Research
1. Understanding and supporting self-regulated learning with technology
We work with educators and school students to co-design effective learning activities and technologies to understand and support meaningful metacognitive learning (e.g., self-regulated learning, informed choice-making during learning). My research has discovered, among others:
- Students whose choices were supported through self-reflection on their own choice-making behaviors in intelligent tutoring software chose to use an instructional aid less frequently yet more strategically, and learned greater domain knowledge and skills
2. Understanding students' perspective on AI use in classroom
We aim to understand how students (aged 11-18) perceive and feel about the use of AI in German school classrooms, what they prefer, and why. We design AI systems based on the understanding of how students feel and what they prefer. Our research has found, among others:
- Student agency in learning with AI in the classroom is a multi-dimensional concept, consisting of several different aspects of agency in making decisions around data, content, orchestration, and feedback/help, rather than a one-dimensional concept.
3. Cognitive understanding of human learning & instruction to support it
We design effective instructional techniques using adaptive technologies to support students’ cognitive learning in STEM domains, and use participatory and learning analytics approaches to understand how learning happens. My research has discovered, among others:
- A scaffolded self-explanation activity with diagrams in intelligent tutoring software supports effective and efficient algebra learning
- A playful learning experience with drag-and-drop interaction and gamification features in intelligent tutoring software supports engaging and effective algebra learning during remote schooling
4. Researcher-practitioner ecosystem
We envision the future of learning research where we will have an ecosystem that systematically allows researchers and practitioners (e.g., educators, parents, and children) to jointly conduct learning research that informs both learning theories and real-world practice. We reflect on our practice regularly and aim to develop such an ecosystem.
5. Design and evaluation of learning analytics tools
We work with educators and students to co-design and evaluate reflection tools and prompts (e.g., learning analytics dashboards) to support teaching and learning
6. Open Educational Resources (OER)
We work with policy researchers, education researchers, and practitioners to develop policies, strategies, and materials that promote equitable access to education.
