Research Associate - School of Computer Science - HCII

Carnegie Mellon University•Pittsburgh, PA

8d•Onsite

About The Position

Carnegie Mellon University's Human-Computer Interaction Institute (HCII) is seeking Research Associates for the summer of 2026 to contribute to a project focused on novel educational technology. This project involves creating mixed-reality smart glasses designed to augment middle-school teachers' awareness of students who may need assistance while they are using AI-based tutoring software. The goal is for teachers to maintain focus on the class while receiving visual cues about each student's progress and struggles. The HCII is a research hub investigating the relationship between computer technology, human activity, and society, aiming to understand and create technology that enhances human capabilities and social environments through interdisciplinary approaches.

Requirements

Bachelor’s degree in human-computer interaction, behavioral sciences, statistics, or a related field.
Coursework in user research, user-centered design, or statistics for behavioral research.
Successful completion of a pre-employment background check.
Ability to work independently.
Experience working in teams.
A combination of education and proven experience from which comparable knowledge is demonstrated may be considered.

Nice To Haves

Experience in interaction design and/or implementation of mixed-reality applications or virtual reality applications.
Unity programming skills and experience.
Experience in statistical analysis highly preferred.
Interest or experience in education technology research.
Affinity for helping K-12 students learn.

Responsibilities

Help with extending the smart glasses with a recommender module.
Analyze data from a classroom study conducted in a school district (31 classes) to test the effect of 'real-time analytics' versus 'historic analytics'.
Address key questions in data analysis regarding how the condition (real-time vs. historic data) affects teacher help and student learning using various data sources, including log data from the tutoring system.