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 Welcome to the Integrated Digital Language Learning homepage

Natural language is ubiquitous in Technology-Enhanced Learning (TEL). It is present in both the input (texts, instructions, scripts) and the output (answers to exercises, collaborative writing, etc.) of the learning process and is the main channel of interactive communication between the tutor and the learner and between the learners. It plays a major role in all TEL fields in both hard and soft sciences. In Technology-Enhanced Language Learning (TELL), it is the learning objective besides being the vehicle for learning.

Although language is crucially involved in most TEL applications, it is usually either left unexploited or processed with crude techniques. Most tools work on the basis of chains of characters (sequences of letters) rather than the more abstract and potentially much more useful linguistic categories provided by Natural Language Processing (lemmatization, morpho-syntactic tagging, semantic tagging). Linguistically annotated data coupled with powerful algorithms make it possible to automate a wide range of processes that are particularly relevant for TEL:  glossing of texts, error detection and feedback, discourse analysis, rating of learners’ answers, exercise generation, etc.

The IDILL group brings together two groups of researchers - from academia and industry - who have a vested interest in language:

- language specialists with expertise in Natural Language Processing, corpus linguistics, lexicography, lexical computing, technology-enhanced language learning

- TEL researchers  who would like to explore new and more effective ways of dealing with language.

The IDILL group offers an opportunity to share new findings and technology and develop joint methods and initiatives. The IDILL homepage will store an extensive resource of news, documents, projects and provide a lively forum for researchers from both academia and industry.

Joining IDILL ?
See the people page for information on how to join the IDILL group.