The fine-tuned descriptors in this Supplement are the result of the FineDesc Project ‘Making the CEFR/CV more user-friendly: fine-tuning descriptors with Learner Corpus Research (LCR) results’ funded by the Spanish Ministry of Science, Innovation and Universities (Grant PID2020-117041GA-I00, funded by MICIU/AEI/10.13039/501100011033). The main objective of this project was to provide L1 Spanish end-users of the Common European Framework of Reference for Languages/Companion Volume (CEFR/CV) (Council of Europe, 2001, 2020) (e.g., teachers, learners, curriculum designers, language testers, employers, etc.) with fine-tuned descriptors (Díez-Bedmar, 2018). That is, CEFR/CV descriptors, which are complemented with learner corpus-based results regarding the language employed by learners when engaging in different communicative language activities at different CEFR levels.
The fine-tuned descriptors in this Supplement have been organized considering four variables: a) the communicative language competence considered (the linguistic, the sociolinguistic and the pragmatic ones); b) the CEFR level (B1, B2 and/or C1). Since different descriptors may be found in a communicative language competence at the same CEFR level, the descriptor has been identified by providing a part of the descriptor which has been fine-tuned between brackets; c) the text type (correspondence, creative writing and/or reports and essays); and d) the main communicative function(s) in the text. The last two variables have been included due to their crucial effect on language production.
Each fine-tuned descriptor is composed of four main sections. The first one identifies the communicative language competence, the communicative language activity and text type students were engaged in, the main communicative function in the text type analysed and the CEFR level at which the texts are (i.e., B1, B2 and C1). The main communicative function in the texts has been included in this section due to the task effect on language use.
The second section offers the original descriptor and its reference. The parts of the descriptors that have been identified as prone to fine-tuning have been signalled in bold type.
The third section provides the fine-tuned descriptor. After repeating the original descriptor, learner-corpus-informed linguistic information is provided to complement those parts of the original descriptor which have been identified as prone to be fine-tuned. The underlined terminology indicates that examples will be offered in the last section of the fine-tuned descriptor.
To help readers understand the linguistic concepts which are underlined in the fine-tuned descriptors and may require some metalinguistic knowledge, the fourth and last section provides real examples taken from the learner corpus. We believe that an important asset of these fine-tuned descriptors is the use of real examples taken verbatim from the FineDesc Learner Corpus, as these allow us to illustrate what students can actually do at the corresponding level. Given the nature of the examples, some of them may contain some errors or non-target-like uses, which contribute to a more accurate view of what these learners can actually do with the language. Some examples may also contain ‘XXX’. This was used to anonymize proper nouns, locations and other types of sensitive information during the anonymization process of the FineDesc Learner Corpus.
All rights reserved