Resources

Louvain Error Tagging Manual and UCLouvain Error Editor.

Detailed error tagging system L2 learner errors produced by foreign- or second-language learners (study of L2 accuracy) and its accompanying error editor tool which aims to facilitate the insertion of error tags.

IRIS database

IRIS is a collection of instruments, materials, data, and data coding and analysis tools used for research into languages, including first, second, and beyond, and signed language learning, multilingualism, language education, language use, and language processing. 

​Inputlog​

Inputlog is a keystroke logging program enabling you to observe writing process dynamics and collect fine grained data. The program also provides a wide range of analyses opening new perspectives to a better understanding of the (cognitive) complexity of writing

​Beldeko Summary Corpus v1.1.0​

The Beldeko (Belgisches Deutschkorpus) Summary Corpus is a learner corpus that consists of summaries written by advanced L2 German learners (CEF level B2-C1) with L1 Dutch. It has been created with the aim of investigating the academic writing skills in L2 German of third-year students of two bachelor programmes in Applied Linguistics and Linguistics and Literature, respectively.

​German Summary Corpus (GerSumCo) v1.0.0​

The GerSumCo (German Summary Corpus) is a learner corpus comprising syntheses written by L2 German writers (CEFR B2/C1) and writers of L1 German. The corpus has been created with the objective of conducting a comparative analysis of the academic writing of L1 German and L2 German students. The two subcorpora (L1 and L2) contain a total of 286 texts (178 L1 and 108 L2), written by 286 students at 14 universities and language schools in Germany (Bamberg, Bochum, Dresden, Hamburg, Hildesheim, Kiel, Leipzig, Magdeburg, Osnabrück, Potsdam, Trier, Wuppertal), Poland (Gdansk) and China (Hangzhou). The texts were collected between 2022 and 2024 as part of a PhD research project about a contrastive interlanguage analysis using GerSumCo and Beldeko to identify L1-dependent features in cohesion in L2/L1 German. The metadata files (Meta_GerSumCo_L1 & Meta_GerSumCo_L2) contain the following information: - Up to three L1s of the writers - Up to three L2s of the writers - Collection date - Topic - Whether the text was written as homework or in class - Group of students the texts belonged to The file names contain the following information: - Whether the text is part of the L1 or L2 subcorpus - Topic The summaries, on average, consist of 230 words. The texts were either produced in class on computers or as homework, within a 60-minute time frame. Students were permitted to use online dictionaries, but no AI-based auxiliary means. They were required to summarise two texts on one of four topics related to language variation in German: Kiezdeutsch, Mundartdebatte in der Schweiz, Viadrinisch and Varianten-Wörterbuch des Deutschen. This version contains the TXT files of the texts and the CSV files containing the manual annotations of the texts with token ID, sentence ID, source text form, target form, automatic annotated lemma, POS (STTS) and simple UPOS part-of-speech tag.

Movie clips for experiments involving sentence elicitation​

For a research project in which we investigated early second language learning via an artificial language learning paradigm (PhD Merel Muylle), we developed a set of 423 animated action movie clips of 3 s, that are useful for a variety of experimental paradigms in which sentences are elicited (Muylle, Wegner, Bernolet & Hartsuiker, 2020). In order to verify that the movie clips (when presented with a verb) indeed elicited intransitive, transitive, or ditransitive sentences, we conducted a written norming study with native speakers of American English. The clips and a list containing the proportions of each response type for each clip are are freely available for research purposes on the Open Science Framework.