Module Overview: Data literacy is the ability to understand, interpret, question, and use data effectively. In university and the workplace, students increasingly need to make decisions based on evidence rather than assumptions. This module introduces the foundations of data literacy and shows why data matters for learning, problem-solving, and future employability.
Learning Focus:
What Is Data Literacy?
Why Data Matters in Learning, Work & Society
Basic Data Concepts Every Student Should Know
Using Data Responsibly
Lesson Sequence:
What Is Data Literacy?
Why Data Matters in Learning, Work & Society
Basic Data Concepts Every Student Should Know
Using Data Responsibly
Module Overview: Not all data is equally reliable, accurate, or useful. Students must learn how to identify different types of data, evaluate data sources, recognize quality issues, and question misleading or incomplete information. This module helps students develop the ability to critically evaluate data before using it for analysis, decision-making, or communication.
Learning Focus:
Understanding Data Types
Data Sources: Primary, Secondary & Digital Sources
Data Quality, Reliability & Validity
Identifying Misleading, Biased & Incomplete Data
Lesson Sequence:
Understanding Data Types
Data Sources: Primary, Secondary & Digital Sources
Data Quality, Reliability & Validity
Identifying Misleading, Biased & Incomplete Data
Module Overview: Data becomes more useful when people can interpret it clearly and communicate insights effectively. Charts, graphs, dashboards, and visual summaries help students understand patterns, compare information, and explain findings to others. This module helps students develop practical skills in reading, interpreting, and creating simple data visualizations responsibly.
Learning Focus:
Reading & Understanding Charts and Graphs
Identifying Patterns, Trends & Insights
Foundations of Effective Data Visualization
Communicating Data Clearly & Avoiding Misleading Visuals
Lesson Sequence:
Reading & Understanding Charts and Graphs
Identifying Patterns, Trends & Insights
Foundations of Effective Data Visualization
Communicating Data Clearly & Avoiding Misleading Visuals
Module Overview: Modern academic and workplace environments require students to solve problems using structured thinking, digital tools, evidence, and data-informed decision-making. Strong problem-solving skills help students identify challenges, evaluate solutions, and make better decisions. This module helps students develop practical digital problem-solving and analytical decision-making skills.
Learning Focus:
Foundations of Digital Problem Solving
Analytical Thinking & Root Cause Analysis
Evidence-Based Decision Making
Evaluating Solutions, Risks & Outcomes
Lesson Sequence:
Foundations of Digital Problem Solving
Analytical Thinking & Root Cause Analysis
Evidence-Based Decision Making
Evaluating Solutions, Risks & Outcomes
Applying Data Literacy in Academic & Workplace Contexts
Module Overview: Data literacy is valuable in both academic and professional environments. Universities, organizations, and industries use data to evaluate performance, solve problems, improve services, and support decision-making. This module helps students apply data literacy skills in real academic, workplace, and collaborative contexts.
Learning Focus:
Data Literacy in Academic Success & Research
Workplace Data, Reporting & Performance Measurement
Communicating Recommendations Using Data
Responsible Data Use, Collaboration & Professional Practice
Lesson Sequence:
Data Literacy in Academic Success & Research
Workplace Data, Reporting & Performance Measurement
Communicating Recommendations Using Data
Responsible Data Use, Collaboration & Professional Practice