Detmar Meurers
Biographic Data
| ID | 1014993 |
|---|---|
| NAME | Detmar Meurers |
| GIVEN NAMES | Detmar |
| FAMILY NAME | Meurers |
| SIGNATURE | MEURERS D |
| AFFILIATIONS | Leibniz-Institut für Wissensmedien |
| ORCID | 0000-0002-9740-7442 |
| VERIFIED | Yes |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 19 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2001 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
From Cefr classification to generative AI materials: Designing and validating the Latill platform
Teaching German as a second language (GSL) in heterogeneous classrooms requires access to authentic and level-appropriate reading materials, yet educators often struggle to find resources that are both pedagogically suitable and legally usable. This paper presents the LATILL platform, an AI-driven tool designed to support teachers in identifying, adapting, and organizing German texts according to the Common European Framework of Reference for Lan…
Collaborative knowledge construction with generative AI: Exploring argumentative co-writing processes through n-gram and cluster analysis
Since the beginning of computer-supported collaborative learning (CSCL) research, collaborative writing has been playing a pivotal role as a tool for learning and knowledge construction. In the study presented here, we ask to what extent large language models may not only assist individuals in their writing processes but also serve as a collaboration partner. For this purpose, we analyzed the writing process of individuals supported by ChatGPT. W…
Using theory-informed learning analytics to understand how homework behavior predicts achievement
Implicit statistical learning and working memory predict EFL development and written task outcomes in adolescents
Investigating the relationship between cognitive individual differences and second language learning has been central to second language acquisition research conducted in controlled laboratory conditions and in educational instructed contexts. However, not much research to date has simultaneously explored the role of multiple cognitive abilities for L2 development or task outcomes in educational environments. In the present study, 77 secondary-sc…
Semantic information boosts the acquisition of a novel grammatical system in different presentation formats
Designing effective language learning settings requires an understanding of the processes taking place in language learning and the way they interact. One important issue concerns the interaction between meaning and grammar. A number of studies have shown a beneficial effect of semantics in grammar learning. What is unclear, however, is how far this effect may be influenced by the presentation formats of the semantic content. In two experiments, …
Designing a task-based conversational agent for EFL in German schools: Student needs, actions, and perceptions
As part of an iterative evaluation process incorporating student stakeholders within a task-based language teaching (TBLT) framework, we examine the design and early learner data of a conversational agent for English as a foreign language (EFL) in the German school context. Students (around age 12 and at an A2 proficiency level) from three 7th grade classes interacted with five tasks and completed a questionnaire assessing their needs and percept…
The Interplay of Task Characteristics, Linguistic Complexity, and Language Proficiency in High‐Stakes English as a Foreign Language Writing
The linguistic characteristics of text productions depend on various factors, including individual language proficiency as well as the tasks used to elicit the production. To date, little attention has been paid to whether some writing tasks are more suitable than others to represent and differentiate students' proficiency levels. This issue is especially relevant in the context of high‐stakes language examinations. In this study, we investigated…
Natural Language Processing and Language learning
Natural language processing (NLP) is concerned with the automated processing of human language. It addresses the analysis and generation of written and spoken language, though speech processing is often regarded as a separate subfield. NLP can be seen as the applied side of computational linguistics, the interdisciplinary field concerned with formal analysis and computational modeling of language at the intersection of linguistics, computer scien…
Interdisciplinary Research at the Intersection of Call, NLP, and SLA: Methodological Implications From an Input Enhancement Project
Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The strategic use of technology offers researchers novel methodological opportunities to examine how incre…
Language Learning Research at the Intersection of Experimental, Computational, and Corpus-Based Approaches
Language acquisition occupies a central place in the study of human cognition, and research on how we learn language can be found across many disciplines, from developmental psychology and linguistics to education, philosophy, and neuroscience. It is a very challenging topic to investigate given that the learning target in first and second language acquisition is highly complex, and part of the challenge consists in identifying how different doma…
Evidence and Interpretation in Language Learning Research: Opportunities for Collaboration With Computational Linguistics
This article discusses two types of opportunities for interdisciplinary collaboration between computational linguistics (CL) and language learning research. We target the connection between data and theory in second language (L2) research and highlight opportunities to (a) enrich the options for obtaining data and (b) support the identification and valid interpretation of relevant learner data. We first characterize options, limitations, and pote…
Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques
Large-scale learner corpora collected from online language learning platforms, such as the EF-Cambridge Open Language Database (EFCAMDAT), provide opportunities to analyze learner data at an unprecedented scale. However, interpreting the learner language in such corpora requires a precise understanding of tasks: How does the prompt and input of a task and its functional requirements influence task-based linguistic performance? This question is vi…
Readability assessment for text simplification: From analysing documents to identifying sentential simplifications
Readability assessment can play a role in the evaluation of a simplification algorithm as well as in the identification of what to simplify. While some previous research used traditional readability formulas to evaluate text simplification, there is little research into the utility of readability assessment for identifying and analyzing sentence level targets for text simplification. We explore this aspect in our paper by first constructing a rea…
Natural Language Processing and Language Learning
As a relatively young field of research and development that began with work on crypt‐analysis and machine translation around 50 years ago, natural language processing (NLP) is concerned with the automated processing of human language.
On the use of electronic corpora for theoretical linguistics
On Expressing Lexical Generalizations in HPSG
This paper investigates the status of the lexicon and the possibilities for expressing lexical generalizations in the paradigm of Head-Driven Phrase Structure Grammar (HPSG). We illustrate that the architecture readily supports the use of implicational principles to express generalizations over a class of word objects. A second kind of lexical generalizations expressing relations between classes of words is often expressed in terms of lexical rul…
Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques
Large-scale learner corpora collected from online language learning platforms, such as the EF-Cambridge Open Language Database (EFCAMDAT), provide opportunities to analyze learner data at an unprecedented scale. However, interpreting the learner language in such corpora requires a precise understanding of tasks: How does the prompt and input of a task and its functional requirements influence task-based linguistic performance? This question is vi…
Interdisciplinary Research at the Intersection of Call, NLP, and SLA: Methodological Implications From an Input Enhancement Project
Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The strategic use of technology offers researchers novel methodological opportunities to examine how incre…
Language Learning Research at the Intersection of Experimental, Computational, and Corpus-Based Approaches
Language acquisition occupies a central place in the study of human cognition, and research on how we learn language can be found across many disciplines, from developmental psychology and linguistics to education, philosophy, and neuroscience. It is a very challenging topic to investigate given that the learning target in first and second language acquisition is highly complex, and part of the challenge consists in identifying how different doma…
On the use of electronic corpora for theoretical linguistics
Evidence and Interpretation in Language Learning Research: Opportunities for Collaboration With Computational Linguistics
This article discusses two types of opportunities for interdisciplinary collaboration between computational linguistics (CL) and language learning research. We target the connection between data and theory in second language (L2) research and highlight opportunities to (a) enrich the options for obtaining data and (b) support the identification and valid interpretation of relevant learner data. We first characterize options, limitations, and pote…
On Expressing Lexical Generalizations in HPSG
This paper investigates the status of the lexicon and the possibilities for expressing lexical generalizations in the paradigm of Head-Driven Phrase Structure Grammar (HPSG). We illustrate that the architecture readily supports the use of implicational principles to express generalizations over a class of word objects. A second kind of lexical generalizations expressing relations between classes of words is often expressed in terms of lexical rul…
On the use of electronic corpora for theoretical linguistics
Natural Language Processing and Language Learning
As a relatively young field of research and development that began with work on crypt‐analysis and machine translation around 50 years ago, natural language processing (NLP) is concerned with the automated processing of human language.
Readability assessment for text simplification: From analysing documents to identifying sentential simplifications
Readability assessment can play a role in the evaluation of a simplification algorithm as well as in the identification of what to simplify. While some previous research used traditional readability formulas to evaluate text simplification, there is little research into the utility of readability assessment for identifying and analyzing sentence level targets for text simplification. We explore this aspect in our paper by first constructing a rea…
Interdisciplinary Research at the Intersection of Call, NLP, and SLA: Methodological Implications From an Input Enhancement Project
Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The strategic use of technology offers researchers novel methodological opportunities to examine how incre…
Language Learning Research at the Intersection of Experimental, Computational, and Corpus-Based Approaches
Language acquisition occupies a central place in the study of human cognition, and research on how we learn language can be found across many disciplines, from developmental psychology and linguistics to education, philosophy, and neuroscience. It is a very challenging topic to investigate given that the learning target in first and second language acquisition is highly complex, and part of the challenge consists in identifying how different doma…
Evidence and Interpretation in Language Learning Research: Opportunities for Collaboration With Computational Linguistics
This article discusses two types of opportunities for interdisciplinary collaboration between computational linguistics (CL) and language learning research. We target the connection between data and theory in second language (L2) research and highlight opportunities to (a) enrich the options for obtaining data and (b) support the identification and valid interpretation of relevant learner data. We first characterize options, limitations, and pote…
Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques
Large-scale learner corpora collected from online language learning platforms, such as the EF-Cambridge Open Language Database (EFCAMDAT), provide opportunities to analyze learner data at an unprecedented scale. However, interpreting the learner language in such corpora requires a precise understanding of tasks: How does the prompt and input of a task and its functional requirements influence task-based linguistic performance? This question is vi…
Natural Language Processing and Language learning
Natural language processing (NLP) is concerned with the automated processing of human language. It addresses the analysis and generation of written and spoken language, though speech processing is often regarded as a separate subfield. NLP can be seen as the applied side of computational linguistics, the interdisciplinary field concerned with formal analysis and computational modeling of language at the intersection of linguistics, computer scien…
Designing a task-based conversational agent for EFL in German schools: Student needs, actions, and perceptions
As part of an iterative evaluation process incorporating student stakeholders within a task-based language teaching (TBLT) framework, we examine the design and early learner data of a conversational agent for English as a foreign language (EFL) in the German school context. Students (around age 12 and at an A2 proficiency level) from three 7th grade classes interacted with five tasks and completed a questionnaire assessing their needs and percept…
The Interplay of Task Characteristics, Linguistic Complexity, and Language Proficiency in High‐Stakes English as a Foreign Language Writing
The linguistic characteristics of text productions depend on various factors, including individual language proficiency as well as the tasks used to elicit the production. To date, little attention has been paid to whether some writing tasks are more suitable than others to represent and differentiate students' proficiency levels. This issue is especially relevant in the context of high‐stakes language examinations. In this study, we investigated…
Using theory-informed learning analytics to understand how homework behavior predicts achievement
Implicit statistical learning and working memory predict EFL development and written task outcomes in adolescents
Investigating the relationship between cognitive individual differences and second language learning has been central to second language acquisition research conducted in controlled laboratory conditions and in educational instructed contexts. However, not much research to date has simultaneously explored the role of multiple cognitive abilities for L2 development or task outcomes in educational environments. In the present study, 77 secondary-sc…
Semantic information boosts the acquisition of a novel grammatical system in different presentation formats
Designing effective language learning settings requires an understanding of the processes taking place in language learning and the way they interact. One important issue concerns the interaction between meaning and grammar. A number of studies have shown a beneficial effect of semantics in grammar learning. What is unclear, however, is how far this effect may be influenced by the presentation formats of the semantic content. In two experiments, …
From Cefr classification to generative AI materials: Designing and validating the Latill platform
Teaching German as a second language (GSL) in heterogeneous classrooms requires access to authentic and level-appropriate reading materials, yet educators often struggle to find resources that are both pedagogically suitable and legally usable. This paper presents the LATILL platform, an AI-driven tool designed to support teachers in identifying, adapting, and organizing German texts according to the Common European Framework of Reference for Lan…
Collaborative knowledge construction with generative AI: Exploring argumentative co-writing processes through n-gram and cluster analysis
Since the beginning of computer-supported collaborative learning (CSCL) research, collaborative writing has been playing a pivotal role as a tool for learning and knowledge construction. In the study presented here, we ask to what extent large language models may not only assist individuals in their writing processes but also serve as a collaboration partner. For this purpose, we analyzed the writing process of individuals supported by ChatGPT. W…
Computer Science (13 works) · Linguistics (12 works) · Natural language processing (9 works) · Natural Language Processing Techniques (8 works) · Artificial Intelligence (7 works) · Mathematics education (7 works) · Psychology (7 works) · Second Language Acquisition and Learning (6 works) · Text Readability and Simplification (6 works) · Artificial Intelligence (5 works)