Online learning environments, be it online (e.g. MOOCs) or on campus (e.g. blended courses), offer tremendous opportunities for education research: large sample sizes ensure sensitive statistics, detailed clickstream data provides high resolution on student behavior and learning, and a matured platform (edX) allow for easy implementation of randomized experiments. The major research responsibility of the postdoc will be to design experiments, author experimental resources, then collect and analyze data from their online use to find out the type resource and student learning behavior that generates deep learning and expertise – particularly in physics problem solving. Our long term goal is to understand which resources and what learning habits improve student learning of specific skills and overall expertise. This postdoc will benefit from the RELATE group’s expertise in educational data mining, advanced psychometrics including multi-dimensional item response theory, and experience in designing online experiments. (see http://relate.mit.edu)
Desirable Skills:
Designing and conducting educational experiments
Knowledge of education research literature, especially in Physics Education
Familiarity with HTML/XML/CSS
Basic Python/R/javascript coding or the ability to quickly pick up new programming languages.
Statistics/data analysis skills.
A Ph.D or Ed.D in physics/science education, instructional design, or cognitive science etc. is required. Applicant must be comfortable working both alone and with others. All former postdocs obtained positions in academia or education companies. Inquiries and applications (CV, cover letter, and at least three references) should be sent to relateMIT@gmail.com (please include “postdoc application” in subject line). Review of applications will begin immediately; starting date summer 2016. MIT is an Affirmative Action/Equal Opportunity employer. For more information check http://web.mit.edu/physics/about/employment.html and http://relate.mit.edu/jobs.html .
