This project will study the Arabic as it was spoken in the first centuries of Islam. Researchers have argued that this moment in history was a watershed moment for the Arabic language. The massive confluence of the Arab tribes and the dramatic increase of second-language speakers during the Arab conquests would have changed the Arabic language drastically from the complex Pre-Islamic Arabic into a simplified common form. These theories have been based on inferences from later periods. Written sources from this early period have not been used to further the knowledge of the spoken language at the time. The ever-present dominance of Classical Arabic as the written language has made it difficult to evaluate early Islamic linguistic material. Xeno-Arabic – Arabic as found in transcriptions and texts of Arabic in non-Arabic scripts – is a source of data that gives insight into the Arabic vernacular. There is a large corpus of not previously studied Xeno-Arabic material datable to the first centuries of Islam. This material can provide new insights into the spoken language of the period. This material is not bound by the linguistic norms and orthography of Arabic in the Arabic script, and therefore more closely reflects Arabic as it was spoken by the Arabic speakers of the early Islamic society. With new insights provided by Xeno-Arabic, we will be able to re-evaluate the language found in the early Islamic papyri written in Arabic script. For the first time it will be possible to use direct evidence of early Islamic Arabic to fill in a gap in our knowledge of the history of Arabic. Combining this with our vastly improved knowledge of Pre-Islamic Arabic, we can use these direct attestations to re-examine the changes that Arabic underwent during these formative centuries of Islamic society.

In English, an interrogative phrase (or wh-phrase) has to be fronted in order to form a question (What did he ask?). In other languages, the wh-phrase remains "in situ", that is, in its original position (cf. French Il a demandé quoi? lit. "He asked what"?, meaning "What did he ask"?). Whereas French has both fronted and in-situ questions, some languages such as Mandarin Chinese only allow the in-situ strategy. In fronted wh-questions, the fronted wh-phrase indicates the clause type from the very beginning of the sentence. The syntactic literature has posited comparable structure for in-situ and fronted questions, in the sense that clause typing always occurs in a designated position high up in the structure. However, up to now it is unknown whether such clause typing is reflected in the prosody of wh-in-situ, nor do we know whether/how the parser anticipates the clause type of the in-situ questions. This project proposes an integrated and comparative study on the syntactic, semantic, prosodic and processing aspects of in-situ wh-questions, taking the Grammar-parser correspondence hypothesis (Phillips 1996, 2003) as a guiding principle. According to this hypothesis, the grammar and the parser are closely intertwined and the competence system of language is guided by grammatical constraints and rules. Given this, we expect that detailed prosodic analyses as well as data on processing will help us understand how clause typing is done in syntactic structure. At the same time it will allow us to verify different hypotheses made in the literature.

Online media affect not only what we believe to be true or false, but also which questions we entertain, what we are curious or uncertain about. Such questions may, in turn, increase our vulnerability to disinformation: people more readily believe a lie if it answers a question they already had. This project will use the millions of questions posted on social media as a window onto our collective curiosity, to investigate, among other things, whether a surge in disinformation is preceded by changes in our curiosity.

A great amount of research has been conducted on the subject of multilingualism and its many advantages: languages unite people, strengthen intercultural understanding, play a vital role in enhancing employability and mobility, thereby offering economic, political and development benefits. However, there is still a long way to go to achieve a multilingual reality and bridge the gap between theory and practice. The proposed three-day conference will bring together scholars and practitioners from The Netherlands, India and elsewhere to discuss the newest insights from research, their implementation into language and education policies and to set up future collaboration.

Leiden University’s Faculty of Humanities is dedicated to the idea that the increasing technologization and globalization of Dutch Higher Education are causing a need for new transferable digital skills. One such skill is the use of machine translation for academic purposes. The aim of the project is to develop, implement and evaluate a learning trajectory and online toolkit for machine translation teaching and research for all BA students in the Faculty of Humanities. The learning trajectory will show students the many opportunities machine translation offers for academic purposes. It will empower them to use machine translation effectively to find and understand sources written in foreign languages, and to use it responsibly to prepare their own assignments and papers. The toolkit offers modules on theory and research, as well as practical training in using different online systems and correcting and revising output. The toolkit includes a Research Hub providing information on current international research in machine translation, as well as access to the research carried out by students and staff at Leiden University in the implementation of the new learning trajectory. The toolkit also includes materials to make students aware of the potential dangers and ethical implications of using machine translation systems, not only within higher education but also in professional and informal contexts. The knowledge and skills acquired ensure that students become critical, responsible and effective users of machine translation, who are able to use their Machine Translation Literacy to create a more inclusive and diverse academic multilingual community.