Carnegie Mellon University's Human-Computer Interaction Institute (HCII) is seeking a Research Assistant to support projects focused on Generative AI in education. The role involves developing and evaluating AI-based systems for multimodal feedback and participatory measurement of Generative AI, aiming to harmonize technology with human capabilities and improve learning environments.
Requirements
- Strong programming skills in Python and/or R, with experience in web technologies (JavaScript, HTML, CSS).
- Basic knowledge of AI in education and/or learning sciences.
- Prior experience with both front-end and back-end development.
- Familiarity with AI tools and APIs (e.g., OpenAI, Hugging Face, or similar).
Responsibilities
- Conduct literature reviews on Generative AI in education, learning sciences, and multimodal feedback.
- Analyze qualitative and quantitative data from user studies.
- Assist in the design, recruitment, and coordination of human-subject experiments under IRB protocols.
- Contribute to both front-end and back-end development for MuFIN systems (SlideItRight and VTutor) and PartiMeas systems (PartiMeas Toolkit), ensuring smooth integration of LLM-based features and interactive UI/UX components.
- Collaborate with the team to refine feedback generation algorithms and system interfaces for MuFIN, as well as interfaces for stakeholder participation in PartiMeas.
- Conduct software testing and debugging to ensure performance and scalability.
Other
- Bachelor’s degree or higher in Computer Science, Human-Computer Interaction, Learning Sciences, or a related field.
- Excellent communication and teamwork skills.
- Demonstrated ability to manage multiple tasks and meet deadlines.
- A combination of education and proven experience from which comparable knowledge is demonstrated may be considered.
- Flexibility, excellence, and passion are vital qualities.
- Collaboration and cultural sensitivity are valued competencies.
- Able to effectively interact with a varied population of internal and external partners at a high level of integrity.
