Council of Ministers of Education, Canada

• Overview
• Pan-Canadian Assessment Program (PCAP)
  • Overview
  • PCAP 2027
  • PCAP 2023
  • PCAP 2019
  • PCAP 2016
  • PCAP 2013
  • PCAP 2010
  • PCAP-13 2007
  • SAIP 1996-2004
• Programme for International Student Assessment (PISA)
• Programme for the International Assessment of Adult Competencies (PIAAC)
• Progress in International Reading Literacy Study (PIRLS)
• International Computer and Information Literacy Study (ICILS)
• Trends in International Mathematics and Science Study (TIMSS)
• Teacher Education and Development Study - Mathematics (TEDS-M)
• Common European Framework of Reference for Languages (CEFR)
• Learning Assessment Data for Researchers

 

 

In spring 2010, the Pan-Canadian Assessment Program (PCAP) was administered for the second time. The primary domain for this assessment was mathematics, and the minor domains were reading and science. The accompanying questionnaires for students, teachers, and school principals were designed to provide jurisdictions with contextual information which would contribute to the interpretation of performance results in mathematics.

The contextual report, PCAP-2010 Contextual Report on Student Achievement in Mathematics, examines achievement in relation to variables derived from the questionnaires and reports the results both descriptively and using simple and multiple regression models.

The first two chapters of this report present an introduction to PCAP and a brief summary of the mathematics achievement results. Chapters 3 through 9 give results for clusters of questionnaire variables and their relationship to mathematics achievement. Three main sets of results are given. First, responses to specific questionnaire items are summarized by population (i.e., jurisdiction and official-language group within each jurisdiction). Next, simple relationships between specific variables and mathematics scores are presented. Finally, at the end of each chapter, a multiple regression model is presented, which examines the relationship of each of the questionnaire variables examined in the chapter, while controlling for all of the other variables in that particular cluster. Chapter 10 examines achievement differences among populations and how these differences relate to equity. The final chapter explores a model that identifies clusters of variables that account for a high percentage of the variability in scores.

Some of the variables associated with higher achievement in mathematics include the following:

• a student's aspirations to higher education levels;
• the use of informal early mathematics learning activities;
• the use of a strategic approach by students to the learning of mathematics;
• more teacher-assigned homework time;
• larger class sizes.

 

Some of the variables associated with lower achievement include the following:

• negative attitudes toward mathematics;
• decreased confidence in mathematics ability over time;
• indirect instruction;
• instruction using projects/assignment.

 

The design of PCAP provides for a research phase that would follow the release of the public and contextual reports. Research work of this kind can extend the findings of this report in relation to policy issues.