ViFoNet

The overarching goal is the research-based creation, implementation, evaluation and dissemination of video-based training concepts and modules for digitally supported teaching in the participating subjects German, German as a second language, English, French, Spanish, geography, economics and chemistry (with a focus on technical language) as well as on the overarching topic of education for sustainable development. For the modules, task formats with teaching and explanatory videos for the use of digitally supported teaching resources in subject lessons are created and used as effective, practice-oriented training elements. This is done in continuous consultation with those responsible for practical teacher training.

The project is part of the “learn:digital transfer centre“

Educational research at the University of Münster

Educational research at the University of Münster is characterised by the broad academic spectrum of a comprehensive university which is one of the largest centres for teacher education in Germany. This research is based on the consistent interdisciplinary linking of educational science and subject-specific didactics. Projects based at the University of Münster are notably practice-oriented and systematically analyse transfer and implementation processes. The Zentrum für Lehrkräftebildung (ZLB) coordinates the interplay of educational science and subject-specific didactics across disciplines and departments. Educational research at the University of Münster aims to investigate the fundamentals of general and subject-specific learning and teaching, develop evidence-based concepts to leverage educational potentials, and evaluate and transfer these innovations for implementation.

Key areas of work and services:

  • Fundamentals of Teaching and Learning: The basics of general and subject-specific learning and teaching are explored in diverse projects conducted by the didactics disciplines.
  • Development and Evaluation of Educational Programmes: Innovative concepts and materials are developed and evaluated to promote competencies across the whole spectrum of academic educational goals.
  • Transfer: A hallmark of the majority of our projects is a close cooperation with school practice partners and a focus on the transfer and implementation of evidence-based, innovative concepts. This research is supported by high-level infrastructure, including several video portals, practice and teaching-learning laboratories, and collaborations with professional development platforms.
  • Professional Development: The dissemination of research findings occurs, among other means, through professional development offerings, which are themselves the subject of transfer and implementation research. Educational science at the University of Münster collaborates with the Münster District Government, the NRW Institute QUA-LiS, and the NRW Ministry of Education, for instance, through the NRW State Competence Centre for Individual Support (lif).
  • Teacher Education: Research activities also encompass the field of teacher education. This involves a wide range of competencies, including subject-specific, didactic, and pedagogical professional knowledge as well as motivational, volitional, and social skills

E-ADAPT

For more than 20 years, international comparative studies have shown that many European students do not have the core basic competencies they need to participate fully in society.

Therefore, the E-ADAPT project’s guiding principle is the ideal of adaptive teaching that supports all learners equally to reach their full potential, which is already increasingly becoming a reality in countries such as Estonia and Finland.

In the E-ADAPT project regular meetings of experts are organized, video documentations of adaptive teaching in numerous European countries created, a manifesto on adaptive teaching and learning created, available methods and technologies compiled, and scientific studies conducted.

KISS-Pro

Language plays a central role in learning at school – both as a communicative prerequisite and as a learning medium and learning objective. At the same time, it also represents a central dimension of heterogeneity. However, teachers often lack the time to support pupils with very different language learning needs individually in their acquisition of language skills. The use of new digital technologies, such as AI-based systems, offers the opportunity to constructively address the linguistic heterogeneity of learners in the context of participation and equal opportunities.

Natural language processing (NLP) applications such as ChatGPT or DeepL are currently developing extremely dynamically and have recently made great progress in the linguistically correct translation of texts and in AI-supported machine text production. The use of such systems therefore has the potential to support teachers in designing individualised language learning opportunities for pupils, for example.

Appropriate professionalisation concepts are needed to prepare teachers for the competent use of AI-based systems in schools and subject lessons. The joint project is therefore developing target group-specific information and qualification programmes that not only impart knowledge about the opportunities and potential of AI-based systems, but also address fears and reservations as well as concrete, factual limits and problems of using AI in the school context.

The joint project will specifically highlight the possibilities of individual feedback for pupils through NLP as well as the possible applications of intelligent tutorial systems and social robots. It also focuses on reflecting on the ethical, legal and social implications of using AI-supported systems in the school context.

Connection to practice, transfer and implementation

The transfer of the developed professionalisation offers for the use of AI-based systems in language teaching into teacher training and thus also into school practice is a central goal of the project network. The concepts are being developed in close collaboration with the cooperating state institutes in Berlin-Brandenburg, Hamburg, Lower Saxony and Schleswig-Holstein. In addition, the developed concepts are to be embedded in the university teacher training programme. In this context, a transfer conference on the topic of AI for university teaching in teacher training programmes will take place at the University of Potsdam in 2025.

The concepts developed will be made available in the form of Open Educational Resources (OER) to enable the modular professionalisation courses to be implemented beyond the participating federal states. The sustainable transfer into practice is also supported by Zukunft Digitale Bildung gGmbH, the Forum Bildung Digitalisierung and the KI-Campus as transfer partners.

DigiProMIN

The aims of DigiProMIN are the research-based development of professionalization modules for the design of digitally supported STEM lessons, the identification of effective possibilities for the use of digital media in further education and training and the design and implementation of a transfer strategy at various levels.

The professionalization modules developed in the network take digitality into account in different ways. Firstly, further and continuing education measures are being designed to (further) qualify teachers of mathematics, computer science and natural sciences for teaching with digital media (“professionalizing teachers for digital media”). On the one hand, these have been developed specifically for the subjects mentioned, while on the other hand they also cover cross-curricular teaching and learning approaches, e.g. for subject teaching. The professionalization modules are related to specific digital teaching materials and tools and are intended to enable teachers to conduct comprehension-oriented, cognitively activating and adaptive lessons with digital media. The focus here is on the development of a coherent range of lessons rather than the use of individual digital tools.

Secondly, it examines how digital media can be used sensibly for the further and continuing education of teachers by developing and implementing digitally supported further and continuing education measures – using virtual reality, simulations and online platforms (“Professionalizing teachers with digital media”).

Connection to practice, transfer and implementation

The professionalization modules are developed in consultation with the specialist managers of the state institutes. They are the subject of the network’s multidimensional transfer and implementation strategy.

  • The material transfer and implementation strategy consists of preparing the results achieved in the project (professionalization modules, digitally supported teaching materials and concepts for digitally supported further education and training) as Open Educational Resources (OER) and making them digitally available nationwide. To this end, existing platforms such as LERNEN.Cloud and Clearing House Unterricht will be networked and expanded.
  • The personal transfer and implementation strategy refers on the one hand to the integration of the modules developed in the project into structured subject-specific or STEM-related further education and training programs of the countries participating in the network as well as into co-constructively designed networks (as professional learning communities of teachers). In doing so, the network is guided by the activities of the German Center for Mathematics Teacher Education (DZLM) as a possible blueprint for a learning:digital STEM competence center.
  • Finally, a systemic transfer and implementation strategy will be implemented by supporting cross-phase cooperation, including the qualification of multipliers and supra-regional cooperation. The systemic strategy also includes the provision of control-relevant knowledge by developing and empirically validating instruments for recording the digitalization-related skills of teachers.

The systemic strategy is being tested as an example in three federal states in cooperation with the respective state institutes and quality institutions. These are Bavaria with the Akademie für Lehrerfortbildung und Personalführung (ALP) and the Staatsinstitut für Schulqualität und Bildungsforschung (ISB), Brandenburg with the Landesinstitut für Schule und Medien Berlin-Brandenburg (LISUM) and the Ministerium für Bildung, Jugend und Sport (MBJS, Referat 45) and Schleswig-Holstein with the Institut für Qualitätsentwicklung an Schulen (IQSH).

Department of Educational Science at the University of Potsdam

The Department of Educational Science is part of the Faculty of Human Sciences at the University of Potsdam, which was founded in 1992. The orientation of the department is empirical-quantitative with a focus on the school education sector. The department’s research investigates central challenges in the educational context against the backdrop of individual, institutional and systemic characteristics. These include the significance of educational inequalities and how to deal with them adaptively in the educational context, the professional development of teachers and the development of innovative and effective technology-enhanced teaching and learning scenarios. In line with the Leibniz Association’s motto theoria cum praxi, the department’s profile is oriented towards a use-inspired basic research agenda, in which scientific insights and social benefit are closely linked. Accordingly, members of the department are heavily involved in shaping the dialog between science, educational practice and educational policy. In teaching, the department is responsible for educational science courses in teacher training. In addition, a separate Bachelor’s degree course and, from winter semester 2024 and 2025 respectively, two Master’s degree courses with different specializations (digital education, educational psychology and educational research) are offered.

Important work and offers:

  • Several professorships in the department are active in various project networks and in the transfer office in the BMBF-funded Kompetenzverbund lernen:digital. The project management including the office of the transfer office are located at the department.
  • Several professorships in the department cooperate with representatives of the Leibniz Institutes as part of the BMBF large-scale projects “Schule macht stark” and “Leistung macht Schule”.
  • One of the department’s professor is a member of the “Science of Intelligence” Cluster of Excellence of the Berlin university alliance.
  • Several professors are involved as lecturers in the IMPRS Research School LIFE, which is supported by the Max Planck Institute for Human Development Berlin and three international universities.
  • The department is committed to the transfer of knowledge and evidence-based policy advice at regional and national level. This includes memberships in the scientific advisory board of the Ministry of Education, Youth and Sport of the State of Brandenburg, in the committees of the Institute for School Quality of the States of Berlin and Brandenburg e.V., in the scientific advisory board of the steering group “Determining the performance of the education system in international comparison” and in the German UNESCO Education Committee.

IWWB-PLUS

The IWWB-PLUS project contributes to strengthening the continuing education landscape in Germany as part of the BMBF’s INVITE funding programme. The core of the project is to increase the attractiveness and user-friendliness of the proven continuing education platform InfoWebWeiterbildung (IWWB). This is to be achieved through the use of innovative technologies. The aim is to develop and implement dialogic technologies (chatbots) to optimise user guidance and integrate light assessments to personalise search results. Through comprehensive, evidence-based re-engineering of the UX design, the focus is on optimising the user experience on IWWB.

PISA-LDW

How do students learn to solve problems in the digital space? How can learning in digital environments be observed and assessed? How are core competencies of digital learning effectively supported? To answer these and other questions, innovative approaches to the diagnostic use of behavioral data from digital learning and assessment environments have great potential. The central goal of this accompanying research on the innovative domain in PISA 2025 “Learning in the Digital World” (LDW) is the development and empirical validation of such approaches.

As an innovative PISA domain, two areas of competence are to be covered that are of particular importance in digital learning contexts: The first is the competence to model complex systems and solve algorithmic problems with the help of digital tools. In doing so, the students go through a process of self-directed learning and “learn” how to solve the problems. On the other hand, the students’ ability to self-regulate this learning process is to be recorded. This means how they monitor, control and adapt this process in (meta-)cognitive, behavioral, motivational and affective terms. For this purpose, behavioral data from the processing of the tasks will also be used – these are obtained by presenting complex problems to the students on the computer in a simulated and interactive learning environment. The students work out solutions step by step – using the learning tasks, learning materials and aids offered in the learning environment. How they accomplish this and how successfully they do so is the subject of the measurement.
For example, in one learning unit, students are asked to create a program by combining commands that are available as blocks in order to control an game piece (see turtle in Fig. 1). The game piece should be made to collect the blue object and then move to a target position. The students can check their programmed solution again and again with the help of a test option, receive supportive feedback and further improve it using learning materials.

Fig. 1. Mockup of a sample task (train turtle) in the style of LDW units.

Mockup of a sample task


The indicators obtained from the behavioral data to capture the competence areas will be examined to determine whether the individual differences they depict can be interpreted in terms of the constructs in question (construct validation). For this purpose, the correlation structure between learning potentials or learning activities on the one hand and LDW problem-solving competence on the other hand will be examined (nomological network). Learning potentials include, among others, reasoning, prior knowledge, self-efficacy and motivation to learn, learning activities the activities in the LDW learning unit as well as preceding learning opportunities in the (extra)curricular setting.

In the context of the research project, (self-regulated) learning processes in digital environments are thus made empirically accessible, the influence of individual preconditions on the learning and problem-solving processes is investigated as well as their effects on learning success. The knowledge gained in the project contributes to a better understanding of learning processes and how they can be diagnosed in digital learning environments.

Objectives

  • Development of indicators to capture the LDW construct domains.
  • Validation of test score interpretations
  • Research on learning processes in interactive learning environments

LogDataAnalyzer

The LogDataAnalyzer reads out data consisting of unstructured process data (log files) and tabulates them. These tables can be further processed with any given spreadsheet or statistical package. Problem Solving Items of PIAAC („Programme for the International Assessment of Adult Competencies“) are analysed that require different actions and several processing steps. Single actions or whole sequences of actions can be selected with the LogDataAnalyzer, as far as they correspond to defined actions or sequences of actions in the log files. For the extraction, specific actions that are relevant for the individual research question are searched for in the log files.

The LogDataAnalyzer has been developed in co-operation with German Social Science Infrastructure Services (GESIS) and serves for data processing. The application of this tool does not need extensive training and can be used easily.

Field of Application

The LogDataAnalyzer was first applied in the DFG project Process Data for Competence Modelling, in which data of the field test are analysed. The extracted data are used amongst others to describe the relations between the result of the process of technology based problem solving items and characteristics of the processing.
The time needed for the solving process of items (Goldhammer et al., in press), the number of interactions between test takers and test surrounding (Naumann, Goldhammer, Rölke & Stelter, under revision) and the time needed for elementary steps of item processing proved to be explanatory predictors.

PIAAC-LN (Leibniz Network)

Competence tests are intended to model, beyond general cognitive skills, the outcomes of learning processes typically taking place in the context of schools. One example of such a learning outcome is reading comprehension. Tests for general cognitive ability, in contrast, are expected to measure more general skills that remain stable over time and are not learned in the school context, for example reasoning.

PIAAC-LN: PIAAC-LN consists of three different modules, which focus on (1) research on competence acquisition and use, (2) knowledge transfer and (3) networking. The sub-project at DIPF represents one out of five projects that belong to the first module. Under the direction of GESIS, the PIAAC Leibniz Network (PIAAC-LN) investigates the acquisition and use of competencies. In addition to the international PIAAC data, data from the longitudinal PIAAC-L study is used. The latter is managed by GESIS and funded by the Federal Ministry of Education and Research (BMBF).

Method

To investigate the research question, the project will draw on data from PIAAC competence assessments of Literacy and Numeracy and assessments of general cognitive competencies from PIAAC-L. Within this sub-project, a computer-based numerical series test, which serves as a central measure of general cognitive ability, will be presented to 800 persons in PIAAC-L.

To answer the research question whether competence tests do not only measure general cognitive skills but also model the outcomes of educational processes, the project will investigate

(1) to what extent competence measures can be distinguished from of general cognitive skills (with regard to dimensionality). For instance, whether success in competence tasks and general cognitive ability depends on a common skill, or whether different skills are involved.

(2)  whether the relationship between processing parameters such as processing time and success is comparable across general cognitive ability tests and competence tests.

(3) whether the relationship to background variables, e.g. age, duration and type of general and vocational education, is comparable across general cognitive ability tests and competence tests.