TrainDL is a Policy Experimentation Project that aims to reduce the digital skills gap by democratising future skills through and across educational systems.
This is done by developing open educational resources (OER) and teacher training modules in three iterative field trials to meet the need for tested and evaluated teaching materials for data literacy and artificial intelligence (AI) education in schools across Europe.
With this project, new pedagogical approaches to data literacy and AI education will be incorporated into schools and teacher trainings to equip teachers of computer science, STEAM subjects, and primary education with the skills they need to address these topics in an accessible, accurate, and subject-specific way.
By focusing on data literacy and AI education, TrainDL acknowledges the need for up-to-date computer science education in schools across Europe, while taking into account the varying levels of access to dedicated computer science classes and the ubiquity of digitisation across fields.
Starting with the partner countries Lithuania, Austria, and Germany, the project outcomes will be adaptable for application in EU member states and beyond.
TrainDL's experimental setup (policy building workshops with different stakeholders to inform three field trials) makes it possible to address the actual needs and parameters that are given by policymakers throughout the educational systems within the three project countries. Evaluation of the effects of such policies and their implementation in repeated field trials will ensure scalability later on.
Besides the practical outcomes (teacher training modules and OER materials), it is a central goal of TrainDL to provide recommendations regarding the structural implementation of data literacy and AI competencies in different national curricula and educational systems across Europe.
In addition to the research findings and recommendations, a prototype will be developed based on the project states' data that will lead to a European Teacher Education Monitor for Data Literacy and Artificial Intelligence.
In the Policy Cluster, the educational policy situation with regard to the project goals (link) is surveyed, analyzed and further developed in close cooperation with relevant ministries and educational authorities. From this, guidelines for the education interventions of the Education Cluster will be developed and continually refined. In addition, the findings will be processed in a newsletter for teacher training and presented in recommendations to education policy decision-makers.
The Education Cluster is concerned with the didactic development and implementation of interventions in teacher training at the primary and secondary levels. New modules on data and AI competencies are being developed and applied directly in teacher training courses in three project cycles. The data and experiences gathered in the process will allow the Policy Cluster to work in an evidence-based manner. In addition, findings will be translated into in-service training modules and best practice recommendations.