Data-Driven Strategies: Moving All Students Forward on the NJSLA - Adaptive - Math

Participants will review NJSLA Evidence Statements, analyze high-level data to drive instructional decisions, explore tools for organizing data, and engage in interactive activities to learn high-leverage strategies in math, leaving with specific strategies and resources for immediate use.

This workshop equips teachers with actionable strategies to enhance student performance on the NJSLA-A-Math assessments. Participants analyze student performance data, explore how NJSLA-A standards are assessed, and apply targeted instructional strategies to support students, especially those "on the bubble." The session emphasizes evidence-based tools and modeling problem types to drive instructional improvement and close learning gaps. Educators leave with a plan for integrating these insights directly into their upcoming lessons.

Core Needs Addressed

  • Difficulty interpreting and using NJSLA-A data to inform instruction

  • Gaps in student understanding of assessed standards and question types

  • Lack of targeted strategies to support students nearing proficiency

Key Learnings

  1. Data Interpretation for Instructional Impact:
    Teachers learn how to analyze high-level and item-specific NJSLA-A data, identify key evidence statements, and determine prerequisite knowledge to inform their lesson planning.

  2. Deep Understanding of Assessment Types:
    Educators explore and deconstruct the three NJSLA-A item types, gaining insights into conceptual understanding, reasoning, and modeling to better prepare students for each question format.

  3. Strategic, Student-Centered Planning:
    Participants are introduced to practical strategies that reinforce prior knowledge, address misconceptions, and engage students in meaningful math discourse aligned to assessment expectations

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Data-Driven Strategies: Moving All Students Forward on the NJSLA - Adaptive - Math

Participants will review NJSLA Evidence Statements, analyze high-level data to drive instructional decisions, explore tools for organizing data, and engage in interactive activities to learn high-leverage strategies in math, leaving with specific strategies and resources for immediate use.

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Last Updated

Feb 12, 2026 10:51 AM

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Core Needs Addressed

Underlying Needs for Stronger Family-School Partnerships

  • Difficulty interpreting and using NJSLA-A data to inform instruction

  • Gaps in student understanding of assessed standards and question types

  • Lack of targeted strategies to support students nearing proficiency

This workshop helped me better understand the challenges families face and gave me practical strategies to strengthen communication and engagement. I now feel more confident in building supportive partnerships with families to improve student success.

Jen Soloman

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Perfect For You

Pre-Winter Break
Sequenced
Science
Editable
Weekly Cadence
Start of School Year
New Jersey
Research Backed

Key Learning

  1. Data Interpretation for Instructional Impact:
    Teachers learn how to analyze high-level and item-specific NJSLA-A data, identify key evidence statements, and determine prerequisite knowledge to inform their lesson planning.

  2. Deep Understanding of Assessment Types:
    Educators explore and deconstruct the three NJSLA-A item types, gaining insights into conceptual understanding, reasoning, and modeling to better prepare students for each question format.

  3. Strategic, Student-Centered Planning:
    Participants are introduced to practical strategies that reinforce prior knowledge, address misconceptions, and engage students in meaningful math discourse aligned to assessment expectations

Workshop Description

This workshop equips teachers with actionable strategies to enhance student performance on the NJSLA-A-Math assessments. Participants analyze student performance data, explore how NJSLA-A standards are assessed, and apply targeted instructional strategies to support students, especially those "on the bubble." The session emphasizes evidence-based tools and modeling problem types to drive instructional improvement and close learning gaps. Educators leave with a plan for integrating these insights directly into their upcoming lessons.

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