PEOPLEJennifer-Carmen Frey

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Jennifer-Carmen Frey

Research Group Leader
Institute for Applied Linguistics

T +39 0471 055 136

jennifercarmen.frey@eurac.edu

https://orcid.org/0000-0002-7008-6394

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About

Research interests:

writing research, literacy and language assessment
language learning and teaching
computer-mediated communication
language variation and dialects of German
corpus linguistics and NLP for non-standard language

Jennifer-Carmen Frey is a Senior Researcher at the Institute for Applied Linguistics at Eurac Research Bolzano. In her interdisciplinary work she combines computational and quantitative methods as well as corpus linguistics with educational questions to study language use in linguistically diverse contexts. Her recent work focuses on communicative competence and language awarenes of multilingual individuals both in educational settings as well as informal contexts such as social media, thereby frequently dealing with non-standard language in all it's forms - be it dialects, learner varieties or social media.

https://www.researchgate.net/profile/Jennifer-Frey

Scientific Publications

Report2025

An overview of Grammatical Error Correction for the twelve MultiGEC-2025 languages

Masciolini A, Caines A, De Clercq O, Kruijsbergen J, Kurfalı M, Muñoz Sánchez R, Volodina E, Östling R,

Lionel Nicolas, Jennifer-Carmen Frey

ISBN: 1401-5919

This overview is complementary to the comprehensive dataset description article for MultiGEC – a dataset for Multilingual Grammatical Error Correction including data for twelve European languages: Czech, English, Estonian, German, Greek, Icelandic, Italian, Latvian, Russian, Slovene, Swedish and Ukrainian. It is well-known that in the field of Natural Language Processing (NLP) most publications tend to focus on the English language. While this is due to historical reasons (ease of publication, greater outreach, increased number of citations, etc.), it does leave other languages at a disadvantage across multiple tasks. The MultiGEC dataset was created as an attempt to counteract this effect. This report provides a historical overview of the evolution of GEC for each of the twelve languages in this dataset and provides a context for the work on the dataset and the related MultiGEC-2025 shared task.

Source

Journal article2025

Analysing child writing in multilingual contexts: Combining corpora, computational tools, and methods for crossing the borders of monolingual studies on communicative competence

Frey JC

Jennifer-Carmen Frey

Project: One School, Many Languages, Learner Corpus Infrastructure, Coherence in academic Italian

Working as a computational corpus linguist in a multilingual area, my research aims to analyse communicative competence as shown in writing not only across different languages but also within multilingual students. I have been working with corpora that contain comparable and/or multilingual – partly longitudinal, partly cross-sectional – data for L1 and L2 students of German and Italian with additional data for English as a foreign language. My research investigates plurilingual competences and questions traditional concepts of L1 and L2 categories when researching students from multilingual areas. In my work, I combine data-driven analysis frameworks, quantitative corpus linguistic methods and qualitative investigations in collaboration with my colleagues, relating language features with detailed sociolinguistic metadata on students’ language backgrounds.

This article brings together some of my work in the area of non-adult writing, presenting the various corpora I have worked on and how they have been used to analyse communicative competence in both German and Italian children’s writing moving from the assumption of clearly separated L1 and L2 contexts towards observing multicompetence in young writers. While the studies presented here show some attempts to uncover the complexity of different learning contexts in a multilingual society, combining various resources as well as quantitative and qualitative research methods, the article will also discuss challenges, potentials and limitations of combining data, as well as methods and tools borrowed from different disciplines, with an outlook for future research in the field.

DOI Source

DOI: 10.1016/j.acorp.2025.100158

Journal article2025

Categorising speakers’ language background: Theoretical assumptions and methodological challenges for learner corpus research

Lopopolo O, Bienati A, Frey JC, Glaznieks A, Spina S

Aivars Glaznieks, Arianna Bienati, Jennifer-Carmen Frey

Project: Learner Corpus Infrastructure

In this article, we investigate how speakers can be categorised based on their language background in the field of Learner Corpus Research (LCR). Specifically, we discuss three key aspects: first, the theoretical assumptions and methodological choices made in learner corpus design, second the integration of a holistic perspective for speaker categorisation in LCR and third the consequences that different categorisations might have on study outcomes. Through a comprehensive review of corpora used in the field, we identify the most common terms, definitions and criteria of categorisation used to describe a speaker's language background. Focusing on the most central metadata encoding language backgrounds, the L1 metadata, we inspect different operationalisations made and scrutinise the theoretical assumptions underlying them. Drawing on research on plurilingualism, we propose a holistic view of speaker's language background for Learner Corpus Research, combining various aspects of speaker's language use by methods inspired from the Dominant Language Constellation framework. We apply this methodology to re-evaluate the language categorisation system in LEONIDE, a multilingual corpus of Italian, German and English texts from secondary school students of diverse language backgrounds. We use the same corpus to evaluate the consequences of using different categorisations of the students on the outcome of possible linguistic studies. Despite a generally high overlap between study results across categorisations, we observe that variables combining multiple aspects of the speakers’ language backgrounds seem to explain group differences for more of the linguistic features investigated.

DOI Source

DOI: 10.1016/j.rmal.2024.100170

Journal article2025

Theoretical Implications of Automated Discourse Parsing in Student Writing

Bienati A, Pascucci M, Frey JC, Palmero Aprosio A

Arianna Bienati, Jennifer-Carmen Frey

Project: Coherence in academic Italian

This article presents a study on annotating explicit discourse relations in Italian student essays, comparing human annotations with outputs from generative large language models and examining their alignment with theoretical models of textuality. We review prior work on automatic discourse relation annotation in Italian, highlighting limitations in language coverage, especially in out-of-domain scenarios and how these have been addressed. Our experiments explore the use of generative models to mitigate the scarcity of domain-specific training data, while assessing their ability to reflect the intended theoretical framework. We evaluate two generative models in detecting connectives and classifying their senses, comparing results to human annotation. For our evaluation sample, we use a string-matching algorithm combined with a rule-based approach to pre-annotate essays with possible connective forms and their senses, based on their presence in the Lexicon of Italian Connectives (LICO). These annotations were manually corrected by two expert annotators, resulting in a publicly available evaluation sample. The study raises significant theoretical questions about the definition of connectives, its relationship to text segmentation and the challenges both human and machines face when annotating discourse relations. Our findings show how computational approaches can shed light on linguistic theories and, vice versa, how linguistic theories can guide the application of computational resources.

DOI Source

DOI: 10.17454/IJCOL112.03

Journal article2024

The Core Metadata Schema for Learner Corpora (LC-meta): collaborative efforts to advance data discoverability, metadata quality and study comparability in L2 research

Paquot M, König A, Stemle EW, Frey JC

Egon W. Stemle, Jennifer-Carmen Frey

Metadata is critical throughout the research process, from study design to corpus selection/compilation, result interpretability and cumulative research. To date, however, learner corpus research has not developed community standards or best practices for metadata collection and sharing. In this article, we present the results of a collaborative project aimed at addressing this issue by developing a standardised metadata schema for learner corpora. We first describe the procedure implemented to design the schema, including the ways in which we continuously involved learner corpus researchers in this initiative. We then introduce the Core Metadata Schema for Learner Corpora (LC-meta, Version 2), which consists in a set of obligatory and optional variables that encapsulate crucial information about L2 data (administrative details, corpus design, text-related variables, learner-related variables, annotations, annotators, or transcribers). Finally, we discuss future developments and emphasise the importance of continued maintenance and further refinement of this schema by the research community.

DOI Source

DOI: 10.1075/ijlcr.24010.paq

Journal article2023

Dialektale Sprachrealitäten über CMC-Korpora erleben: Das DiDi-Korpus zur internetbasierten Kommunikation aus Südtirol im DaZ-Unterricht

Glaznieks A, Frey JC

Aivars Glaznieks, Jennifer-Carmen Frey

Project: Digital Natives - Digital Immigrants. Writing on Social Network Sites: a corpus-based observation of the current language use in South Tyrol, with particular consideration of the writers' age, Written language online in everyday life

Der Beitrag stellt das DiDi-Korpus zur internetbasierten Kommunikation (IBK) aus Südtirol (vgl. Frey et al. 2016) vor und diskutiert seinen potenziellen Wert für den DaZ-Unterricht. Das Korpus besteht aus etwa 40.000 Facebooktexten von privaten NutzerInnen und zeigt einen authentischen Ausschnitt der schriftlichen digitalen Kommunikation in Südtirol, die sich neben typischen Merkmalen der IBK auch durch die Nutzung mehrerer Varietäten (z.B. Standarddeutsch und Dialekt) und Sprachen (z.B. Deutsch und Italienisch) auszeichnet (vgl. Glaznieks / Frey 2018). Der Beitrag fokussiert auf den schriftlichen Gebrauch mehrerer Varietäten in der IBK und stellt den soziokulturellen und kommunikativ-pragmatischen Mehrwert des DiDi-Korpus als authentische Sprachressource für DaZ-Lernende heraus.

DOI

DOI: 10.48694/kordaf.3839

Journal article2023

The Kolipsi Corpus Family: Resources for Learner Corpus Research in Italian and German

Glaznieks A, Frey JC, Abel A, Nicolas L, Vettori C

Aivars Glaznieks, Chiara Vettori, Andrea Abel, Lionel Nicolas, Jennifer-Carmen Frey

Project: KOLIPSI II: South-Tyrolean pupils and the second language: a linguistic and socio-psychological investigation, Learner Corpus Infrastructure

This article describes the Kolipsi Corpus Family (KCF), a collection of eight related resources for learner corpus research in German and Italian. The KCF supports the study of second language (L2) acquisition of Italian and German in upper secondary schools. It subsumes four L2 corpora with comparable corpus design (with respect to data collection, writing tasks, additional metadata, annotation and processing), portraying two homogeneous learner groups and their learner varieties. The corpora are representative of language learners in the multilingual Italian province of South Tyrol, where both languages are taught daily. The L2 corpora were collected at two different points in time, in 2007 (Kolipsi-1) and 2014 (Kolipsi-2), and all texts were labeled with CEFR levels to allow comparisons of proficiency levels across time. L2 German texts were collected in schools with Italian as the main language of instruction, whereas L2 Italian texts were collected in schools with German as the main language of instruction. Additional resources within the KCF allow researchers to compare the students’ language competences in their L2 with the language competences in their first language (L1) in a different task (Kolipsi-Matura) and with similarly aged L1 writers performing the same task (Kolipsi-1-L1). All texts are freely available to the scientific community. Access to the data is granted via an ANNIS search interface and via the Eurac Research CLARIN Repository, from which corpus data can be downloaded in various formats.

DOI Source

DOI: 10.4000/ijcol.1210

Journal article2022

Leonide: A longitudinal trilingual corpus of young learners of Italian, German and English

Glaznieks A, Frey JC, Stopfner M, Zanasi L, Nicolas L

Aivars Glaznieks, Maria Stopfner, Lorenzo Zanasi, Lionel Nicolas, Jennifer-Carmen Frey

Project: One School, Many Languages, Learner Corpus Infrastructure, One School, Many Languages 2.0

This article presents the longitudinal trilingual corpus of young learners of Italian, German and English called LEONIDE. The corpus consists of L1, L2 and L3 learner texts. L1 texts were written in two languages of schooling (i.e. Italian and German), L2 texts in two languages learned as second languages (i.e. German and Italian), and L3 texts in an additional foreign language (i.e. English). All texts were collected from a group of lower secondary school pupils from the multilingual Italian province of South Tyrol whose development in all three languages was observed over a period of three years. Each text comes with rich metadata as well as manual and automatic annotations.

DOI Source

DOI: 10.1075/ijlcr.21004.gla

Journal article2021

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

König A, Frey JC, Stemle EW

Egon W. Stemle, Jennifer-Carmen Frey

Project: Learner Corpus Infrastructure

Up until today research in various educational and linguistic domains such as learner corpus research, writing research, or second language acquisition has produced a substantial amount of research data in the form of L1 and L2 learner corpora. However, the multitude of individual solutions combined with domain-inherent obstacles in data sharing have so far hampered comparability, reusability and reproducibility of data and research results. In this article, we present work in creating a digital infrastructure for L1 and L2 learner corpora and populating it with data collected in the past. We embed our infrastructure efforts in the broader field of infrastructures for scientific research, drawing from technical solutions and frameworks from research data management, among which the FAIR guiding principles for data stewardship. We share our experiences from integrating some L1 and L2 learner corpora from concluded projects into the infrastructure while trying to ensure compliance with the FAIR principles and the standards we established for reproducibility, discussing how far research data that has been collected in the past can be made comparable, reusable and reproducible. Our results show that some basic needs for providing comparable and reusable data are covered by existing general infrastructure solutions and can be exploited for domain-specific infrastructures such as the one presented in this article. Other aspects need genuinely domain-driven approaches. The solutions found for the corpora in the presented infrastructure can only be a preliminary attempt, and further community involvement would be needed to provide templates and models acknowledged and promoted by the community. Furthermore, forward-looking data management would be needed starting from the beginning of new corpus creation projects to ensure that all requirements for FAIR data can be met.

DOI Source

DOI: 10.3390/info12050199

Conference proceedings article2020

Creating a learner corpus infrastructure: Experiences from making language learner data available

Frey J, König A, Fišer D

Jennifer-Carmen Frey

Project: Learner Corpus Infrastructure

With language resources being collected in many - also small - projects in learner corpus research with considerate amounts of time and effort spent in this activity, making these types of data available in a FAIR way, with standardized and reasoned methods, would contribute substantially to the advancement of the field. Additionally, it would answer current demands in transparency, replicability and reusability. In this article, we discuss some of the challenges when making learner corpora FAIR and report from experiences in fulfilling this aim while creating a learner corpus infrastructure at a research institution hosting five different learner corpora.

DOI Source

DOI: 10.1051/itmconf/20203303006

Inbook2020

Das DiDi‐Korpus: Internetbasierte Kommunikation aus Südtirol

Glaznieks A, Frey JC

Aivars Glaznieks, Jennifer-Carmen Frey

Das DiDi-Korpus ist eine Sammlung von soziolinguistisch und computerlinguistisch aufbereiteten Facebook-Statusmeldungen, -Kommentaren und -Chatnachrichten. Alle Texte stammen von privaten Profilen von 136 Schreiberinnen und Schreibern aus Südtirol und stellen deren gesamte Facebook-Kommunikation des Jahres 2013 dar. Die Schreiberinnen und Schreiber geben überwiegend Deutsch als ihre Erstsprache an (108/136) und verteilen sich auf unterschiedliche Altersgruppen. Neben der breiten Altersspanne der Schreiberinnen und Schreiber (14-74 Jahre) zeichnet sich das Korpus vor allem durch regionale Eigenheiten wie seinem hohen Anteil dialektaler und mehrsprachiger Texte (besonders Deutsch, Italienisch und Englisch) aus. Das Korpus ist frei zugänglich und kann über eine ANNIS-Suchoberfläche durchsucht oder als XML bzw. JSON heruntergeladen werden (https://commul.eurac.edu/annis/didi).

DOI

DOI: 10.1515/9783110679885-019

Inbook2019

Wie misst man Textqualität im digitalen Zeitalter? (MIT.Qualität)

Abel A, Frey JC, Glaznieks A, Linthe M, Müller-Spitzer C, Storrer A, Wolfer S

Andrea Abel, Aivars Glaznieks, Jennifer-Carmen Frey

Project: Measuring language quality in the digital age

Schreibprodukte in sozialen Netzwerken entsprechen nicht immer den normativen Erwartungen, die man an redigierte Texte in der Presse, der Wissenschaft oder der Belletristik heranträgt. Die Frage, wie sich dies auf unsere Schriftsprache und auf die Entwicklung von Schreibkompetenzen auswirkt, wird in der Öffentlichkeit kontrovers diskutiert (vgl. Dürscheid/Brommer 2009; Storrer 2014; Dürscheid/Frick 2016). Allerdings gibt es bislang wenig Möglichkeiten, empirisch fundierte Antworten auf diese Frage zu geben. Das liegt einerseits daran, dass es aufwändig ist, Korpora mit Lernertexten aus dem schulischen Bereich und Schreibprodukten aus sozialen Medien zu sammeln und für die empirische Analyse aufzubereiten. Es liegt aber auch daran, dass eine „einheitliche Antwort auf die Frage, was eine gute Schreibkompetenz ist, noch immer aussteht“ (Dürscheid/Frick 2016, S. 125). Das Projekt „Wie misst man Textqualität im digitalen Zeitalter?“ (MIT.Qualität)1 setzt an dieser Lücke an und möchte in zwei Arbeitsbereichen dazu beitragen, die Voraussetzungen für die empirische Untersuchung des Schreibgebrauchs und der Schreibkompetenzen in digitalen Medien zu verbessern.

DOI Source

DOI: 10.1515/9783110622591-025

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Journal article2021

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

König A, Frey JC, Stemle EW

Egon W. Stemle, Jennifer-Carmen Frey

Project: Learner Corpus Infrastructure

DOI Source

DOI: 10.3390/info12050199

Jennifer-Carmen Frey

About

Scientific Publications

An overview of Grammatical Error Correction for the twelve MultiGEC-2025 languages

Analysing child writing in multilingual contexts: Combining corpora, computational tools, and methods for crossing the borders of monolingual studies on communicative competence

Categorising speakers’ language background: Theoretical assumptions and methodological challenges for learner corpus research

Theoretical Implications of Automated Discourse Parsing in Student Writing

The Core Metadata Schema for Learner Corpora (LC-meta): collaborative efforts to advance data discoverability, metadata quality and study comparability in L2 research

Dialektale Sprachrealitäten über CMC-Korpora erleben: Das DiDi-Korpus zur internetbasierten Kommunikation aus Südtirol im DaZ-Unterricht

The Kolipsi Corpus Family: Resources for Learner Corpus Research in Italian and German

Leonide: A longitudinal trilingual corpus of young learners of Italian, German and English

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

Creating a learner corpus infrastructure: Experiences from making language learner data available

Das DiDi‐Korpus: Internetbasierte Kommunikation aus Südtirol

Wie misst man Textqualität im digitalen Zeitalter? (MIT.Qualität)

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Scientific Publications

An overview of Grammatical Error Correction for the twelve MultiGEC-2025 languages

Analysing child writing in multilingual contexts: Combining corpora, computational tools, and methods for crossing the borders of monolingual studies on communicative competence

Categorising speakers’ language background: Theoretical assumptions and methodological challenges for learner corpus research

Theoretical Implications of Automated Discourse Parsing in Student Writing

The Core Metadata Schema for Learner Corpora (LC-meta): collaborative efforts to advance data discoverability, metadata quality and study comparability in L2 research

Dialektale Sprachrealitäten über CMC-Korpora erleben: Das DiDi-Korpus zur internetbasierten Kommunikation aus Südtirol im DaZ-Unterricht

The Kolipsi Corpus Family: Resources for Learner Corpus Research in Italian and German

Leonide: A longitudinal trilingual corpus of young learners of Italian, German and English

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

Creating a learner corpus infrastructure: Experiences from making language learner data available

Das DiDi‐Korpus: Internetbasierte Kommunikation aus Südtirol

Wie misst man Textqualität im digitalen Zeitalter? (MIT.Qualität)