The quality of digital curriculum resources for mathematics in German educational policy

This paper examines the governance and quality control of digital curriculum resources (DCR) for K-12 mathematics education in Germany. It focuses on approval processes and criteria set by the 16 federal states, arguing that these have the potential to influence the development of DCR. Using qualita...

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Bibliographic Details
Published in:ZDM Vol. 57; no. 5; pp. 891 - 904
Main Author: Rezat, Sebastian
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2025
Springer Nature B.V
Subjects:
Artificial intelligence
Connectivity
Content analysis
Criteria
Curricula
Customization
Education
Educational Objectives
Educational Quality
Educational Resources
Expectation
Fundamental Concepts
Individualized Instruction
Influence of Technology
Instructional design
Instructional Materials
International Organizations
Investigations
Learning Activities
Mathematics
Mathematics Education
Mathematics Instruction
Multimedia
Opportunities
Original Paper
Outcomes of Education
Qualitative analysis
Quality control
Quality standards
School Policy
Schools
Socialization
Structural Elements (Construction)
Students
Teaching
Textbooks
Germany
ISSN:1863-9690, 1863-9704
Online Access:Get full text
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Summary:This paper examines the governance and quality control of digital curriculum resources (DCR) for K-12 mathematics education in Germany. It focuses on approval processes and criteria set by the 16 federal states, arguing that these have the potential to influence the development of DCR. Using qualitative content analysis, the study explores three research questions: which DCR require official approval, the criteria applied for approval, and the extent to which these criteria are mathematics-specific. Findings indicate that 10 federal states maintain official approval systems, covering digital equivalents of printed textbooks and selected supplemental materials. However, most DCR fall outside these regulated processes, leaving their evaluation largely to individual schools and teachers. The study identifies 17 categories of quality criteria, but reveals a lack of detailed, mathematics-specific requirements. Instead, many criteria are broad references to didactical principles and educational goals, leaving the interpretation and application of these quality standards open-ended. Subject-specific criteria are included but remain limited in specificity. The study underscores the need for research-informed, mathematics-specific quality standards to guide DCR development and approval, emphasizing their importance amidst challenges like artificial intelligence. Policymakers are urged to adopt clearer criteria to ensure high-quality DCR to be used in schools.
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ISSN:1863-9690
1863-9704
DOI:10.1007/s11858-025-01708-w