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Reconfiguring teachers' work through automated evaluation

Publication date
2024-12-20
Document type
Sammelbandbeitrag oder Buchkapitel
Author
Alirezabeigi, Samira
Decuypere, Mathias
Hartong, Sigrid 
Organisational unit
Transformation von Governance in Bildung und Gesellschaft 
DTEC.bw 
DOI
10.24405/16812
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/16812
ISBN
978-3-86818-329-0
Project
Smarte Schulen 
Book title
dtec.bw-Beiträge der Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg : Forschungsaktivitäten im Zentrum für Digitalisierungs- und Technologieforschung der Bundeswehr dtec.bw : Band 2 – 2024
First page
291
Last page
296
Is part of
https://openhsu.ub.hsu-hh.de/handle/10.24405/16768
Peer-reviewed
✅
Part of the university bibliography
✅
Files
 openHSU_16812.pdf (375.38 KB)
  • Additional Information
Keyword
dtec.bw
Digitization of schools
Teachers' work
Automated evaluation practices
Grading
SMASCH (Smart Schools)
Abstract
Over the past years, the potential benefits and risks of educational technologies (EdTech) in schools have been increasingly debated. At the same time, research has only started to develop a more nuanced understanding of the manifold pedagogical effects of these technologies in school and classroom practice. Within the broader context of the dtec.bw project SMASCH (Smart Schools), which aims at supporting schools in their digital transformation, this chapter focuses on concrete manifestations and effects of automated evaluation practices on teachers' work. More specifically, the study analysed the screen recordings of ten digital tests from the moment of their creation to their archiving and is equally based on interviews with teachers about their evaluative practices. The findings of the study indicate different and ambivalent processes that reconfigure the relations between teachers and technology, which we exemplify using two cases – when teachers make digital tests for later automation, and when teachers supervise the machine's actual grading and feedback provision practices. Our findings not only offer important conclusions regarding how automated evaluation can, and should, be more strongly framed in a pedagogical manner, but they can also inform the need for a careful response to the more recent rise of GenAI technologies.
Version
Published version
Access right on openHSU
Open access

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