*CFPs special issue of Research in Corpus Linguistics (RiCL)*

*‘Learner Corpus Research meets the Common European Framework of Reference for Languages and the Companion Volume’*

Due to the importance of the *Common European Framework of Reference for Languages* (CEFR) and the *Companion Volume* (CV) (Council of Europe, 2001, 2020) for the learning, teaching and assessment of languages, most learner corpora nowadays employ the learner’s CEFR level to specify the student’s communicative language competence level or proficiency level.

Most learner corpora compiled in CEFR-aligned high-stakes foreign language accreditation/certification exams - for instance, the *Cambridge Learner Corpus* (O’Keeffe & Mark, 2017), the *FineDesc Learner Corpus *(Díez-Bedmar, 2025) - are composed of learners of English production in successful certification/accreditation exams at different CEFR levels. Other target languages are compiled in similar foreign language accreditation/certification exam conditions, such as the CELI corpus for Italian (Spina et al., 2023) or the Merlin corpus for Italian, German and Czech (Wisniewski, 2020). Other learner corpora composed of accreditation/certification exams that are not aligned to the CEFR or learner corpora compiled in other contexts have also been partially or fully aligned to the CEFR levels, as reported by Gablasova et al., (2019) regarding the *Trinity Lancaster* *Corpus*, Thewissen (2013) concerning *ICLE* or Tono (2018) as to the *JEFLL corpus*.

The use of LCR results from CEFR-aligned learner corpora to inform or facilitate the implementation of the CEFR/CV is, however, still limited. Among the most important LCR contributions in this respect are those by the *English Profile Project* (Salamoura, 2008) and the CEFR-J Project (Tono, 2019). The former used the *Cambridge Learner Corpus* to provide linguistic information on the language produced at each CEFR level (UCLES/CUP, 2011) and freely available online resources (eg., the English Grammar Profile and the English Vocabulary Profile). The latter employed learner corpora, among other corpora types, to adapt the CEFR for the L1 Japanese EFL context (12 sublevels), create the Vocabulary Profile and the Grammar Profile.

Despite these efforts, CEFR/CV end-users and stake-holders find difficulties in the implementation of the CEFR/CV in their L1-contexts, on most occasions due to the language neutral nature of the CEFR/CV descriptors (see Díez-Bedmar & Byram, 2019; Díez-Bedmar & Luque-Agulló, 2023; Luque-Agulló & Díez-Bedmar, 2025). It is for this reason that they demand fine-tuned descriptors, i.e., CEFR/CV descriptors informed by CEFR-aligned L1-specific learner corpus results (Díez-Bedmar, 2018). In the Spanish context, the *FineDesc Project* (Grant PID2020-117041GA-I00, funded by MICIU/AEI/10.13039/501100011033) has provided L1 Spanish CEFR/CV end-users and stake-holders’ with fine-tuned descriptors thanks to the analysis of the 1.3-million-word *FineDesc Learner* *Corpus* (Díez-Bedmar, 2025), a freely available L1-specific learner corpus by L1 Spanish monolingual students (or bilingual L1 Spanish/a co-official language in Spain). The learner corpus results have informed fine-tuned descriptors not only for the linguistic competence, but also for the sociolinguistic and pragmatic ones, when students engage in different communicative language activities at B1, B2 and C1 levels (see Díez-Bedmar et al., 2026). These fine-tuned descriptors aim at paving the way for the implementation of the CEFR/CV in the L1 Spanish context.

These are just some examples which show how LCR may inform the CEFR/CV and facilitate its implementation in different contexts. Other efforts are being made by the LCR community by using either general CEFR-aligned learner corpora or L1-specific ones, as shown in some papers presented at the International Online Conference ‘Bringing together research on the CEFR/CV and LCR: a focus on descriptors’ which was organized by the FineDesc Project (https://web.ujaen.es/investiga/finedesc/index.php).

It is the objective of this special issue to bring together research on the different ways how LCR may meet the CEFR/CV. Contributions which employ any reliably CEFR-aligned learner corpus with this objective in mind are welcome, whether they were presented at the conference or not. Researchers who do not have access to any CEFR-aligned learner corpus are encouraged to use the *FineDesc Learner Corpus*, freely available at www.finedesc.com.

*Potential topics for this special issue are (but are not limited to):*

-The fine-tuning of CEFR/CV descriptors for L1-specific contexts thanks to LCR.

-The integration of CAF results in fine-tuned descriptors.

-The (cross-sectional) analysis of CEFR-aligned learner corpora considering the linguistic, sociolinguistic or pragmatic competences to inform CEFR-aligned pedagogical resources/language assessment.

-The exploitation of CEFR-aligned learner corpora to design tools/software which may help analyse learner corpora at different CEFR levels.

-The overcoming of any difficulties in CEFR/CV implementation with the help of LCR.

*Important dates*

Deadline for proposals: April 30, 2026

Outcome of proposal review: May 21, 2026

Deadline for manuscript first drafts: December 1,2026

Notification of reviewer outcome: March 5, 2027

Deadline for manuscript final drafts: May 28th, 2027

Special issue publication: Autumn 2027

*Proposal format and submission*

Potential contributors should prepare an extended 800-word abstract of the proposed paper following RiCL’s submission guidelines, which can be found at https://ricl.aelinco.es/index.php/ricl/about/submissions

The abstract should include a tentative title, motivate the study, state the research questions, provide methodological information (learner corpus or learner corpora analysed and the procedure employed to align it/them to CEFR/CV levels as well as the statistical tests employed), tentative results and clear information on the way how the results inform the CEFR/CV and its implementation.

Please submit your proposal to the special issue editor, María Belén Díez-Bedmar (belendb@ujaen.es), before the deadline (April 30, 2026) including in your proposal your name(s), email(s) and affiliation(s).

*Peer review*

All accepted manuscripts will undergo double-blind peer review.

*References*

Council of Europe (2001). Common European Framework of Reference for Languages: learning, teaching, assessment. Council of Europe Publishing.

Council of Europe (2020). Common European Framework of Reference for Languages: learning, teaching, assessment – Companion Volume. Council of Europe Publishing.

Díez-Bedmar, M. B. (2018). Fine-tuning descriptors for CEFR B1 level: insights from learner corpora. *ELT Journal*, 72(2), 199-209. https://doi.org/10.1093/elt/ccx052

Díez-Bedmar, M. B. (2025). FineDesc Learner Corpus 2.0 (España, 2510243469857). SafeCreative. https://www.safecreative.org/validity

Díez-Bedmar, M. B., & Byram, M. (2019). The current influence of the CEFR in secondary education: teachers’ perceptions. *Language, Culture and Curriculum*,* 32*(1), 1–15. https://doi.org/10.1080/07908318.2018.1493492

Díez-Bedmar, M. B., Laso-Martín, N. J., Maíz-Arévalo, C., & Carrió-Pastor, M. L. (2026). Supplement to the Common European Framework of Reference for Languages and the Companion Volume: L1 Spanish users (Spain, 2601214327051). SafeCreative. https://www.safecreative.org/validity

Díez-Bedmar, M. B. & Luque-Agulló, G. (2023). Analysing the CEFR/CV in University Language Centres in Spain: The Raters' Perspective. In M. Fernández Álvarez & A. L. Gordenstein Montes (Eds.), *Global Perspectives on Effective Assessment in English Language Teaching* (pp. 1-33). IGI Global.

Gablasova, D., Brezina, V., & McEnery, T. (2019). The Trinity Lancaster Corpus. Development, description and application. *International Journal of Learner Corpus Research*, *5*(2), 126-158. https://doi.org/10.1075/ijlcr.19001.gab

Luque-Agulló, G. & Díez-Bedmar, M.B. (2025). Listening to the teachers: CEFR implementation in University language Centres in Spain. *Revista de Lingüística y Lenguas Aplicadas* (RLyLA),*20*, 72-86. https://doi.org/10.4995/rlyla.2025.21285

O’Keeffe, A., and Mark, G. 2017. The English Grammar Profile of learner competence: Methodology and key findings. *International Journal of Corpus Linguistics,* *22*(4), 457-489. https://doi.org/10.1075/ijcl.14086.oke

Salamoura, A. (2008). Aligning English Profile research data to the CEFR. Cambridge ESOL: *Research Notes*, *33*, 5–7.

Spina, S., Fioravanti, I., Forti, L., & Zanda, F. (2023). The CELI corpus: Design and linguistic annotation of a new online learner corpus. *Second Language Research*, 40(2), 457-477. https://doi.org/10.1177/02676583231176370

Thewissen, J. (2013). Capturing L2 accuracy developmental patterns: Insights from an error-tagged EFL learner corpus. *The Modern Language Journal*, *97*(S1), 77-101.

Tono, Y. (2018). Corpus approaches to L2 Learner Profiling Research. In Y. N. Leung, J. Katchen, S. Y. Hwang & Y. Chen (Eds.), Reconceptualizing English language teaching and learning in the 21st century: A special monograph in memory of Professor Kai-Chong Cheung (pp. 390-402). Taipei, Taiwan: Crane Publishing Company.

Tono, Y. (2019). Coming full circle – from CEFR to CEFR-J and back. CEFR Journal. *Research and Practice*, *1*, 5-17. https://doi.org/10.37546/JALTSIG.CEFR1-1

UCLES/CUP (2011). *English Profile. Introducing the CEFR for English Version 1.1*. Cambridge University Press.

Wisniewski, K. (2020). SLA developmental stages in the CEFR-related learner corpus MERLIN: Inversion and verb-end structures in German A2 and B1 learner texts. *International Journal of* *Learner Corpus Research*, *6*(1), 1–17. https://doi.org/10.1075/ijlcr.18008.wis