When dealing with Language for Specific Purposes (LSP), teachers always have to confront with issues which are strictly linked to the specificities of the language of a given field. This is not only the case of language teachers, but it is also and particularly true for CLIL teachers in Italy, who are subject teachers sharing with language teachers some aspects of pupils' language education. This paper is grounded in the discussion of Data-driven Learning (DDL) as a scaffolding method to support the language aspects of CLIL, and the role of data-driven materials in enhancing learning in general. Corpus-based methodology in CLIL classes (the LSP learning environment par excellence) means to empower both teachers and students to develop competences in moving away from mere surface features of text to selecting and understanding meanings and structures. In doing so, they use texts with specific intentions, becoming familiar with tools such as corpora to compensate, for instance, the deficiencies of general dictionaries. Over 25 years ago Tim Johns advocated the learning-centered value of DDL, calling "every student a Sherlock Holmes." In fact, DDL good practices perfectly align with current theories and practices of SLA, namely the constructivist and learner-centered approaches to language acquisition. It underpins the mandate in contemporary communicative language instruction for the use of authentic language materials and for the development of metalinguistic knowledge and learner autonomy. The uses and benefits of corpora for language learning are widely reported in the literature, although there is still little field practice, in Italy at least. Our word wants to suggest possible good and effective practices combining CLIL needs and the DDL approach to language and content. A case study where DDL was successfully used in a vocational context will be presented. The reference corpus was based on oral and written productions by English native speakers, elicited from a picture specifically sketched for the activity (a hairdresser's salon with multiple actions and objects). Both lexical items and syntactic structures were extracted by students who were confronted with the data and had to deal with different tasks for their analysis. Results were encouraging and students who were exposed to DDL engaged in an involving activity that considerably improved their language skills in their actual working practice.

A diagnostic component for natural language utterances has been devised which allows one to integrate (possibly inconsistent) evidence from a wide range of knowledge sources into a unique decision procedure. It is based on a procedure for the disambiguation of dependency structures using graded constraints. Different description levels like syntax, semantics, and others are treated by separate structural representations, which are disambiguated simultaneously. Due to the complete symmetry of the system architecture the approach allows to handle a wide variety of student errors successfully.

Building on the results of a previous study on reformulative discourse markers (Corino 2012), this paper examines the different functions and semantic features of the Italian discourse markercioèin the hope of elaborating a clear framework for its many functions and uses. The outcomes will enable us to answer three main research questions: 1) Is there a relevant relationship between the learner’s mother tongue and the use ofcioè? 2) What points in Italian as a second language (ISL) need to be taught to learners in order to improve the use of DMs? 3) What functions ofcioèare used more or less by learners of ISL with respect to native speakers? To this end, the distribution of this DM will be analyzed in texts written by ISL learners, collected in the learner corpora VALICO and ADIL2, in search of regularities in acquisition vs. evidence of influence of the learners’ mother tongues.

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