Forschungs- und Entwicklungsprojekte

Laufende Forschungsprojekte

• FLAIR—Facilitating Learning with Artificial Intelligence, ongoing since 2023
  Research network
  Following a successful 5-year project promoting Self-Regulated Learning (SRL) through real-time personalized scaffolds (FLoRA), the promoted early-career project members of the project have initiated the international research network, “Facilitating Learning with Artificial Intelligence (FLAIR)”, in order to extend the prior research efforts. The general aim of the research network is to advance research in SRL in the age of AI. Current and planned network research activities comprise of intensive scientific exchange, joint publications and conference and project proposals on this innovative research topic.
  The research network collaborators are: Dr. Lyn Lim, Technical University of Munich (TUM), TUM School of Social Sciences and Technology, Chair for Teaching and Learning with Digital Media, Germany; Asst. Prof. Joep van der Graaf, Radboud University Nijmegen, Behavioral Science Institute, Adaptive Learning Lab, Department of Orthopedagogics: Learning and Development, The Netherlands; Asst. Prof. Yizhou Fan, Peking University, Graduate School of Education, China.
  Contact person: Dr. Lyn Lim
   
• FLoRA - "Facilitating Self-Regulated Learning with Personalized Scaffolds on Student’s own Regulation Activities", 2019 - 2023
  Project funded by Open Research Area for the Social Sciences (ORA; DFG: BA2044/10-1)
  Education has been geared towards students’ ability to regulate their own learning within technology-enhanced learning environments (TELs). Prior research has shown that self-regulated learning (SRL) leads to better learning performance but students often experience difficulties to adequately self-regulate their learning. They can be supported by instructional scaffolds which consequently improve learning outcomes. However, scaffolds are often not standardized and individualized. Learning analytics and machine learning offer an approach to better understand SRL-processes during learning. Yet, current approaches lack validity or require extensive analysis after the learning process. This project aims to advance support given to students by i) improving unobtrusive data collection and machine learning techniques to gain better measurement and understanding of SRL-processes and ii) using these new insights to facilitate student’s SRL by providing personalized scaffolds. The researchers involved will reach this goal by conducting exploratory, laboratory, and field studies, in which they investigate and improve trace data and subsequently develop and test personalized scaffolds based on individual learning processes. Their joint expertise in the fields of self-regulated learning and learning analytics provide superior opportunities to develop and test more powerful adaptive educational technologies.
  Applicants and research partners are: Prof. Dr. Maria Bannert, Technische Universtät München (TUM), TUM School of Education, Susanne Klatten Endowed Chair for Teaching and Learning with Digital Media, Germany; Dr. Inge Molenaar, Radboud University Nijmegen, Behavioral Science Institute, Learning and Plasticity group, Department of Pedagogics and Educational Sciences, The Netherlands; Prof. Dragan Gasevic, University of Edinburgh, Moray House School of Education and School of Informatics, United Kingdom; Prof. Johanna Moore, University of Edinburgh, Human Communication Research Centre, United Kingdom 
  Contact persons: Prof. Dr. Maria Bannert, Lyn Lim, M.Ed.

  Information about the FLoRA Project can be found here