One of the distinguishing features of the DataScEd4CiEn project is its strong research foundation. Every stage of the project—from the development of the conceptual framework and the professional development programme to the design of classroom scenarios and the online platform—was guided by a rigorous research and evaluation process.
Rather than evaluating the project only at the end, the consortium adopted a Design-Based Research (DBR) approach, enabling researchers, teacher educators and teachers to collaboratively design, implement, evaluate and refine every project output. This continuous cycle of improvement ensured that all educational resources were evidence-informed, classroom-tested and responsive to the needs of teachers and students across Europe.
Research design
The DataScEd4CiEn project adopted a mixed-methods Design-Based Research methodology, combining quantitative and qualitative evidence to evaluate both the implementation process and the impact of the project.
The research focused on understanding how teachers develop the knowledge, confidence and pedagogical skills needed to integrate Data Science within STEAM education, while also exploring how students engage with authentic data to develop critical thinking, civic engagement and social justice awareness.
Rather than viewing evaluation as a final stage, the project embedded research throughout its lifetime. Evidence gathered during the first implementation informed the revision of the Professional Development Course, STEAM learning scenarios, research instruments and online platform before a second implementation cycle validated the improved materials. This iterative approach ensured that every project output evolved through continuous reflection and refinement.
A Continuous Cycle of Improvement
The project followed a two-phase implementation model that ensured continuous improvement through evidence-based decision making.
Phase 1 – Initial Implementation
The first implementation involved the delivery of the Professional Development Programme, the design of interdisciplinary STEAM scenarios, and their classroom implementation across partner countries. During this phase, extensive data were collected through surveys, teacher reflections, classroom observations and focus group discussions to evaluate both the educational resources and the implementation process.
Reflection and Redesign
Following the first implementation, the consortium analysed findings from all participating countries. Feedback from teachers, teacher educators and students was used to refine the conceptual framework, revise the Professional Development modules, improve the classroom scenarios, enhance the online platform and strengthen the research instruments.
Phase 2 – Final Implementation
The revised materials were implemented during a second cycle across partner countries. This final implementation enabled the consortium to evaluate the effectiveness of the improved resources and confirm their quality before publication as open educational resources available through the DataScEd4CiEn platform.
Research Instruments
A comprehensive set of research instruments was developed to gather evidence throughout the project. These tools explored teachers’ professional learning, students’ experiences, classroom implementation and the overall effectiveness of the DataScEd4CiEn approach.
Teacher Research Instruments
- Teacher Initial Survey
- Teacher Final Survey
- Professional Development Session Evaluation
- Teacher Reflection on STEAM Scenario Implementation
- Focus Group Discussion Protocol
Student Research Instruments
- Student Initial Survey
- Student Final Survey
Teacher Educator Research Instruments
- Teacher Educator Reflection Sheets
- Teacher Educator Diaries
- Semi-Structured Interview Protocol
Together, these instruments provided a rich understanding of how teachers and students experienced Data Science education within STEAM contexts and supported the continuous improvement of all project outputs.
Evaluation and Quality Assurance
Quality assurance was embedded throughout the project through both internal and external evaluation processes.
Internally, evidence from national reports, transnational implementation reports and the final evaluation report enabled the consortium to monitor progress, identify strengths, address challenges and evaluate the overall impact of the project across all partner countries.
To ensure objectivity, the project also underwent an independent external evaluation led by Dr Sibel Kazak (Middle East Technical University, Türkiye), an expert in statistics and data science education. The external evaluation reviewed the project’s conceptual framework, Professional Development Programme, STEAM scenarios, online platform and research methodology, providing valuable recommendations that contributed to the refinement of the project’s educational resources and overall quality.
Research Publications
Research has been a central outcome of the DataScEd4CiEn project. Findings have been disseminated through journal articles, conference papers, posters, workshops and seminars, contributing to the growing international field of Data Science Education within STEAM for civic engagement and social justice.
These publications document the project’s conceptual framework, professional development model, classroom implementations, research methodology and educational impact, ensuring that the knowledge generated extends beyond the lifetime of the project and supports future research and educational innovation.
Lasting Impact
The Research and Evaluation Work Package ensured that every DataScEd4CiEn output was grounded in educational research and validated through authentic classroom practice. By combining collaborative design, continuous evaluation and evidence-based refinement, the project produced a coherent collection of educational resources that have been tested by teachers, evaluated by researchers and reviewed by an independent external expert.
Today, the DataScEd4CiEn project offers far more than a collection of teaching materials. It provides an evidence-based educational approach that supports teachers in integrating Data Science, STEAM education, civic engagement and social justice into meaningful classroom learning experiences. The project’s research outputs, professional development programme, classroom scenarios and online platform will continue to support educators and researchers across Europe and beyond.
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.