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Practice reflections within a workshop: supervising students' scientific reading in thesis writing in times of Artificial Intelligence
Citation Link: https://doi.org/10.15480/882.16838
Publikationstyp
Conference Paper
Date Issued
2025
Sprache
English
TORE-DOI
Start Page
1167
End Page
1176
Citation
53rd Annual Conference of the European Society for Engineering: Educating Responsible Engineers, SEFI 2025
Contribution to Conference
Publisher DOI
Scopus ID
ISBN of container
978-2-87352-029-8
To reflectively supervise students in final theses along the research process is very much under pressure in the age of artificial intelligence (AI). Being inspired by TL;DRs (abbreviation for «too long; didn't read», automatically generated hyper-short paper summaries), we emphasize in this article on the rather unattentive aspect of reading competences within the intertwinned reading – writing – researching – critical thinking approach. We asked: ''How can academics support students' reading competences when supervising them in their final theses in the age of AI?'' Thus, we encouraged reflection in a workshop for 17 supervisors by using (1) a self-designed, survey consisting of three parts: reflection, exercise and transfer, and (2) a peer exchange. Supervisors' reflections showed that they read scientific articles with joy, less time and rely on traditional reading strategies rather than using AI tools for reading. Being unaware of TL;DRs first, an exercise on writing and generating a hyper-short summary using a university's HAWKI-based LLM led them to evaluate the text quality to be both promising and risky. This resulted in assessing their training of competences to be multifaceted. Together, they updated their supervision guidelines considering multiple deskilling risks and various competence development potentials for students when using AI or not. Finally, we argue that such practical reflections and peer dicussions raise supervisors' awareness for responsible guidance of students in their final theses (best earlier within the curriculum) to strengthen their critical and AI literacy in an AI-enriched learning environment.
DDC Class
378.1: Organization and Management; Curriculums
371.3: Methods of instruction and study
006.3: Artificial Intelligence
Publication version
publishedVersion
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