Data literacy for teachers refers broadly to the competence set (knowledge, skills and attitudes) that is required to identify, collect, analyze, interpret and act upon educational data, with the aim of continuously improving the teaching, learning and assessment process. Given MOE’s recent efforts to encourage designing and administering learning opportunities via the Student Learning Space (SLS), it is imperative to equip teachers with the essential conceptual knowledge and competencies required for being data fluent in making full use of the affordances of SLS. This one-day PD will be designed to introduce data literacy fundamentals. Through this course, educators will engage in various activities to gain a deeper understanding of how data-driven decision making can be used to improve teaching and learning.

1. Develop conceptual knowledge about different types of educational data that may be generated via systems like MOE’s SLS.


2. Understand various components of data literacy that are required to engage in data-driven decision making.


3. Critique the benefits and risks of different ways to analyze data distributions for making inferences on student performance.


4. Gain experience with interpreting and understanding pitfalls of several common numerical and graphical representations in reasoning with educational data.

• Exploring the importance to of data literacy for teachers


• Learning how to collect, analyze, and interpret data, as well as how to use data-driven insights to make informed decisions

• Defining measures to understand and compare data distributions


• Reasoning about how common data visualizations can be misleading and how to accurately read and interpret them

Mode of Delivery: 

*MOE Participants include: MOE Participants & Direct Hires Staff from independent schools, Specialised Independent and Specialised Schools