Welcome to the website of the project TRAI:
Exploring the Triad of
Academic Writing, Critical Thinking and AI Literacy:
Interdisciplinary Perspectives on Undergraduate Thesis Writing
Can students still think critically when they write their academic theses in the age of AI?
The Bachelor’s thesis has long been a defining moment in undergraduate education. After three to four years of structured learning, students are expected to conduct independent research, construct arguments, and demonstrate intellectual maturity. It is here that academic thesis writing becomes more than a technical skill, it becomes a marker of scholarly identity and epistemic development.
Today, this milestone stands at the centre of a profound transformation. Artificial Intelligence is not simply entering higher education; it is reshaping the intellectual conditions under which students learn to think and write.
The challenge: academic writing, critical thinking, and AI
AI systems, particularly large language models, now assist students with idea generation, structuring, summarising, revising, and even argument development. These tools intervene directly in processes that have traditionally been central to the cultivation of critical thinking.
This project investigates the dynamic relationship between academic writing, critical thinking, and AI literacy in the context of Bachelor’s thesis production. Rather than focusing primarily on ethical debates, we examine the deeper intellectual question:
How is knowledge constructed when writing becomes a collaboration between human and machine?
We address the following core research questions:
- How does AI use reshape the students’ thesis writing processes, including idea generation, structuring, argumentation, and revision?
- How do students conceptualise intellectual responsibility and authorship in AI-assisted writing?
- How do supervisors and institutions redefine independent research in the context of AI-supported knowledge production?
- Which linguistic and rhetorical indicators reveal levels of critical thinking and epistemic awareness in AI-assisted theses?
- How can pedagogical interventions foster critical thinking in AI-augmented academic environments?
An intercultural perspective
The project is explicitly intercultural. As AI technologies advance globally, we seek to understand whether the intellectual challenges they introduce are similar across different educational systems, or whether they manifest differently depending on academic cultures, institutional traditions, and linguistic contexts.
Our TRAI consortium brings together three institutional partners:
- Institute of Information and Communication Technologies, Bulgarian Academy of Sciences (BAS), Bulgaria – expertise in computational linguistics, language resources, and intelligent text analysis tools.
- West University of Timișoara (WUT), Romania – expertise in corpus-based writing research, contrastive rhetoric, and digital humanities.
- Zurich University of Applied Sciences (ZHAW), Switzerland – expertise in academic writing research, digital writing technologies, AI-supported feedback systems, and MOOC development.
By comparing data from German-, Romanian-, and Bulgarian-speaking contexts, the project investigates whether AI-induced shifts in writing and thinking represent a global convergence or culturally shaped adaptations.
A multi-layered empirical design
To capture these transformations, the project combines qualitative and corpus-based methodologies across two data collection phases.
1. Interviews and surveys
We conduct:
- Semi-structured interviews with Bachelor’s students
- Semi-structured interviews with thesis supervisors
- Large-scale student surveys on AI use and AI literacy in thesis writing
These data allow us to explore perceptions, practices, uncertainties, and institutional responses surrounding AI-assisted thesis writing.
2. A Multilingual thesis corpus (TEZEC)
A central component of the project is the creation of a multilingual corpus of 300 Bachelor’s theses (German, Romanian, Bulgarian).
This corpus enables computational and linguistic analyses of indicators of critical thinking and epistemic awareness, including argumentation patterns, author positioning, hedging, complexity, and rhetorical structuring.
3. Digital infrastructure and teaching innovation
The project produces two major educational and research infrastructures:
- eTEZEC Platform:
A multilingual, open-access platform that allows corpus searches, linguistic queries, and access to research findings and teaching recommendations. - MOOC (Moodle-based teaching platform):
A multilingual course on AI use in thesis writing, providing guidance on academic work, responsible AI use, and the cultivation of critical thinking. The MOOC functions both as a pedagogical intervention and as a research instrument to assess how structured AI literacy training affects writing practices.
Why this matters
Thesis writing is often described as a “capstone experience” of undergraduate education. It is where students transition from knowledge consumers to knowledge producers. If AI transforms this process, it may also transform the intellectual foundations of higher education itself.
By combining intercultural comparison, qualitative inquiry, computational corpus analysis, and pedagogical innovation, this project seeks to map the emerging forms of digital scholarship in the age of AI.
The central question remains urgent:
If machines can assist in generating arguments and synthesising knowledge, what does it mean, for students to think critically?
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Title project: Exploring the Triad of Academic Writing, Critical Thinking and AI Literacy: Interdisciplinary Perspectives on Undergraduate Thesis Writing PI Bulgaria: Prof. Dr. Habil. Petya Osenova, Institute of Information and Communication Technologies Bulgarian Academy of Sciences PI Romania : Assoc. Prof. Dr. Habil. Madalina Chitez, Department of Modern Languages and Literatures West University of Timisoara, Romania PI Switzerland: Dr. Christian Rapp, Zentrum für Innovative Didaktik School of Management and Law Zürcher Hochschule Winterthur Project partner: Period: 2025-2029 Financed by: SNSF / Swiss National Science Foundation, within the framework of the program Multilateral Academic Projects (MAPS) Co-financed by: |
More information about the project here.