STEM Education Topics
Collecting high quality data is a critical component of STEM research and evaluations, and it is central to stand-alone national surveys used to provide up-to-date statistics to enable researchers and policymakers to monitor the size and characteristics of the scientific workforce.
Data collections involve identifying and sampling the appropriate populations, developing instruments, and collecting data through alternative and innovative methods. Data management involves documenting and maintaining information about those in the scientific workforce for the use of researchers and policymakers.
Evidence & Insights
Publication
Measuring Ambitious and Inclusive Mathematics Instruction
This paper introduces and explores the validity and reliability of a classroom observation tool that the team developed to measure ambitious (cognitively demanding and standards-based) and inclusive (culturally responsive, linguistically responsive, and equitable) mathematics teaching.
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