Data-Rich, Information-Poor: Data Practices for Equitable, Student-Centered Learning

Participate and share : Poster

Thursday, December 3, 12:00–1:00 pm PST (Pacific Standard Time)

Stephen Pham
Schools are notoriously data-rich but information-poor. Though it can be unmanageable for educators in the age of COVID, data-use is crucial for shedding light on inequities. In this session, leaders will explore classroom and school-wide practices to enable equity-driven data-use and learning design.

Audience:	Coaches, Curriculum/district specialists, Principals/head teachers
Skill level:	Intermediate
Attendee devices:	Devices not needed
Topic:	Assessment/evaluations/use of data
Grade level:	PK-12
ISTE Standards:	For Coaches: Teaching, Learning and Assessments Coach teachers in and model effective use of technology tools and resources to systematically collect and analyze student achievement data, interpret results, and communicate findings to improve instructional practice and maximize student learning. Coach teachers in and model design and implementation of technology-enhanced learning experiences using a variety of research-based, learner-centered instructional strategies and assessment tools to address the diverse needs and interests of all students. Professional Development and Program Evaluation Evaluate results of professional learning programs to determine the effectiveness on deepening teacher content knowledge, improving teacher pedagogical skills and/or increasing student learning.

Proposal summary

Purpose & objective

Strategic data are required to design for equitable learning, but the deluge of data is challenging to navigate and competing priorities and tools in the age of COVID make data-use inaccessible. This session aims to share concrete practices for using data to support equitable, student-centered learning in any model, including distance learning. Attendees will leave with strategies for using data to understand gaps and resources for taking it further on their own.

The session will be successful if participants build their toolkit and gain confidence in utilizing and organizing data to ensure equity-driven data practices.

Supporting research

Council of the Great City Schools, 2012. CHARTING SUCCESS: Data Use and Student Achievement in Urban Schools. https://files.eric.ed.gov/fulltext/ED536748.pdf.

Bill & Melinda Gates Foundation, June 2015. Teachers Know Best: Making Data Work For Teachers and Students. http://k12education.gatesfoundation.org/download/?Num=2335&filename=TeachersKnowBest-MakingDataWork.compressed.pdf.

Washington State School Directors' Association. Data dashboards for school directors: Using data for accountability and student achievement. https://files.eric.ed.gov/fulltext/ED521609.pdf.

More [+]

Presenters

Stephen Pham, The Learning Accelerator

Stephen Pham is Director, Organizational Learning at The Learning Accelerator (TLA). An experienced educator and systems leader, he brings expertise in blended and personalized learning, school design, adult learning, and data use in schools. At TLA, Stephen leads strategic projects focused on educator professional learning, data use in schools, and diversity, equity, and inclusion. Before, Stephen managed school model innovation and personalized learning nationally at Rocketship Public Schools, where he also started as a fifth-grade STEM teacher and Teach For America corps member. Stephen earned a B.S. in biophysics from UCLA and is based out of Seattle.

Data-Rich, Information-Poor: Data Practices for Equitable, Student-Centered Learning

Proposal summary

Purpose & objective

Supporting research

Presenters

People also viewed