Postdoctoral Associate, Computer Science Teacher Education

07/10/2019 ∙ 0 APPLY VIEW ALL JOBS

Job Number: 17679

Functional Area: Research - Other

Department: Comparative Media Studies/Writing

School Area: Humanities, Arts, & Social Sciences

Employment Type: Full-Time Temporary

Employment Category: Exempt

Visa Sponsorship Available: Yes

Working at MIT offers opportunities, an environment, a culture - and benefits - that just aren't found together anywhere else. If you're curious, motivated, want to be part of a unique community, and help shape the future - then take a look at this opportunity.

POSTDOCTORAL ASSOCIATE, COMPUTER SCIENCE TEACHER EDUCATIONComparative Media Studies/Writing (CMS/W)-Teaching Systems Lab, to conduct research into computer science teacher education in K-12 school districts and colleges of education. The Teaching Systems Lab develops teacher practice spaces--games and simulations that let teachers rehearse for and reflect on important decisions in teaching. Will help lead two research-practice partnerships--one with Massachusetts' school districts and one with colleges of education--to broaden participation in computing education. Will use design-based research methods to co-design, implement, evaluate, and iteratively improve teacher practice spaces--embedded in professional learning experiences--that focus on equity teaching practices in computer science teaching. Responsibilities will include developing and maintaining research-practice partnerships, developing innovative professional learning resources, conducting professional development with CS teacher educators and CS teachers in diverse settings, collecting and analyzing data, and writing publications for high-impact scholarly and practitioner venues.

Job Requirements

REQUIRED: earned doctoral degree in learning science, computer science, teacher education, or related field; publication record directed at both scholarly and practitioner audiences; experience with design-based methods; familiarity with qualitative, quantitative, or mixed methods (including ethnography, learning analytics, evaluation, assessment, etc.); familiarity with artificial intelligence methods, ethics, and critiques; ability to work effectively with and contribute to cross functional groups; excellent interpersonal and communication skills; demonstrated experience with and commitment to promoting equity and diversity. Job #17679

Some travel to field sites in the U.S. will be required. 

This is a temporary, one-year position. 


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