Integrating mixed reality (MR) with knowledge graphs offers a transformative approach in an era where education is becoming increasingly personalized and interactive. Visualizing knowledge through graphs and providing an immersive experience allows learners to shape their educational spaces and engage with information in new, dynamic ways.
Thesis Type |
|
Status |
Cancelled |
Supervisor(s) |
Stefan Decker |
Advisor(s) |
Anika Martin |
Contact |
anika.martin@fit.fraunhofer.de |
This thesis focuses on designing and implementing a Mixed Reality Tour Guide for Knowledge Graphs, utilizing both the Virtual Agent Framework and the Social Bot Framework. It involves creating a virtual environment where knowledge is displayed and interacted with, enhancing engagement and retention. The goal is to develop a system that supports interactive knowledge acquisition, allowing users to navigate through tours and engage with individual knowledge elements. This work represents a novel intersection of MR, AI, and educational technology, paving the way for innovative learning strategies.
Goals & Objectives
- Develop an MR-based tour guide for visually representing knowledge maps.
- Enable interactive navigation and engagement with knowledge elements.
- Evaluate the effectiveness of the system in enhancing learning experiences.
Possible Research Questions
- How can MR be integrated with knowledge graphs to provide an engaging learning experience?
- What are the optimal interaction patterns for navigating through knowledge graphs in MR?
- How does the MR-based system impact knowledge acquisition and retention?
Methodology & Approach
- Review research on MR in education, knowledge graph visualization, and intelligent virtual agents.
- Exploration of existing technologies and frameworks in the context of interactive learning.
- Comparison of different MR applications in educational settings.
- Identification of strengths and weaknesses in existing solutions.
- Qualitative and quantitative methods for understanding user interaction.
- Development of MR prototypes
- User testing and iterative design to enhance usability.
Data Collection Methods and Sources
- Surveys, interviews, and observation for user feedback.
- Collection of interaction data within the MR environment.
Tools, Models, or Frameworks to be Employed
- AI and ML algorithms for intelligent agent interaction.
- Utilization of existing MR tools and the integration of the Virtual Agent and Social Bot Framework (including OpenAI/LangChain).
Opportunities & Benefits
- Skill development in MR, AI, and educational technology.
- Contribution to an emerging field with significant potential.
- Opportunities to publish your work in a follow-up research paper (journal/conference), and continue your work as a student worker.
- Knowledge of Mixed Reality (MR) Technologies: Understanding MR tools and platforms, including hardware and software aspects.
- Programming Skills: Proficiency in programming languages such as Python, C#, Java, or others that may be used in developing the MR environment.
- Understanding of Knowledge Graphs: Background in representing knowledge using graphs, including relevant data structures and visualization techniques.
Nice to have:
- Experience with Virtual Agent and Social Bot Frameworks: Ability to work with specific frameworks for developing virtual agents, guided by the project’s requirements.