Massive open online courses (MOOCs) offer tremendous opportunities for education research: huge sample sizes and the ability to study student behavior in a self-contained environment of instructional and assessment activities. This postdoc will employ and develop the RELATE group’s expertise in educational data mining and advanced psychometrics to understand how student actions influence their learning and to improve online resources. They will analyze data from both physics and electrical engineering courses to study both short- and long-term learning. A particular interest is mining the data to provide point of need help to future students. In addition, we are implementing our new Modeling Applied to Problem Solving pedagogy in an online course aimed at physics teachers and will be evaluating course elements designed to teach critical skills and 21st century outcomes. This course is also blended with a successful on-campus course. See http://relate.mit.edu for related work.
Minimum Requirements:
PhD/EdD in physics, education research, statistics, computer science, etc…
Quantitative data analysis experience
Desired Skills:
R, Python, MySQL, XML
Experience with large data sets
Familiarity with relevant education literature
Teaching experience
Interest in online education
All former postdocs have continued to positions in academia or education companies. Inquiries and applications (CV, cover letter, and three references) should be sent to RelateMIT@gmail.com (please include “postdoc application” in subject line). Review of applications will begin immediately; starting date flexible.
MIT is an Affirmative Action/Equal Opportunity employer. For more information check http://web.mit.edu/
