Digital Assistants for Individualised Learning Systems (DAISy)

• Adaptive learning platforms: Adaptive learning platforms provide immediate and personalized support of technology-enhanced learning without intervention from a human instructor. They also cater for the training needs of an increasingly diverse workforce where other training methods often fail. Such platforms provide individualized learning by, for instance, aligning the specific content learners are given with their prior knowledge, and the amount of learner control may co-vary with prior knowledge. When learning content is largely predetermined, instructors can scaffold learning processes by using data on observable learning behaviors, which is often referred to as adaptive tutoring.
• Real-time learning analytics: Such adaptive tutoring is one of the two main lines of our research. We develop digital assistance tools to support self-directed e-learning, by defining a content-specific prototypical learning path through the content. This path includes, for example, expected study times for each content section. The prototypical path is generated from offline (including prior knowledge level) and on-line (such as responses to assessment questions) data. If a learner deviates from the prototypical learning process, this triggers specific prompts to identify their learning support needs as they arise.
• Self-directed learning: Our studies show that stimulating self-directed learning can increase learning efficiency and reduce the time required for learning. It is possible to promote such learning by identifying individual support needs in real-time data and covering them through self-directed immersion opportunities for specific learning content. At the same time, learners report that they experience learning as less stressful.
• Digital assistant: We also look at the role of instructional design in e-learning. Our guiding assumption is that beyond learners’ self-regulation skills, self-directed learning depends on certain features of the instructional design underlying e-learning offers. That design can support self-direction — or make it more difficult. In response to this, we developed a digital assistant. Together with learning authors and/or instructors, the assistance tool analyzes the instructional design of a given learning unit according to the CALL model (Constructive alignment of learning activities) of action-oriented learning. The tool makes specific suggestions to authors on how they can make a given learning unit even more competence-oriented by aligning intended learning outcomes, learning content, and learning activities. Building on the competency models in a specific domain, the tool helps establish and integrate the instructional core of effective and efficient courses into e-learning offerings.
• Design guidelines: Considering that we work with authors in a broad range of domains, we aim to develop guidelines for comprehensive instructional design that supports learning authors in virtually any domain. The authoring tool has graded functionality, ranging from a check-list function (tool checks the instructional design of an e-learning for CALL compatibility) to dialogue-based template creation. For example, the tool creates the basic framework of a learning unit from a dialogue with the author and suggests design guidelines for the content that the author adds to that basic framework.

• Through our individualized learning research, we see increases in the effectiveness and efficiency of learning, and empowering learners to assume more responsibility for their learning progress. In the longer run, the instructional design principles we elaborate may enable the creation of a comprehensive portfolio of learning and training formats beyond e-learning that provide a sustainable basis for competence-building training.
• Prof. Christian Stamov Roßnagel was appointed as an advisory board member at the Institut für Betriebliche Bildung. In collaboration with major companies, the institute develops evidence-based standards for effective training.
• Prof. Stamov Roßnagel was commissioned by AOK Gesundheitskasse to consult personnel managers on their organization-wide learning-platform relaunch.
• He was also invited as the keynote speaker at the “Future of Competence Development” workshop funded by the Federal Ministry of Labour and Social Affairs.

Prof. Stamov Roßnagel’s research group includes a postdoctoral fellow and a PhD student. They contributed to our LeADS research which was funded through grants from the Federal Ministry of Labour and Social Affairs and the Jacobs Foundation.

• Langen, I., Stamov Roßnagel, C. (2023). East is East: Socratic classroom communication is linked to higher stress in students from Confucian heritage cultures. Heliyon, 9 (5), 
• Bittner, J.V., Stamov Roßnagel, C. & Staudinger, U.M. (2021). Educational self-regulation competence: toward a lifespan-based concept and assessment strategy. International Journal of Educational and Vocational Guidance, 22, 307–325 (2022). 
• Stamov Roßnagel, C., Lo Baido, K., & Fitzallen, N. (2021). Revisiting the relationship between constructive alignment and learning approaches: A perceived alignment perspective. PLOS One 16 (8), e0253949. 
• Stamov Roßnagel, C., Fitzallen, N., & Lo Baido, K. (2020). Constructive alignment and the learning experience: relationships with student motivation and perceived learning demands. Higher Education Research & Development 40 (4), 838-851. 
• Rinn, R., Stamov Roßnagel, C., & Navin Lal, T. (2019). Development