In 2026, the Centre collégial de développement de matériel didactique (CCDMD) released Quantitative Analysis: Learn to Read, Interpret, and Apply Data, a new online resource developed by Jacqueline De Stefano, a teacher at Marianopolis College. Designed for students enrolled in the mandatory Quantitative Analysis (QA) methodology course in the Social Science Program, the online course helps learners develop the knowledge and skills needed to interpret, analyze, and critically evaluate quantitative data. The platform offers 4 learning modules based on authentic social issues.
September 24, 2026
Quantitative Analysis: A New Online Resource for Social Science Students
Contents
A practical approach to quantitative analysis
The QA course introduces students to the statistical principles and quantitative methods used in social science research. Students learn to:
- formulate measurable hypotheses
- interpret and analyze data
- evaluate research methods
- critically assess data
Designed to support the program competency “Interpret human realities by using quantitative analysis in the social sciences,” the course helps students apply the concepts of the competency to authentic social issues. Rather than presenting statistics in isolation, the modules show how quantitative analysis can help to better understand the world around us.
The 4 self-paced learning modules can be used independently by students or integrated into a course, making them suitable for homework, formative assessment, or in-class activities.
The online modules reinforce the competency through activities that combine theoretical concepts with authentic datasets and current social issues. Within each module, students are encouraged to interpret evidence, question research findings, and reflect on the ethical considerations involved in collecting and analyzing data.
Each module follows a consistent learning sequence:
- Students explore a contemporary issue through news articles and contextual questions.
- They learn about the quantitative concepts and statistical methods required to analyze the topic.
- They apply these concepts by examining peer-reviewed research articles using a Peer-Reviewed Article Breakdown Guide.
- They reflect on the peer-review process.
Relevant formulas and supporting resources are also provided for each module.
4 modules on 4 contemporary issues
Each module explores a different social issue while introducing students to the quantitative tools and social science theories required to investigate it.
Module 1: Language Identity in Quebec
Using debates surrounding language use in Quebec, this module examines how quantitative data can help explore questions related to identity, bilingualism, and language policies. Students learn how to organize and interpret data while exploring social science theories such as:
- social identity theory
- social comparison theory
- social linguistics
Module 2: Youth Unemployment in Quebec and Canada
In this module, students use economic and labour market data to explore employment trends among young Canadians. Students analyze unemployment statistics while exploring concepts such as economic growth, immigration policies, and Okun’s Law to better understand the factors influencing youth employment.
Module 3: Canadian Voting in the 2021 Federal Election
Political polling provides the context for this module, which explores how surveys are designed, interpreted, and communicated during election campaigns. Students examine the reliability and validity of polling data while learning about electoral behaviour, strategic voting, and the role quantitative analysis plays in understanding public opinion.
Module 4: The Loneliness Epidemic
The 4th module focuses on the growing issue of social isolation and its impact on individuals and society. Using data related to health, well-being, and social relationships, students investigate how researchers measure loneliness and explore concepts such as attachment theory and socialization.
Conclusion
By connecting statistical concepts to contemporary social issues, Quantitative Analysis: Learn to Read, Interpret, and Apply Data helps students recognize the relevance of quantitative methods beyond the classroom. Its structured activities provide teachers with flexible resources to support student learning and complement existing QA material.
Whether used to reinforce classroom learning or encourage independent learning, this new CCDMD resource offers an engaging approach to teaching quantitative analysis. How do you think you might integrate these modules into your students’ learning? Share your ideas in the comments section.
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