MIT Teaching Systems Lab
People & Projects Working at MIT TSL with
Panel: Panel 3
Panel 3: If teachers matter most, what about teachers matters?: Exploring the role of non-instructional predictors of math teacher instructional outcomes
To the practitioner or the parent, it may not come as a surprise that decades of rigorous research in economics point to teacher quality as the single largest predictor of student achievement gains above other school characteristics, particularly for students of color. However, in breaking down “teacher quality” there are some outstanding puzzles. For instance, years of preparation, teacher degrees and advanced course work are relatively weak predictors of math teacher effectiveness. The field stands to learn much about what non-instructional factors predict math teacher effectiveness; little is known about the relative importance of teacher beliefs about their own abilities, teacher expectations for students, teacher agency, teacher satisfaction, and retention, etc. This panel focuses on shaping a research agenda that would help the field better understand malleable, non-instructional predictors of math teacher learning. Panelists will focus on reviewing what is known, unknown, how to learn more, and implications for targeting new kinds of professional learning.
To the practitioner or the parent, it may not come as a surprise that decades of rigorous research in economics point to teacher quality as the single largest predictor of student achievement gains above other school characteristics, particularly for students of color. However, in breaking down “teacher quality” there are some outstanding puzzles. For instance, years of preparation, teacher degrees and advanced course work are relatively weak predictors of math teacher effectiveness. The field stands to learn much about what non-instructional factors predict math teacher effectiveness; little is known about the relative importance of teacher beliefs about their own abilities, teacher expectations for students, teacher agency, teacher satisfaction, and retention, etc. This panel focuses on shaping a research agenda that would help the field better understand malleable, non-instructional predictors of math teacher learning. Panelists will focus on reviewing what is known, unknown, how to learn more, and implications for targeting new kinds of professional learning.
Half day workshops at the ICLS London 2018 for all designers and researchers interested in Playful Assessment!
Collaboration will support Pre-K-12 teachers in using emerging digital learning tools.
Spencer Foundation launches $2 million effort to create first-of-their-kind measures.
Patrick Riccards, Chief Communications and Strategy Officer for the Woodrow Wilson National Fellowship Foundation, discusses competency-based education in Real Clear Education.
New program provides funding for three projects working to improve STEM education.
Cutting-edge model capitalizes on blended learning to take personalization further.
Teaching Systems Lab Executive Director Justin Reich awarded a grant from Google For teacher-facing intervention research
This year’s recipients tackle a range of innovations in education from using the Unhangout Platform to support teachers’ professional development to using artificial intelligence to make students’ mathematical problem solving visible to the teachers.
Thanks to a National Science Foundation grant, TSL will collaborate with Maker Ed to improve school-based assessment practices in maker-centered education.
MIT’s Teaching Systems Lab (TSL), with support from the Woodrow Wilson National Fellowship Foundation, is excited to announce the recipients for the 2018-2019 Teaching and Learning Innovation Grant (TLIG).
Half day workshops at the ICLS London 2018 for all designers and researchers interested in Playful Assessment!
The mission is to create and share high quality resources to facilitate digital and non-digital learning for K-12 and lifelong learners. By providing science, technology, engineering, arts, and mathematics (STEAM) based instructional materials and an open forum for users to share insights, we aim to inspire a diverse global community of educators, students, and parents to find innovative solutions to the challenges of learning at a distance
Research and Insight on K-12 Teacher Learning from the MIT Teaching Systems Lab
To more deeply understand the practice and professional experiences of educators during the 2020 extended school closures, we interviewed 40 teachers from across the country in public, charter, and private schools, at different grade levels, and in different subject areas.
In May 2020, we conducted four online design charrettes with school and district leaders, teachers, students, parents, and other stakeholders to translate design-based practices for leading school change into an online context.
We analyze the state education agency policy guidance concerning remote learning published by all 50 U.S. states by the end of March 2020.
Justin Reich is the Co-Principal Investigator on a project that will develop, pilot, and refine a set of coordinated and complementary activities that teacher education programs can use in both online and face-to-face settings.