Fostering transparency: a critical introduction of generative AI in students’ assignments

Abstract This article analyses a specific strategy designed to include generative artificial intelligence (GenAI) tools in students’ written assignments. While we recognise that GenAI tools represent a challenge for teachers in terms of their classroom use and the development of digital literacy among students, we believe that banning them is not a viable option. In our view, students need to develop a sustainable, critical approach to these tools, informed by the need to be transparent. With this in mind, we have thus developed, tested and evaluated a protocol for language learners in two Swiss universities. In our experiment, students were allowed to use any online tools available for their written assignments, but they were required to clearly highlight in their texts any output derived from text generators (ChatGPT), machine translation tools (DeepL), online corpora and online dictionaries in their texts. They also had to report on their writing process in an additional, meta-analytical paragraph. After submitting their assignments, students were asked to answer a questionnaire investigating their use of, and attitude to, GenAI tools as well as their transparency in completing the task. The data gathered allowed us to gauge students’ trustworthiness as to their self-reported tool use and to determine whether our protocol could help teachers preserve the take-home written assignment in the GenAI era. Finally, the analysis yielded interesting insights into students’ use of GenAI in L2 writing and highlighted different ways in which teachers can foster more transparency. This innovative action-research study brings much-needed data and offers practical guidance to language teachers interested in GenAI.

Authors

Institutions

Publication Details

Journal
Language Learning in Higher Education
Published
2025-05-01
DOI
https://doi.org/10.1515/cercles-2024-0105
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fostering transparency: a critical introduction of generative AI in students’ assignments

Sara Cotelli Kureth, Suzana Zink, Elisabeth Paliot
1 citations
Language Learning in Higher Education
Online Learning and Analytics
1.69
article

Fostering transparency: a critical introduction of generative AI in students’ assignments

Sara Cotelli Kureth, Suzana Zink, Elisabeth Paliot
article en
1 citations

Abstract

Abstract This article analyses a specific strategy designed to include generative artificial intelligence (GenAI) tools in students’ written assignments. While we recognise that GenAI tools represent a challenge for teachers in terms of their classroom use and the development of digital literacy among students, we believe that banning them is not a viable option. In our view, students need to develop a sustainable, critical approach to these tools, informed by the need to be transparent. With this in mind, we have thus developed, tested and evaluated a protocol for language learners in two Swiss universities. In our experiment, students were allowed to use any online tools available for their written assignments, but they were required to clearly highlight in their texts any output derived from text generators (ChatGPT), machine translation tools (DeepL), online corpora and online dictionaries in their texts. They also had to report on their writing process in an additional, meta-analytical paragraph. After submitting their assignments, students were asked to answer a questionnaire investigating their use of, and attitude to, GenAI tools as well as their transparency in completing the task. The data gathered allowed us to gauge students’ trustworthiness as to their self-reported tool use and to determine whether our protocol could help teachers preserve the take-home written assignment in the GenAI era. Finally, the analysis yielded interesting insights into students’ use of GenAI in L2 writing and highlighted different ways in which teachers can foster more transparency. This innovative action-research study brings much-needed data and offers practical guidance to language teachers interested in GenAI.

Language Learning in Higher EducationVol. 15(1)
Haute École Pédagogique du Canton de Vaud (CH), Haute école d'ingénierie et de gestion du canton de Vaud, HES-SO Haute Ecole Spécialisée de Suisse Occidentale (CH), University of Neuchâtel (CH)
Openalex Percentile: Top 13%
Online Learning and Analytics
1.69
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.