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DI-daktika

The project aims to identify when digital didactics with elements of artificial intelligence (AI), informed by learning analytics (LA), enhance teaching, learning, and assessment.

The potential transformative power of Artificial Intelligence (AI) spans all economic and social sectors, including education. While there is no single definition of what AI is, this project focuses on generative AI, which is defined as a technology that automatically generates content in response to prompts written in natural language conversational interfaces (UNESCO, 2023).

Research confirms that AI can help teachers explain tasks to students, provide feedback to teachers, generate alternative tasks and assessment tools designed for enhancing achievement, and support the planning of the learning process. However, although considerable attention has been given to the development of AI technologies and ethical considerations, there is still a lack of research on learning analytics (LA)-based evidence for the didactical changes required to effectively use elements of AI in education.

Therefore, this project investigates how digital didactics enriched with elements of AI and informed by learning analytics can support effective transformations in teaching, learning, and assessment practices. The project also promotes a critical and evidence-based approach to the use of AI in education.

Project objectives and main activities:

1. To identify the challenges of teaching, learning, and assessment using elements of AI, informed by learning analytics (LA), in the classroom curriculum.
2. To develop a taxonomy of AI digital competence as a sub-set of digital competencies applicable to teachers and methodological guidelines on their development.
3. To design and assess pedagogical scenarios for using elements of AI, informed by learning analytics (LA), to enhance teaching, learning, and assessment.
4. To draw evidence-based recommendations for state institutions on how to substantiate solutions for using elements of AI, informed by learning analytics (LA), to improve the quality and sustainable advancement of classroom didactics and school education.

Key project results:

• Publication on the challenges of teaching, learning and assessment using elements of AI, informed by learning analytics (LA), in the classroom curriculum.
• Publication on the sub-set of AI digital competences of teachers.
• A research study on the application of pedagogical scenarios for using elements of AI in teaching, learning, and assessment.
• Methodological guidelines providing context and recommendations for how the taxonomy can be applied by school teachers to enhance teaching, learning, and assessment.
• Evidence-based recommendations for state institutions on how to substantiate solutions for using elements of AI, informed by learning analytics (LA).

The main research results will be presented at national and international research conferences and other scientific events.

International collaboration:

The project “DI-daktika” is grounded in a long-term international collaboration experience between the VMU Institute for Study Innovations and high-level experts from the Open University of Catalonia (UOC), Spain, and Dublin City University (DCU), Ireland, as well as other international higher education and research institutions. Multiple collaborative activities will be delivered, aiming to contribute to the internationalisation of this educational research.

Firstly, two high-level international experts and lecturers will contribute to this research. Prof. dr. Josep M. Duart from UOC is a widely recognised scholar in the application of technology in education and higher education, the founder of EDEN Digital Learning Europe’s annual doctoral symposium, and is involved in doctoral studies at universities around the world. Following his expertise, among other research activities within this project, prof. Duart will engage in theoretical analysis, analyse existing international practices, participate in the doctoral process, and contribute to paper publication and presentations.

Secondly, two international internships are planned throughout the project period, serving both the project researchers’ knowledge sharing and competence development, and involving high-level experts from recognised higher education institutions and research centres to share their expertise, insights, and experiences in the use of AI informed by learning analytics for teaching, learning, and assessment.

Thirdly, project researchers (a PhD student and the supervisor) will participate in two international research networks and programs, sharing and extending scientific discussions at a global level and thereby contributing to the exploration of the research problem.

Fourthly, scientific publications, the research study, and presentations at international conferences will contribute to the dissemination of the research at an international level.

Finally, an international scientific event will be organised to present the project and its results to international experts.

Project funding:

This research (No. P-EDU-23-1) is co-funded by the European Union through the project “Breakthrough in Educational Research” (No. 10-044-P-0001) under the 1 April 2025 Agreement with the Research Council of Lithuania (RCL) and the 17 April 2025 Joint Activity Agreement with Vytautas Magnus University.

Coordinator of the project “Breakthrough in Educational Research”: Research Council of Lithuania.

Partner institutions of the project “Breakthrough in Educational Research”: Vilnius University, Kaunas University of Technology, Vytautas Magnus University, Vilnius Gediminas Technical University, Lithuanian University of Health Sciences, Mykolas Romeris University, Klaipėda University.