Power of Data-Driven Teaching in Schools

Contents

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.