Linda Lin is a researcher at AIR with experience in designing and conducting education research and evaluation studies. Dr. Lin specializes in experimental and quasi-experimental study design and quantitative methodology, with a particular interest in casual inference methods, multilevel modeling and data mining. She also has extensive experience in developing ...
The Plan, Do, Study, Act Process is central to the improvement of instructional routines. Watch one of the Better Math Teaching Network members in real time and in a real classroom setting introduce the Plan, Do, Study, Act, or PDSA, process.
Roddy Theobald is a managing researcher in the Center for Analysis of Longitudinal Data in Education Research (CALDER) at AIR. His primary responsibilities include overseeing eight externally-funded research projects related to the teacher labor market and its implications for student outcomes. He has extensive experience using large administrative datasets to ...
Jill Bowdon is a principal researcher at AIR. Dr. Bowdon has extensive training in statistical methods appropriate for making causal inferences, including experimental design and quasi-experimental methods. Altogether, she has 10 years of experience performing education research. Dr. Bowdon is a lead analyst for the Regional Educational Laboratory (REL) Midwest ...
Michael S. Garet is a vice president and institute fellow at AIR. His areas of specialization include teacher development and methodological issues in evaluating the impacts of educational interventions. He is currently co-leading two projects for the Institute of Education Sciences: a study of the impact of multi-tiered systems of ...
Chris Magyar is a senior TA consultant with over 35 years of business, workforce development and information technology experience. Magyar serves as a project director for the Department of Labor-funded Industry Intermediary project working in partnership with CompTIA’s Apprenticeships for Tech initiative to expand and accelerate the growth of information ...
The study uses nationally representative data to investigate how high school STEM motivation, STEM course taking, STEM achievement and social networks are associated with the decision of students who go on to enroll in 4-year colleges to choose a STEM major or not. The study findings highlight the important role ...
Using 2015 grade 8 NAEP science data, this study aims to understand the role that science motivation plays in middle school science achievement using a hierarchical linear modeling approach. The results indicated that both science self-efficacy and science interest as measures of science motivation were significant positive predictors of science ...