Projects of the CATALPA Research Center
Photo: Henrik Schipper
In our projects, scientists from CATALPA and in-kind project leaders from the faculties use the unique research opportunities of the cluster. Through the connection to the FernUniversität with its numerous and diverse students studying digitally and hybrid, they achieve valid results in the area of the individualization of higher education through the possibilities of digitalization. They are in constant exchange and cooperate with relevant scientific institutions, which can use this special field of research together with CATALPA.
Our interdisciplinary teams from computer science, computational linguistics, psychology, sociology or educational science gain a wide range of insights - from fundamental research to application in large groups.
Aiducator
How can feedback be generated automatically in a scalable, timely, and cost-effective manner? With the Aiducator project, our researchers have set themselves the goal of generating personalized feedback in real time and tailoring it to the individual needs of learners. Aiducator is being tested and researched for competency-based assessments in conceptual modeling in computer science, with the aim of expanding the tool.
AIM-HE
What are the conditions of AI in higher education? What role do multi-levels and its associations play? What is the contribution of AI technology characteristics? These and other fundamental questions are the focus of the project explicitly dedicated to artificial intelligence in universities.
ASLAN
In addition to imparting knowledge, assessing learning success is one of the most important tasks in any teaching and learning process. Free-text assignments, i.e., assignments that require a short, freely formulated text as an answer, play a central role in many subjects. The researchers are investigating how they can use AI to support the correction of such assignments and are taking a novel approach. (DFG funded)
DECIDE
Under which circumstances is choice beneficial for students and under which circumstances can it be detrimental? DECIDE explores the consequences of choice in the context of distance learning – also taking into account student diversity.
LEAD:FUH
The LEAD:FUH (Learning Empowerment through Analytics and Data) project aims to develop a transferable change management concept for a university-wide teaching architecture that enables the systematic use of learning analytics (LA) in degree programs with different subject-specific requirements.
METALADIN
How can tasks that promote complex thinking processes be generated automatically and in a scalable manner? Researchers working on the METALADIN project are addressing this question. They want to create personalized, iterative exercises for competence-oriented tasks. Their focus is primarily on the skills of analysis, evaluation, and creation.
MULTIDIVERSE-CSCL
Collaboration in virtual study groups is beneficial for students’ sense of belonging and performance in distance education. However, student diversity can impair the collaboration within the study groups. The project investigates the influence of stereotypes on the collaboration and develops technological support for virtual study groups.
OrA/ORC
The ORC project analyzes the interrelationship between resilience, creativity and educational technologies. It also elaborates concrete recommendations for action for the university as an organization. ORC builds on the OrA project, which looked at the implementation of educational technology in international higher education institutions.
SRL-Agent
How can we better understand and support students’ self-regulated learning (SRL) skills and strategies? This project revisits one of the instruments for measuring SRL—structured interviews—which, despite it validity, have long been underused due to time-consuming and resource-intensive nature. By combining multi-agent system (MAS) and learning analytics (LA), we aim to overcome these limitations and examine how automated SRL interviews can complement existing tools and methods.
Former Projects
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NOVA:ea
Is it even possible to test online in a meaningful way? And how can the diversity of students be taken into account? In the NOVA:ea project, study-oriented e-assessments are implemented, scientifically monitored and evaluated - in cooperation with RWTH Aachen University, TH Cologne and the German Institute for Adult Education.
KISS.Pro
Preparing language teachers for the competent use of AI-based systems - that is one of the goals of KISS-Pro. The joint project of four universities develops and tests professionalisation concepts for teachers that address the opportunities, reservations, factual limits and problems of AI in the school context.
IMPACT
Better higher education thanks to artificial intelligence - the IMPACT cooperation project not only researched the use of trusted learning analytics and AI in university teaching, but also provided scientific support for implementation.
AI.EDU/AI.EDU 2.0
Artificial intelligence that supports learners and teachers in processing and structuring study content - AI.EDU has researched how exactly this can be achieved.
DAKODA
How can the language of German learners be analyzed automatically? DAKODA did some groundwork here. Various learner corpora were merged into a large overall data set with search and filter functions. At the same time, young researchers in the field of German as a foreign language and German as a second language were trained in the handling of large data sets.
APLE/APLE II
Knowing where one's own weaknesses lie, where learning gaps exist, and thus raising awareness of one's own learning process - APLE (I and II) investigated how a digital platform can best support students in their learning success. For example, students received recommendations for their next learning steps and could reflect on their learning behavior through visualizations.
LA DIVA
Learners are individual, have different strengths, are in different stages of life, and therefore need different types of support, especially in digital distance learning. This was precisely where LA DIVA came in and determined the potential of learning analytics.
InterMINT
How can we better support international students in Germany, especially in STEM subjects? In order to answer this question, we must first determine which predictors are crucial for academic success here. The InterMINT project investigated this with the help of data from the "International Student Survey" study progress panel.
LAMASS
Why do some students drop out while others continue successfully? Data on this is based predominantly on the present teaching of traditional universities. If we want to know more about the factors in digital studies, it helps to look at distance learning universities as a comparison group. In the research project LAMASS@DiLea, Prof. Dr. Claudia de Witt's department of educational theory and media pedagogy investigated factors for academic success and dropout in digital study formats and compared these insights directly with traditional studies.
KISTRA
Police crime statistics showed a significant increase in politically motivated Internet-related crimes in recent years. Investigating authorities need tools that are tailored to their needs, enable pre-filtering and support them in criminal prosecution. KISTRA explored the possibilities of using Artificial Intelligence to detect, prevent and prosecute crimes. The subproject led by CATALPA research professor Torsten Zesch was specifically concerned with the question of how the criminal liability of hate speech in social media can be modeled computer linguistically.
WisPerMed
The Research Training Group WisPerMed was a highly diversified and interdisciplinary team of computer scientists, pychologists, and physicians. Together we aimed for the fusion of Artificial Intelligence and medical decision support to drive forward knowledge and data-based personalization of medicine at the Point of Care.
Explaining AI
Artificial intelligence as a black box? Automatic assessment algorithms that can reliably evaluate learner responses create important capacities for teachers in the education sector. But what if learners can't do anything with the feedback? Explaining AI explored methods to generate helpful feedback using AI in the future.
Do I belong?
Does the ethnicity and thus the expectation that students with migration background are stereotyped impair equal opportunities? "Do I belong?" dealt with the consequences of perceived stereotype threat for the social inclusion and social relations of young people with a migration background in the German school context.
DivAdapt
The project dealt with the description, prediction, and explanation of diversity effects in computer-supported collaborative learning (CSCL). One goal of the project was to develop evidence-based diversity-enriched optimization of CSCL in higher education.
Permeability
This project was concerned with the permeability between vocational education and bachelor’s degree - from IT specialist to bachelor’s degree in computer science.
Universities of the Future (HdZ)
The Universities of the Future project (duration: 1 May 2017 to 30 April 2018) examined the demands of digitalization on universities, their strategic processes, and their politics.
to the project (in German)
