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Module 1:

Understanding Data-Driven Teaching in Schools:

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• Learning Objectives:

  • Define data-driven teaching and its significance.

  • Understand the types of educational data available (academic, behavioural, attendance).

• Topics:

  • The role of data in modern education.

  • Overview of critical data sources in schools.

• Activities:

  • Reflection: Assess your school’s current use of data.

  • Case Study: How a school improved outcomes using data.

Module 2: Collecting and Organizing Data

• Learning Objectives:

  • Learn methods to collect meaningful and accurate data.

  • Organize data effectively for analysis and application.

• Topics:

  • Data collection tools and techniques (surveys, LMS, assessments).

  • We are ensuring ethical data collection practices.

• Activities:

  • Hands-on: Using data management tools (Google Sheets, Excel, or SIS).

  • Discussion: Identifying data gaps in your institution.

Module 3: Analyzing Data for Insights

• Learning Objectives:

  • Develop skills to interpret and analyze educational data.

  • Use data visualization tools to identify trends and patterns.

• Topics:

  • Key metrics for student performance and teacher effectiveness.

  • Introduction to data visualization software.

• Activities:

  • Workshop: Create a dashboard to track student performance.

  • Group Exercise: Interpret data to suggest actionable insights.

Module 4: Applying Data to Instruction

• Learning Objectives:

  • Learn to use data for personalized instruction and intervention.

  • Understand strategies to differentiate teaching based on data.

• Topics:

  • Designing data-informed lesson plans.

  • Using formative assessments to guide teaching.

• Activities:

  • Role-Play: Customizing a lesson for diverse learners using data.

  • Case Study: Successful intervention strategies.

Module 5: Driving Equity Through Data

• Learning Objectives:

  • Use data to identify and address inequities in education.

  • Develop strategies for inclusive teaching.

• Topics:

  • Recognizing patterns of inequity using data.

  • Implementing targeted interventions for underserved groups.

• Activities:

  • Discussion: Addressing unconscious bias with data.

  • Action Plan: Develop an equity-focused strategy for your school.

Module 6: Building a Data-Driven Culture

• Learning Objectives:

  • Foster a school-wide commitment to data-informed decision-making.

  • Train staff and stakeholders to use data effectively.

• Topics:

  • Leadership’s role in promoting data use.

  • Overcoming resistance to data-driven practices.

• Activities:

  • Simulation: Leading a data-driven staff meeting.

  • Workshop: Designing a professional development session on data use.

Module 7: Tools and Technology for Data-Driven Teaching

• Learning Objectives:

  • Explore technology tools that support data collection and analysis.

  • Leverage AI and EdTech for predictive insights.

• Topics:

  • Overview of Learning Management Systems (LMS).

  • Introduction to AI in education analytics.

• Activities:

  • Demo: Exploring EdTech tools like Power BI, Tableau, and AI platforms.

  • Lab: Automating data reporting.