Research Programme: EdTEch&AI – Educational Technologies and Artificial Intelligence

Together with her team, Prof. Nikol Rummel is interested in how teaching and learning processes can be examined, supported, and improved in technology-supported environments.
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With expertise spanning Education, Educational Psychology, Media Psychology, and Computer Science, the research program investigates various aspects of using digital technologies & Artificial Intelligence (AI) in educational contexts.

Determine the quality of cooperation with learning analytics

Self-regulated learning in adult education

From the perspective of the research programme, the role of technology and AI in education is to complement human skills rather than replacing them. The researchers recognize the use of technology and its potential to facilitate learning and teaching through personalized support. However, they also acknowledge the challenges and limitations of using technology in education and strive to take a critical and realistic approach to its implementation.

Learning with AI-generated texts

Prof. Dr. Nikol Rummel

 

Head of the EdTEch&AI research programme
bki@cais-research.de

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Research areas

In the area of Learning with technology & AI, the research program is interested in individual and small group learning across diverse educational settings such as schools, universities, vocational education as well as non-formal learning settings (e.g. museums).

 

In the area of Teaching with technology & AI, the researchers explore competencies and needs of teachers. The researchers identify opportunities and challenges that educators encounter when teaching in digital environments, examining how they adapt digital learning materials. Particularly, the researchers investigate the role of teacher dashboards, how they can inform the teacher and how teachers can use them to improve their teaching.

 

At the intersection of learning and teaching, the researchers explore how Learning Analytics can support both learners and educators in schools, university settings, as well as out of school settings. Furthermore, the team scrutinizes the ethical and privacy implications associated with AI tools.

 

Projects

Third-party funded research projects

Teacher-AI Complementarity (TAICo). A Horizon Europe Project on AI and the future of the teaching profession.

Partners: University for Continuing Education Krems (Austria), University of Oulu (Finland), Tallinn University (Estonia), Radboud University (The Netherlands), University College London (United Kingdom), European Edtech Alliance (Germany), Education and Youth Board (Estonia), European Digital Learning Network (Italy), The European Trade Union Committee on Education (Associated Partner) (Belgium)

The Teacher-AI Complementarity (TAICo) project will explore the role of Artificial Intelligence (AI) in complementing teachers’ skills across various educational contexts. With the increasing presence of AI technologies in education, it is critical to understand how AI can support rather than replace the human element in teaching, particularly in the development of essential skills such as problem-solving, collaboration, and self-regulation. Funded by the EU Horizon program, this initiative spans six countries: Austria, Estonia, Finland, Germany, the Netherlands, and the UK. TAICo will engage directly with practitioners across primary, secondary, higher education, and continuing education sectors. The project focuses on how AI technologies can align with human teaching tasks, augmenting teachers’ strengths while maintaining their critical role in the learning process. The project’s goal is to provide evidence-based guidelines for integrating AI tools into classrooms, ensuring they effectively support teaching practices. TAICo’s participatory approach, involving teachers, policymakers, and EdTech developers, will ensure that AI solutions are both practical and ethically sound, meeting the evolving needs of modern educational environments.

Further Information: https://taico-project.eu/

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How Modes of Social Regulation Emerge and Impact Learning from Collaboration (MoRe)

Partners: Interim Prof. Dr. Sebastian Strauß  (Ruhr-Universität Bochum), Isis Tunnigkeit (Ruhr-Universität Bochum), Prof. Dr. Nikol Rummel (CAIS)

In cooperative learning, regulation is required both at the individual level and at the group level. Based on theories of self-regulated learning, Co-Regulation of Learning (CoRL) and Socially Shared Regulation of Learning (SSRL) have been described as additional modes of social regulation. These differ in the degree of transactivity within the interactions between learners. The planned project aims to further develop the precise measurement of the social regulation modes CoRL and SSRL, to systematically investigate the conditions under which these modes occur, and to explore their relationship to individual learning success. To address these research questions, laboratory experiments will be conducted in which students collaborate in pairs (dyads) within a digital simulation. Particular attention in these studies will be paid to the composition of the dyads with respect to various learner characteristics, such as domain-specific prior knowledge or learning goals, and how these factors influence both the cooperation process and the knowledge acquisition of the group members.

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