Power of Data-Driven Teaching in Schools

Module 1:

Understanding Data-Driven Teaching in Schools:

• 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.