Data-driven Learning

Effective use of data about science learning guides instruction and student ownership of learning. Both teachers and students rely on the interpretation and analysis of data to gain the most learning from instruction. The responsibility for learning rests on both of these parties. The sessions in this strand will emphasize the importance of gathering, interpreting, communicating, and acting on data to guide instruction and enhance conceptual learning.
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Goals
To provide workshops and presentations focusing on one or more of the following:
• Setting clear expectations for student learning.
• Exploring the meaning and uses of formative and summative assessment, knowing when to assess, and how to use the data obtained.
• Providing mechanisms to assist students in monitoring their own learning.
• Selecting appropriate data and assessment tools to measure student learning.
• Through Professional Learning Communities (PLCs) and other venues, collaborating to make meaning from data and address implications for instruction.

Criteria
Proposals will be evaluated on the extent that they:
• Show appropriate applications of data interpretation.
• Feature methods to enhance student reflection on learning.
• Align with one or more strand goals.
• Align with state and national science education standards (NSES and Benchmarks).
• Are based on current and available research and issues in science.
• Involve participants through activities and/or discussion.