Research Associate, Education and Research Focus - School of Computer Science - HCII

Carnegie Mellon University•Pittsburgh, PA

19h•Onsite

About The Position

Carnegie Mellon University is seeking an enthusiastic individual with a keen interest in exploring the role of technology in educational settings for the PLUS - Personalized Learning Squared project. This project, run by the Human-Computer Interaction Institute, aims to double the rate of math learning in middle school students, particularly those historically underserved. The project operates in collaboration with Carnegie Learning and Stanford University and is led by Principal Investigator Prof. Ken Koedinger. The program features a hybrid tutoring platform that combines human and AI tutoring to deliver personalized learning. The team consists of diverse individuals with backgrounds ranging from experienced educators, researchers, and engineers. The work intersects with Artificial Intelligence, Learning Sciences, and Human-Computer Interaction. The Research Associate will play a crucial role in advancing research by contributing to the improvement of tools designed to enhance the effectiveness of tutors in aiding students during their learning sessions. This position offers the unique opportunity to collaborate with and learn from experts at CMU and Stanford. The ideal candidate will be naturally inquisitive and capable of independently identifying and pursuing research questions, with an emphasis on deriving meaningful insights and contributions.

Requirements

Bachelor’s Degree required.
Previous research lab experience required.
Academic and educational research experience, preferably within K-12 public education.
Instructional design and/or learning engineering knowledge.
Experience with content creation, such as creating curriculum and instructional materials.
Effective communication skills.
Successful completion of a pre-employment background check.

Nice To Haves

Experience with education data analysis or learning analytics is a plus.
Some prior publication experience is a plus.
A combination of education and proven experience from which comparable knowledge is demonstrated may be considered.

Responsibilities

Tagging and coding of qualitative data, such as user response data.
Applying mixed methods analysis of quantitative and qualitative data.
Conducting quantitative analysis using R/Python or similar statistical packages.
Creating instructional lessons and materials that are driven by research.
Conducting literature reviews of education research.