(734) 763-1462
Applications: Astronomy and Cosmology, Behavioral Science, Education, Human Subjects Trials and Intervention Studies, Learning Analytics, Physics Methodologies: Algorithms, Causal Inference, Classification, Data Collection Design, Data Munging, Data Visualization, Decision Science, Human-Computer Interaction, Missing Data and Imputation, Natural Language Processing, Statistical Inference Relevant Projects:

NSF, DOE, EDUCAUSE, HHMI

Sloan Foundation

REBUILD STEM Education Initiative (PI)

Digital Innovation Greenhouse (PI)

ECoach Project (PI)

Dark Energy Survey (Builder)

Sloan/CIC LARA Project (Co-I)

Connections:

CIC Learning and Research Analytics Project: Organizer, UM Representative for AAU STEM Initiative, Chair of UM Learning Analytics Task Force

Timothy McKay

Professor, Physics, College of Literature, Science, and the Arts

Affiliation(s):

Astronomy, College of Literature, Science, and the Arts
Education, School of Education

I am a data scientist, with extensive and various experience drawing inference from large data sets. In education research, I work to understand and improve postsecondary student outcomes using the rich, extensive, and complex digital data produced in the course of educating students in the 21st century. In 2011, we launched the E2Coach computer tailored support system, and in 2014, we began the REBUILD project, a college-wide effort to increase the use of evidence-based methods in introductory STEM courses. In 2015, we launched the Digital Innovation Greenhouse, an education technology accelerator within the UM Office of Digital Education and Innovation. In astrophysics, my main research tools have been the Sloan Digital Sky Survey, the Dark Energy Survey, and the simulations which support them both. We use these tools to probe the growth and nature of cosmic structure as well as the expansion history of the Universe, especially through studies of galaxy clusters. I have also studied astrophysical transients as part of the Robotic Optical Transient Search Experiment.

This image, drawn from a network analysis of 127,653,500 connections among 57,752 students, shows the relative degrees of connection for students in the 19 schools and colleges which constitute the University of Michigan. It provides a 30,000 foot overview of the connection and isolation of various groups of students at Michigan. (Drawn from the senior thesis work of UM Computer Science major Kar Epker)

This image, drawn from a network analysis of 127,653,500 connections among 57,752 students, shows the relative degrees of connection for students in the 19 schools and colleges which constitute the University of Michigan. It provides a 30,000 foot overview of the connection and isolation of various groups of students at Michigan. (Drawn from the senior thesis work of UM Computer Science major Kar Epker)