I Don’t Know Who You Are, but I Know What You Need: Guidelines for Federated Learning in Educational Recommender Systems

Enrico Kochon (), Daniel Stattkus (), Simon Binz (), Marian Eleks (), Nils Lauinger (), Philipp Fukas (), Ann-Kristin Claudia Müller (), Julia Knopf () and Oliver Thomas ()
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Enrico Kochon: Osnabrück University, Information Management and Information Systems
Daniel Stattkus: Smart Enterprise Engineering, German Research Center for Artificial Intelligence
Simon Binz: Smart Enterprise Engineering, German Research Center for Artificial Intelligence
Marian Eleks: Strategion GmbH
Nils Lauinger: Saarland University, Forschungsinstitut Bildung Digital
Philipp Fukas: Osnabrück University, Information Management and Information Systems
Ann-Kristin Claudia Müller: Saarland University, Forschungsinstitut Bildung Digital
Julia Knopf: Saarland University, Forschungsinstitut Bildung Digital
Oliver Thomas: Osnabrück University, Information Management and Information Systems

A chapter in People, Society, and Ethical Challenges of Information Systems, 2026, pp 307-322 from Springer

Abstract: Abstract The ongoing digitalization of the education sector yields great potential through the use of Artificial Intelligence but is decelerated by a necessity for privacy and security. This paper investigates the potential of Federated Recommender Systems in school education as a solution to this problem within a two-cycle design science research approach. Meta-requirements for Federated Recommender Systems are extracted from the literature and evaluated through an educational prototype. To balance the technical evaluation, practical design guidelines are articulated and evaluated by a focus group of experts resulting in tangible guidelines for practitioners and educational stakeholders.

Keywords: Federated Learning; Education; Recommender Systems; Design guidelines; Design science research; Information systems (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-08486-6_21

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