PhD-Projects
The doctoral candidates from research professorship Learning Sciences in Higher Education qualify within the CATALPA Graduate School.
-
Supervisor: Prof. Dr. Marcus Matthäus Specht
Co-Supervisor: Dr. Florence Lehnert
Title From Goal Setting to Adaptation: Supporting Self-Regulated Learning Processes in Programming with Pedagogical Conversational Agents
Abstract This doctoral project investigates how pedagogical conversational agents (PCAs) can foster self-regulated learning (SRL) in higher education. AI tools often boost short-term performance but may also lead learners to offload critical metacognitive processes. Addressing this tension, this doctoral project examines how PCAs can be designed to support learners by leveraging the full SRL cycle - forethought, performance, and reflection - rather than narrowly facilitating task completion. The research proceeds in three phases: (1) a systematic literature review that derives design principles to support full-cycle SRL, (2) a formative phase consisting of prototyping and lab studies in introductory R programming, during which phase-aligned SRL indicators are identified from multimodal interaction data and (3 a summative interventional deployment in a semester-long undergraduate course to model within-student SRL. The expected contribution is an integrated design and measurement framework that advances PCA development and LA-informed understanding of SRL in higher education.
-
Titel: AI-Supported Regulation Processes in Collaborative Writing
Supervisor: Prof. Dr. Marcus Specht
Co-Supervisor: PD Dr. Laura Froehlich, Dr. Niels Seidel
The doctoral project „AI-Supported Regulation Processes in Collaborative Writing“ explores how artificial intelligence can strengthen collaboration in higher education. Grounded in CSCL and Socially Shared Regulation of Learning (SSRL), it examines how student groups coordinate, monitor, and adapt their work in digital writing tasks. Based on trace data, a literature review and interview regulatory challenges are identified to develop pedagogical conversational agent (PCA) prototypes that scaffold group-level processes. A randomized controlled trial evaluates their effects on shared regulation, engagement, and collaboration quality.
-
Titel: Learning design informed by data-driven insights and its impact on educational outcomes
Supervisor: Prof. Dr. Marcus Specht
Co- Supervisor: Prof. Dr. Ioana Jivet, Dr. Maryam Alqassab, Prof. Dr. Hendrik Drachsler
Educators, learners, and tools together have the potential to improve Learning Design. However, the tools available to educators often lack insights from both educators and learners, frequently focusing more on one than the other. This PhD project aims to conceptualize, develop, implement, and evaluate an educational-theory-based and user-centered Learning Design tool for stakeholders involved in Learning Design. The goal is to improve learners’ performance by integrating teaching and learning analytics along with artificial intelligence into Learning Design, and to support the development of iterative, systematic processes for Learning Design, evaluation, and refinement.
