Temporary Research Assistant

WPI • Worcester, MA

1d • Onsite

About The Position

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.

Requirements

• Masters in Learning Sciences or a closely related field.
• Ability to communicate effectively (both verbally and written).
• Ability to learn from and collaborate with researchers from a variety of interdisciplinary areas (math education, cognitive psychology, statistics).

Nice To Haves

• Proven publication track record.
• Relevant research experience in some combination of math cognition, machine learning, educational data mining, learning analytics, classification algorithms, behavior detectors, or artificial intelligence.
• Scholarly work involving empirical and theoretical studies of the cognitive and affective processes and mechanisms that underlie technology-enhanced learning.

Responsibilities

• Perform basic and applied research in math education.
• Support the processing and analysis of educational data.
• Utilize a variety of quantitative methods (e.g., ML, clustering, multilevel modeling) to analyze data.
• Develop data models to produce algorithms that identify student behaviors and mathematical strategies that could also predict learning and engagement.

What This Job Offers

• Job Type: Part-time
• Career Level: Mid Level