the Academic Collocation List (ACL), which was compiled from the written curricular component of the Pearson International Corpus of Academic English (PICAE) comprising over 25 million words. The development involved four stages: (1) computational analysis; (2) refinement of the data-driven list based on quantitative and qualitative parameters; (3) expert review; and (4) systematization. While taking advantage of statistical information to help identify and prioritize the corpus-derived collocational items that traditional manual examination are unable to manage, we argue that only with human intervention can a data-driven collocation listing be of much pedagogical use. Focusing on lexical collocations only, we present a new Academic Collocation List compiled using a mixed-method approach of corpus statistics and expert judgement, consisting of the 2,468 most frequent and pedagogically relevant entries we believe can be immediately operationalized by EAP teachers and students. By highlighting the most important cross-disciplinary collocations, the ACL can help learners increase their collocational competence and thus their proficiency in academic English. The ACL can also support EAP teachers in their lesson planning and provide a research tool for investigating academic language development.