The use of educational technology and related efforts to individualize and optimize learning (keyword: learning analytics) as well as data-based decision making are transforming educational practices, including learning and teaching, assessing and counseling, and pedagogical decision making (Hartong et al., 2025; Krein & Schiefner-Rohs, 2021; Macgilchrist et al., 2023). Data, as a ubiquitous element of these developments, becomes increasingly meaningful in educational settings and in teachers' everyday work, with data literacy emerging as a key media education skill (Hepp et al., 2022; Wolff et al., 2016). This leads to new demands on teachers' professional competence, requiring them not only to understand data and its implications, but also to critically reflect on it and use it responsibly in educational settings. Data literacy, therefore understood as the ability to read, analyse, interpret, create and communicate data, as well as to critically evaluate the relevance and credibility of data, reflect on ethical implications and interpret social and contextual conditions, is a key prerequisite for meeting these expectations (Jarke & Breiter, 2019; Altenrath et al., 2021; D'Ignazio & Bhargava, 2016). However, data literacy has only been integrated into teacher training to a limited extent. Despite the high level of interest among teachers in data-based approaches, they report feelings of unpreparedness when it comes to working with data (DATA-READY Consortium, 2025).

The EU project DATA-READY (Erasmus+ Policy Experimentation) aims to address this gap. Using a multidimensional approach, the project conducted an international survey, including literature reviews, document analyses, surveys and interviews in five countries (Germany, Greece, Portugal, Poland, Cyprus) to examine current strategies and practices on data literacy (DATA-READY Consortium, 2025). Based on the findings, a comprehensive Data Literacy Framework was developed to define essential data literacy competencies for teachers and students in compulsory education. Building on the Data Literacy Framework, a higher education course was developed that translates the identified data literacy competencies into specific learning objectives and content. The overarching goal is to establish data literacy as a core component of professional teaching competence in teacher training, thereby addressing the existing need for professionalisation. Since data literacy is a multidimensional, complex construct, promoting it within an educational setting with limited time resources poses major challenges. In order to exchange and discuss experiences in this area at a European level, the contribution provides a structured overview of the course design and reports first insights from the development and piloting process. It addresses the following research questions:

1. What specific challenges arise when designing a higher education course for promoting data literacy in teacher training?

2. What aspects need to be considered in order to transfer the course to other (European) countries? 

3. How do students assess the relevance of the course content for their future professional practice?

The higher education course is designed according to the constructive alignment approach (Biggs & Tang, 2011), which ensures consistency between the intended learning outcomes, teaching and learning activities, and assessment methods. The course is grounded in a theory-based European framework for promoting data literacy, which delineates seven dimensions with associated competencies and specific learning objectives. The content of the framework will be translated into competency-oriented modules for an adaptive blended learning seminar; this allows for the flexible adaptation of the course format to different higher education contexts, including face-to-face, online or blended learning formats. Each module focuses on specific aspects of data-related competences and integrates content modules, exercise formats and reflection tasks, which are supported by detailed teaching and learning guides. The course content and materials will be evaluated with students during the summer semester of 2026 using research-based learning methods (Reinmann et al., 2019). The evaluation's objective is to examine the extent to which the materials and content provided illustrate and promote the relevance of data literacy for students' future professional practices.

The development of the course to date, in collaboration with European project partners, has revealed significant challenges in coordinating the practical requirements of teacher training. These include suitable teaching formats, assessment strategies, and structural integration into universities. Furthermore, transferring this course to the higher education contexts of the project partners (e.g., institutional structures, linguistic and cultural adaptations, etc.) is proving to be challenging. These challenges are presented, appropriate strategies for dealing with them as well as their success are outlined. As the pilot course will be completed in Germany in the summer semester of 2026 (April–July) and the evaluation of the content will take place there with the students, the poster will be supplemented by the results of this phase at ECER 2026. These insights are of particular European relevance because they inform the transferability of a framework-based higher education course across diverse teacher education contexts and contribute to building shared competence expectations for data-informed and ethically responsible teaching in Europe.

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