How can adult learners use their own language output (text and voice) to further acquire language skills? How can adult learners use their critical thinking, analysis and awareness skills to improve their communicative competence across different CEFR levels? How can learners take advantage of their own mobile devices to input their own language and gain further communicative competence? The use of learner and native language information presents opportunities to look at human language in a different light, both quantitatively and qualitatively. While pedagogical innovations in the field of ICT have fostered the implementation of a myriad of language learning e-learning experiences, the exploitation of language information for the teaching and learning of languages is restricted to scattered areas of linguistics, corpus linguistics and applications of data mining. Thus, experts in corpus linguistics use language data and convert them into information to research language use in specific contexts and derive generalizations on the nature of language and language communication. Similarly, natural language (NL) processing experts, among other aspects, research methodologies that facilitate the use of NL in communication and information systems. TELL-OP is a Strategic Partnership that seeks to promote the take-up of innovative practices in European language learning by supporting personalised learning approaches that rely on the use of ICT and OER by bringing together the knowledge and expertise of European stakeholders in the fields of language education, corpus and applied linguistics, e-learning and knowledge engineering in order to promote cooperation and contribute to unleash the potential behind already available web 2.0 services to promote the personalized e-learning of languages in the contexts of higher and adult education, in particular, through mobile devices. The outputs of the TELL-OP include (1) a report of the state-of-the art technologies and services that process learner and native speaker language data into language information, (2) a survey of the knowledge and current use of open educational resources and services among higher and adult education language teachers in the realm of learner data-driven learning, (3) an app where a selection of these services is streamlined and teachers can be trained, (4) a European workshop on the integration of learner language information in higher and adult education institutions, (5) an online training initiative for HE staff in the use of the ICT and OER tools advocated by the TELL-OP SP and (6) the constitution of a European SIG to promote the use of learner language information for language learning and teaching in the context of mobile learning. In our context, language information is defined as language data which have been gathered to portray properties or characteristics of language. Examples of language information in highly specialized research and academic contexts include quantitative measures such as frequencies of occurrence of discrete language items (from characters to words or string of words), other text stats like, among many others, the Fog index, the Flesch index or the Flesch-Kincaid index, Part of Speech Tagging, or different measures of complexity. While average language learners should benefit from these insights, it is beyond any doubt that they should avoid all the technical aspects and associated jargon. The mission of TELL-OP is to exploit the expertise and good practices of the consortium in order to allow European language educators in higher education and adult education institutions to integrate learner language information into their teaching and thus transform the existing wealth of Open Educational Resources in language processing into knowledge that can ultimately be used by language learners across the EU as a resource to improve their e-learning skills in the context of both autonomous and personalized learning experiences. We expect that by the end of the project at least 500 students and 200 HE and AE language teachers have received both face-to-face and distance training in the possibilities to use learner language processing in order to empower learners with the competencies and the skills to further exploit these ICT-driven OE resources.