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TUHH Open Research - Research Data TUHH
Conference object . 2025
License: CC BY NC SA
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TUHH Open Research (TORE)
Conference object . 2025
License: CC BY NC SA
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Practice Reflections Within a Workshop: Supervising Students' Scientific Reading in Thesis Writing in Times of Artificial Intelligence

Authors: Bulmann, Ulrike; Stahlberg, Nadine;

Practice Reflections Within a Workshop: Supervising Students' Scientific Reading in Thesis Writing in Times of Artificial Intelligence

Abstract

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.

Country
Germany
Keywords

DR, TL, Social Sciences::371: Teachers, Methods, and Discipline::371.3: Methods of instruction and study, Thesis Supervision, AI Literacy, Reading Competences, Computer Science, Information and General Works::006: Special computer methods::006.3: Artificial Intelligence, Critical Literacy, Social Sciences::378: Higher Education (Tertiary Education)::378.1: Organization and Management; Curriculums

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green