The research group “Education for the Digital World: Technologies, Competencies, Paradigm Shifts“ focuses on the requirements for developing and designing digital teaching and learning processes and the possibilities and limits of individualization in education. The use of new technologies, especially AI, is researched from a theoretical and application-oriented perspective.
Our research focuses on the impact of digital transformation and digital technologies on education and competence development and the new requirements that will define these processes in the future. The group's applied research includes research, an ongoing transfer of requirements from practice (schools, universities, companies, society), and the application of research results to practice.
The group examines the similarities and differences in the context of school, university, and vocational education and training. The planned research program builds on preliminary work from the first phase of the Weizenbaum Institute, in which further research needs were identified as particularly relevant. These findings shape the work of the group, which is organized into the following subprojects:
A theoretical framework for digital learning
As a result of the digital transformation in the educational context, traditional forms of knowledge transfer, such as face-to-face events, are increasingly being replaced by digital formats. Overall, learning mediated via information and communication technologies in physical or virtual spaces can enable more active participation and a high degree of self-determination for individual learners. Learning objectives, methods and questions can be tailored more closely to the needs of the learner. Learning success depends not only on the cognitive abilities of learners and instructors and the content but also on aspects such as the medium used, the degree of individualization, access to information, location and timing, etc. Against this background, the research group has already developed an initial digital learning model as the first step toward a new digital learning theory. The model shows the relevant learning elements and their characteristics in the digital world: learners, teachers, learning mode, learning content, and learning output. These are specified for the circumstances of the digital world and described in their context. Explicit attention is given to where the differences and similarities to classical learning exist.
Human-AI interaction in the learning context
Many uses of AI in education lie in personalizing one-on-one instruction so that decisions are made about an individual student's learning path and the content to be taught. In addition, AI can support collaborative learning by organizing the online collaboration of a learning group; it can replace teachers and connect with students. Last, intelligent virtual reality can be used to create authentic virtual realities and gamified learning environments or to have learners tutored by virtual tutors. Different levels of human-AI interaction exist depending on the type of technical agents interacting with humans via mixed-initiative systems.
With this in mind, we explore human-AI interaction in digital learning environments in the context of education and corporate training, especially when AI plays an active role. We look at the limitations of this interaction in light of understanding learning as a social process and the social and ethical challenges of this interaction.
Personalization and individualization in digital learning processes
A key benefit of digital learning is the more significant individualization of the learning experience. The learning process and outcomes can be customized to the learner's prior knowledge by carefully organizing the learning task, sequence, medium, etc. In addition, the increasing use of ICT in the educational context allows targeted control of individual learning paths and specific definitions of learning times and goals. The targeted use of digital media can reduce inequalities among learners so that instruction can be designed appropriately and greater creative freedom is made possible for teachers and learners.
Here, targeted interdisciplinary research is needed that allows the central characteristics of a learner to be structured to address the learning process directly. The group's research shows that, for example, cultural aspects play a role here, subject-specific characteristics exert an influence on the acceptance of digital learning offerings, and educational offerings must be designed in an age-appropriate manner. Central questions against this background are connected with the core components of a personality model of learners and learning method fit challenges when addressing learners in an individualized way.
Various empirical projects are planned in all subprojects, such as literature analyses, studies, surveys, and (laboratory) experiments.
Research Group Lead