The researcher will work with an interdisciplinary team in the Learning Sciences and Technologies program that conducts research in K12 STEM education.
The candidate will utilize a variety of quantitative methods (ie. ML, clustering, multilevel modeling) to analyze data and develop data models to produce algorithms that identify student behaviors and mathematical strategies that could also predict learning and engagement.
Successful candidates will have expertise in the use of complex data analytic techniques that leverage rich data to understand phenomena related to learning, engagement, and performance.
Preference will be given for candidates that have conducted scholarly work involving empirical and theoretical studies of the cognitive and affective processes and mechanisms that underlie technology-enhanced learning.
Requirements
The candidate should have a Masters in Learning Sciences or a closely related field.
A proven publication track record and relevant research experience in some combination of math cognition, machine learning, educational data mining, learning analytics, classification algorithms, behavior detectors, or artificial intelligence is preferred.
Candidates must also be able to communicate effectively (both verbally and written) and learn from and collaborate with researchers from a variety of interdisciplinary areas (math education, cognitive psychology, statistics)
Hourly rate is $25/hr. Part time 20 hours per week until August 14th. Review of materials will begin immediately and will continue until the position is filled.
FLSA STATUS
United States of America (Non-Exempt)
Benefits
Vision insurance
Additional Information
JOB TITLE
Temporary Research Assistant
LOCATION
Worcester
DEPARTMENT NAME
Social Science & Policy Studies - JM
DIVISION NAME
Worcester Polytechnic Institute - WPI
JOB DESCRIPTION SUMMARY
The candidate will perform basic and applied research in math education and support the processing and analysis of educational data that is produced as students engage with math problems using a variety of technology tools (eye tracking, executive function tasks, math technology). The researcher would join an interdisciplinary team to work on several NSF funded projects examining the intersections of math and algebra problem solving, math cognition, perceptual learning, student errors and strategy use, feedback, executive function and attention, and learning technologies. These projects will provide a lot of opportunities to examine student math performance and achievement outcomes as well as action and problem log-level data analysis of student interactions within technologies.
The position is funded for one summer.
JOB DESCRIPTION