Corpora have given rise to a wide range of lexicographic resources aimed at helping novice users of academic English with their writing. This includes academic vocabulary lists, a variety of textbooks, and even a bespoke academic English dictionary. However, writers may not be familiar with these resources or may not be sufficiently aware of the lexical shortcomings of their emerging texts to trigger the need to use such help in the first place. Moreover, writers who have to stop writing to look up a word can be distracted from getting their ideas down on paper. The ColloCaid project (www.collocaid.uk) aims to address these problems by integrating information on collocation with text editors. In this paper, we share the research underpinning the initial development of ColloCaid by detailing the rationale of (1) the lexicographic database we are compiling to support the collocation needs of novice users of English for Academic Purposes (EAP) and (2) the preliminary visualisation decisions taken to present information on collocation to EAP users without disrupting their writing. We conclude the paper by outlining the next steps in the research.

In metalexicographical research, experts have judged the performance of technologies such as OpenAI Generative Pretrained Transformer (GPT) in lexicographic production tasks as promising yet inferior to human lexicographers. It remains unclear whether this perceived inferiority limits the effectiveness of AI-generated lexicography in resolving practical language doubts. Accordingly, this study compares the effectiveness of AI-generated definitions to those from the Macmillan English Dictionary (MED) in resolving vocabulary doubts in a multiple-choice reading task designed to test lexical knowledge. It involves 43 L2 English users in the third year of an English studies degree at a Spanish university. Students provided with MED definitions performed better on the reading task than those without access to definitions. However, there was no significant difference between the performance of students with either MED definitions or without definitions altogether, and those provided with AI-definitions. The implications of these findings are discussed along with avenues for further research.

This short paper summarizes the development of ColloCaid (www.collocaid.uk), a text editor that supports writers with academic English collocations. After a brief introduction, the paper summarizes how the lexicographic database underlying ColloCaid was compiled, how text editor integration was achieved, and results from initial user studies. The paper concludes by outlining future developments.

Making information about language accessible to users has long been a key concern of lexicographic research. Adopting a narrower perspective, this examination of three dictionary websites (collinsdictionary.com, merriam-webster.com, and dle.rae.es) employs the Web Content Accessibility Guidelines (WCAG) to examine their accessibility for people with visual impairments. Dictionaries can be motors for social inclusion of this oft-marginalised group since, beyond resolving language doubts, they can also help affirm socio-cultural identities. Unlike paper dictionaries where space-saving conventions make accessibility a challenge, in principle, online resources are adaptable to the needs of users with visual impairments. In practice, although none of the websites evaluated meet any officially recognised WCAG conformance level, they do contain features aimed at improving accessibility for this group. Most impediments to accessibility are the result of ancillary elements such as advertising, social media, games, and word of the day features. Although these ancillary elements may not necessarily be the principal focus of dictionary use, they nonetheless have a negative effect on the accessibility of the dictionary entry itself. This article concludes with suggestions for solving several of these accessibility issues.

The concept of the word family has been widely employed in research on vocabulary in the teaching and learning of foreign and second languages. The underlying assumption being that once learners know one member of a word family, they can recognise other members. Empirical research supports this vis-à-vis receptive knowledge of inflectionally related wordforms. However, studies of academic writing indicate that using appropriate derivative forms of a known word is challenging, suggesting a need for dictionaries with morphological support for writers. Traditionally, in paper-based dictionaries, this need could not be fulfilled due, in part, to space constraints. This study aims to establish if it is met in five online English dictionary websites. It analyses the treatment of seventy-four academic wordforms which academic writers have been shown to have difficulty deriving when presented with the related base word. Results indicate good coverage of the derivative forms across the dictionary websites examined but inconsistency within and between resources in the way in which forms are treated. Differences include the status as entries or subentries and the provision of writing support features such as examples, grammar patterns, and collocation information. Finally, changes to the treatment of derivatives to better serve academic writers are suggested. Keywords: academic writing, derivative forms, lexicography, morphology, online dictionaries, vocabulary acquisition, word families, writing support