This course introduces educators, school administrators, and education students to the practical use of artificial intelligence and data analytics to support data-informed decision-making in schools.

Participants explore how AI and machine learning analyze common educational data such as attendance records, grades, and assessment results. Through guided discussions, demonstrations of AI-supported tools, and analysis of real or simulated school scenarios, participants learn how AI can help identify learning gaps and indicators of at-risk students.

The course culminates in the design of a basic AI-integrated data analytics tool or dashboard and the development of an ethical, inclusive, and context-appropriate intervention plan tailored to participants’ school contexts in the Philippines.

• Describe the role of AI and machine learning in analyzing education data (attendance, grades, diagnostics) and how it complements traditional teaching. 

• Apply AI tools (e.g. predictive analytics, data visualization) to identify learning gaps and at-risk students using real or simulated school data.

• Develop a data-driven intervention plan using AI insights to improve student outcomes. 

• Evaluate the ethical, privacy and equity implications of AI in their local context, ensuring interventions are inclusive.

Educators
School administrators
Education students