Evaluation of the Education Statistics Program

Background

Overview of the Education Statistics Program

In Canada, education is a provincial and territorial responsibility. At the same time, comparable pan-Canadian information is essential to support federal, provincial and territorial (FPT) coordination; inform policy development; and meet national and international reporting commitments. To support this need, pan-Canadian governance bodies and working-level committees help set priorities, make decisions, and coordinate processes that ensure coherent and comparable education statistics. It is within this context that the Canadian Centre for Education Statistics (CCES) delivers the Education Statistics Program (ESP) as part of Statistics Canada's mandate.

The CCES serves as Statistics Canada's centre of expertise for education, training and learning statistics. It provides several national indicators and contributes to internationally comparable pan-Canadian measures. CCES data products are widely used to inform policy, support research and provide insights into Canada's education landscape. Its activities are funded through Statistics Canada's ongoing operating budget for education and social statistics, supplemented by cost-recovery funding. From fiscal years 2020/2021 to 2024/2025, CCES expenditures totalled $40 million.

Within Statistics Canada, several divisions collaborate to ensure alignment of education-related priorities and to leverage complementary expertise. While the CCES leads the coordination and delivery of core education statistics, other divisions also produce education-related information as part of their mandates. For example, the Economic and Social Analysis and Modelling Division and the Health Analysis and Modelling Division produce analytical products that integrate education variables, strengthening analysis across interconnected domains such as education, health, family well-being and the labour market. Major data sources, such as the Census of Population, the Labour Force Survey and the Indigenous Peoples Survey, also contribute education-related content that is disseminated both within and outside the CCES.

Governance of education statistics in Canada

Governance of education in Canada is inherently multi‑layered and complex. Because authority rests with the provinces and territories, producing national-level education statistics depends on coordination rather than centralized control. Pan‑Canadian governance mechanisms provide structured forums for jurisdictions to collaborate on shared priorities, address cross‑jurisdictional challenges and coordinate responses to national issues. These mechanisms also help present a unified Canadian voice in international education forums and support more harmonized policy approaches across Canada's decentralized landscape.

At the pan-Canadian level, the Council of Ministers of Education, Canada (CMEC) serves as the main intergovernmental forum through which the provinces and territories collaborate on shared education priorities and coordinate national and international engagements. CMEC activities are supported by the CMEC Secretariat, which manages intergovernmental meetings and communications, and by the Advisory Committee of Deputy Ministers of Education, which provides strategic advice and raises issues requiring ministerial attention.

CMEC also oversees data and research activities that inform education policy across Canada. Many of these initiatives are delivered through the Canadian Education Statistics Council (CESC), a partnership between CMEC and Statistics Canada. As one of the primary governance bodies for pan-Canadian education statistics, it is composed of deputy-level members and provides strategic oversight on national objectives, priorities, methodologies, data needs and budget planning to support coherent and comparable education statistics across jurisdictions.

The Strategic Management Committee (SMC) reports to CESC, and this committee includes representatives from provincial and territorial education ministries, CMEC, and the CCES. Co-chaired by CMEC and Statistics Canada, the SMC meets twice each year and serves as the operational arm of CESC. It facilitates information sharing, supports indicator development and methodological discussions, and keeps partners informed of ongoing and planned initiatives. Several working groups report to the SMC, enabling coordination across related pan-Canadian and international projects.

Internationally, Canada's education statistics are shaped by participation in multilateral initiatives, particularly those led by the Organisation for Economic Co-operation and Development (OECD). CMEC and Employment and Social Development Canada (ESDC) coordinate Canada's engagement on these committees, with Statistics Canada contributing technical and analytical expertise to ensure high-quality, internationally comparable education data.

Through these mechanisms and its close relationship with ESDC, the CCES contributes to harmonized pan‑Canadian data collection, supports the development of shared indicators and helps ensure that national statistical outputs are aligned with broader intergovernmental priorities. Figure 1 provides a simplified view of the governance structure referenced in this evaluation and does not reflect its full complexity.

Description - Figure 1

Figure 1 shows the main organizations and committees referenced in the evaluation that are involved in pan-Canadian education statistics and how they relate to each other. The figure is simplified and is intended to be read from top to bottom, moving from pan-Canadian education leadership to education statistics governance, operational committees, and supporting units. It also includes an international component describing Canada's engagement with the Organisation for Economic Co-operation and Development (OECD). The overall graphic suggests that Statistics Canada and CMEC are central coordinating bodies.

Top of the diagram (pan-Canadian education leadership)

• Statistics Canada is shown at the top left. A horizontal line connects Statistics Canada to the Council of Ministers of Education, Canada (CMEC) near the top centre, and continues to Employment and Social Development Canada at the top right..
• The Council of Ministers of Education, Canada (CMEC) is shown at the top centre as the overarching pan-Canadian education body. Two connected supporting bodies are places below it: the CMEC Secretariat and the Advisory Committee of Deputy Ministers of Education, which support CMEC.

Middle of the diagram (education statistics governance partnership)

• Below CMEC is the Canadian Education Statistics Council (CESC), which is a partnership between CMEC and Statistics Canada and is shown as the primary governance body for pan-Canadian education statistics.

Lower part of the diagram (operational committee structure and support)

• Below the CESC is the Education Strategic Management Committee (SMC), which oversees working groups and subcommittees, which report to, and are shown under, the SMC.
• Below Statistics Canada, the Canadian Centre for Education Statistics (CCES), a division of Statistics Canada, is shown as supporting the SMC. The accompanying text also notes that CCES delivers workshops.

International component (OECD engagement)

• In the international component, the figure shows how Canadian partners engage with the Organisation for Economic Co-operation and Development (OECD).
• CMEC and Employment and Social Development Canada (ESDC) are shown as coordinating Canada's participation in OECD-led multilateral initiatives.
• Statistics Canada is shown as supporting this work by contributing statistical expertise to the OECD and by supporting ESDC.

About the evaluation

Authority

The evaluation was conducted in accordance with the Treasury Board Policy on Results and Statistics Canada's Risk-Based Audit and Evaluation Plan (2025/2026 to 2029/2030).

Objective and scope

The objective of the evaluation is to provide a neutral, evidence-based assessment of the ESP's ongoing relevance and performance, including how well the program meets evolving information needs and contributes to the availability of high-quality education-related statistical information.

The scope, determined in consultation with the CCES as the office of primary interest, covered statistical data and insights organized under the following five thematic areas:

1. early childhood learning
2. elementary and secondary education
3. postsecondary education
4. adult learning
5. integrated education information.

These thematic areas align with the four pillars of learning in the CMEC Framework for Statistics on Learning and Education in Canada, with an additional category of integrated education information that cuts across all four pillars. The list of surveys and administrative data collections that underpin these data and insights, and that were included in the evaluation scope, is provided in Appendix A.

The evaluation was conducted from August to November 2025.

Approach and methodology

The evaluation was guided by the following two questions:

1. How well does the ESP's coverage align with key statistical information needs and priorities?
2. How effectively does the ESP deliver high-quality education-related statistical information?

More information about the evaluation questions and related indicators can be found in Appendix B.

The data collection methods outlined in Figure 2 were used. The findings outlined in this report are based on the triangulation of these data collection methods.

Description - Figure 2

Figure 2 outlines the methods used by the evaluation for data collection.

• External Interviews: These are semi-structured interviews and group discussions with data users from federal and provincial government organizations, academia, and education organizations. A total of 21 external interviews with 26 people were conducted.
• Internal Interviews: These are semi-structured interviews with CCES representatives, as well as partners within Statistics Canada. A total of 12 internal interviews with 18 people were conducted.
• Document Review: Review of Statistics Canada's documents, grey literature and web trends information
• External Survey: A survey of data users from FPT governments, academia and other organizations. The data user survey was sent to 99 users, with a response rate of 17%.

Three main limitations were identified, and mitigation strategies were employed, as outlined in Table 1.

Relevance

The ESP's coverage follows the CMEC framework and has expanded over time to include a mix of surveys, administrative data and integrated initiatives that together provide a comprehensive picture of education in Canada.

ESP statistical data and insights are guided by the CMEC Framework for Statistics on Learning and Education in Canada, which provides a common structure across jurisdictions to support coherence and comparability in education statistics. The framework organizes education statistics into four lifelong learning pillars: early childhood learning and development, elementary and secondary schooling, postsecondary education, and adult learning and skills development.

The ESP comprises a mix of surveys and administrative data collections that have evolved over time and operate on different collection cycles. The mix includes long-standing surveys that continue to be collected, surveys that have been discontinued or restructured, and newer initiatives introduced at different points in time.

The CCES manages 12 household and institutional surveys, many of which draw on respondents' administrative records. The CCES also manages three administrative data collections based on operational records and plays a technical implementation and data stewardship role for three additional assessments governed internationally and across Canada. Moreover, the CCES oversees three complementary education information initiatives that bring together multiple sources to support cross-cutting analysis and comparability across jurisdictions and over time, ranging from a consolidated data survey to integrated platforms (see Table 2).

Overall, the ESP provides comprehensive coverage across all pillars of lifelong learning and key elements of the education system. It is supported by integrated data sources and partnerships that enhance longitudinal analysis and ensures alignment with evolving pan‑Canadian priorities.

ESP surveys and administrative data provide extensive and detailed coverage across the four lifelong learning pillars and key dynamic elements of the education system, from inputs to longer-term outcomes, consistent with the CMEC framework (see Table 3).

The ESP integrates and harmonizes surveys and administrative data and coordinates collection cycles to enable longitudinal analysis and support evidence-based decision making (see Figure 3).

Description - Figure 3

Figure 3 presents three data sources that the ESP uses to integrate and harmonize survey and administrative data and to coordinate collection cycles:

• Administrative sources: Data collected by organizations for operational purposes and later used by the ESP to produce statistical information (e.g., PSIS, RAIS, FINCOL, FINUNI, TLAC).
• Surveys: Information collected directly from people living in private dwellings (e.g., ESES, SAEP, PIAAC, SELCCA, CSELCC, Census of Population, Indigenous Peoples Survey).
• Data integration: Data integrated from multiple sources—often administrative or survey data—to create unified datasets for longitudinal and cross-sector analysis (e.g., ELMLP) (see Appendix C).

This integrated approach benefits both data providers and users by reducing response burden on individuals and institutions while helping policy makers and stakeholders understand how access, resources, delivery and outcomes interact across the education lifecycle. For example, educational attainment data can be linked with labour market outcomes to provide a more complete picture of pathways and results. This approach also supports the identification of emerging gaps, pressures and trade-offs. ESP data also support national reporting requirements and Canada's international reporting commitments.

To maintain this comprehensive coverage of education in Canada and to ensure that its statistical information aligns with the needs and priorities of the main data users, the CCES has worked closely with partners across organizations and government departments to evolve its surveys and administrative data collections in response to emerging priorities and information needs.

• Provincial and territorial education partners: Collaborations with provincial and territorial education partners inform pan-Canadian education indicators and research agendas. Consultations with key users, including ESDC and CMEC, inform indicator updates derived from selected surveys to expand available datasets that meet data users' evolving needs. For example, the 2020 NGS included new questions on the impacts of the COVID-19 pandemic on the education and employment of graduates, and both the NGS and the PSIS were updated to capture microcredential programs^{Footnote 3} to better understand the supply of labour market skills.
• Partnerships with federal departments: Collaboration with ESDC, a main partner of the ESP, involves cost-recovery deliverables that collect data to inform needs related to the labour market, skills development, financial and affordability research, and policy and program development. For example, the SELCCA, CSELCC and SAEP data inform accessibility and affordability policies and programs for early learning and child care and postsecondary education. While data collected through the PSIS, NGS, RAIS and ELMLP enable analysis of education-to-work pathways and skills supply, they also enable alignment with labour market needs. Additionally, the SPFR, sponsored by Innovation, Science and Economic Development Canada,^{Footnote 4} addressed information gaps related to equity, diversity and inclusion (EDI) among postsecondary educators and researchers.

In addition to partnerships with provincial and federal organizations, the ESP partners with other professional organizations to ensure that education statistics remain relevant for conducting strategic planning, monitoring performance, and informing evidence‑based policy and program development. For example, through its long‑standing partnership with the Canadian Association of University Business Officers, Statistics Canada works with universities and colleges to produce standardized financial information for the postsecondary sector, enhancing its quality, comparability and policy usefulness.

ESP statistical data and insights are reported to provide national-level information that would otherwise not be available to support data users' needs and to be useful and relevant for a wide variety of applications.

Overall, evidence from multiple sources indicates that the ESP's statistical data and insights are highly valued because they provide a trusted, neutral source of information not easily replaced by other data. Statistics Canada is viewed as one of the few organizations with both the mandate and the capacity to support data coordination across all jurisdictions. As a result, its data are widely regarded as credible and are used to support a broad range of analytical and operational activities (see Figure 4).

ESP data are considered essential by most users because national-level statistical information is either unavailable elsewhere or difficult to obtain from other sources. Surveyed users highlighted the program's importance: 53% reported relying entirely on ESP data, while 31% reported partial reliance, often supplementing these data with provincial, territorial, institutional or other sector-specific sources.^{Footnote 5} Patterns of use suggest that most users engage with the data to meet practical and immediate needs. A majority of users (77%) reported accessing the data either regularly throughout the year or in "bursts" during periods of high demand, while about 20% reported lighter, more occasional use.

Users most often reported relying on data tables and analytical products to support their work and areas of interest. Thematically, they most frequently chose postsecondary education information and integrated statistical information (e.g., the ELMLP) as their top areas of interest. This is reinforced by Statistics Canada web metrics, which show sustained interest in postsecondary education products, particularly those related to institutional financial information, as well as in integrated analytical content. Additionally, a review of web traffic also showed that online searches led individuals to discontinued publications that examined trends and relationships across the education and training landscape, suggesting continued interest in integrated information. Overall, uptake of online ESP products has remained generally stable from fiscal years 2020/2021 to 2024/2025.

At the same time, many users noted that additional analytical products would enhance the relevance and usefulness of ESP data. Ongoing work within the PCEIP's modernization, such as new analytical papers (e.g., on populations not in employment, education or training and on high school completion for Indigenous communities), new or updated indicators, expanded data visualizations, and enhanced communications, may help address these needs.

Description - Figure 4

Figure 4 is a four-panel summary of how respondents use education statistics. It combines (1) a list of common uses, (2) a bar chart reporting the share of respondents who rated thematic areas as important, (3) a short summary of usage patterns expressed as percentages, and (4) a table listing the most-viewed education data and publications with their number of views.

Panel 1: Overall use of education statistics

This panel lists six main ways respondents reported using education statistics:

• Academic and labour market research (e.g., aligning skills requirements with the labour market).
• Policy development and analysis (e.g., assessing postsecondary education accessibility).
• Program planning and evaluation (e.g., monitoring progress on affordability-related initiatives).
• Public and stakeholder reporting (e.g., supporting departmental and public reporting requirements).
• National trend monitoring and benchmarking (e.g., tracking enrolment patterns and assessment results).
• Advocacy activities (e.g., supporting evidence-informed positions or briefings).

The source for this panel is the evaluation survey and interviews.

Panel 2: Perceived importance of education thematic areas (bar chart)

This panel is a bar chart. Each bar is an education thematic area, and the value is the percentage of respondents who ranked that area as important. The thematic areas are shown from highest to lowest percentage:

• Post-secondary: 87.9%.
• Education and Labour Market Longitudinal Platform (ELMLP): 70.7%.
• Elementary and secondary: 69.7%.
• Adult learning: 65.7%.
• Pan-Canadian Education Indicators Program (PCEIP): 60.6%.
• Early childhood learning: 51.5%.

The source for this panel is the evaluation survey.

Panel 3: Use patterns

This panel summarizes how respondents described their use of Statistics Canada education data. The figure reports three percentage statements:

• 53% rely entirely on Statistics Canada data.
• 42% reported burst-style use (use concentrated in specific periods rather than ongoing).
• 35% reported continuous use (ongoing use over time).

The source for this panel is the evaluation survey.

Panel 4: Most-viewed education statistics data and insights (table)

This panel is a table of web engagement. It lists specific education-related data tables and publications and shows the number of views for each. The table is split into two groups: "Data tables" and "Publications." Within each group, each row contains the item title (or identifier) and its view count. The source for this panel is Statistics Canada web metrics for fiscal years 2020/2021 to 2024/2025.

For the data tables, the items titles and their corresponding view count are as follows:

• 37-10-0045-01—Canadian and international tuition fees by level of study (current dollars): 101,700 views
• 37-10-0018-01—Postsecondary enrolments, by registration status, institution type, status of student in Canada and gender: 65,312 views
• 37-10-0036-01—Student debt from all sources, by province of study and level of study: 55,173 views
• 37-10-0003-01—Canadian undergraduate tuition fees by field of study (current dollars): 53,985 views
• 37-10-0108-01—Number and salaries of full-time teaching staff at Canadian universities: 51,938 views

For the publications, the items titles and their corresponding view count are as follows:

• Education Matters: Insights on Education, Learning and Training in Canada: 297,265 views
• Education Indicators in Canada: An International Perspective: 287,288 views
• Education Indicators in Canada: Fact Sheet: 105,062 views
• Education Indicators in Canada: Report of the Pan-Canadian Education Indicators Program: 86,377 views
• Technical Reference Guides for the Education and Labour Market Longitudinal Platform (ELMLP): 28,478 views

While ESP coverage is reported to be meeting data users' needs and priorities, supporting both analysis and decision making, some coverage gaps remain, particularly in areas requiring enhanced disaggregation, longitudinal linkage (e.g., the ELMLP) or program-level outcomes. These gaps reflect structural and resource constraints inherent in a partnership-based data environment, including reliance on provincial and territorial data, combined with predominantly federal funding. Where possible, the ESP addresses these challenges through targeted partnerships and ongoing improvements.

Overall, data users report that ESP statistical coverage meets their needs, but some gaps remain. Data users reported ongoing challenges in accessing disaggregated data across thematic areas, such as across geographic regions and equity groups. For example, users have shared that they would like to see rural and remote data in the SAEP and gender categories beyond "woman" and "man" in the UCASS. Some of these gaps may be partially addressed through future data linkages with the 2026 Census of Population, which will collect more detailed information on equity group identifiers (e.g., sexual orientation), and the UCASS modernization initiative is integrating new EDI variables.

Other coverage gaps were reported to occur at the national and cross-jurisdictional levels. For example, while several provinces and regions, including Ontario, Quebec and the Atlantic provinces, regularly survey postsecondary graduates, data from the NGS are released only every four years. The infrequent collection of the NGS is reported to limit its ability to track labour market misalignments, especially in fast-moving fields, such as science, technology, engineering and mathematics (STEM). Additionally, certain provinces and territories track secondary-to-postsecondary transition rates but lack the mechanisms to compare their jurisdictional data with those in other jurisdictions or with national statistics. Meanwhile, Statistics Canada does not have the secondary school microdata for most jurisdictions that would be needed for pan-Canadian or national longitudinal secondary-to-postsecondary transition rates.

The ELMLP has been widely recognized by users as a significant innovation. It enables large-scale longitudinal analysis of education pathways and labour market outcomes through the linkage of annually refreshed core datasets (e.g., PSIS, RAIS) and supplementary datasets (e.g., census, NGS, NAS), which are updated on variable cycles. Recent expansion through linkages with provincial kindergarten to Grade 12 (K-12) data in British Columbia and Ontario further enhances the ELMLP's analytical potential by enabling examination of how earlier educational experiences shape later outcomes in these provinces. Evidence indicates that the relevance of the ELMLP could be increased by expanding K-12 linkages across additional jurisdictions and integrating more demographic and contextual data to enhance national coverage, policy insights and equity analysis.

The literature review has also revealed some gaps in the availability of data related to learning quality, particularly in areas such as early learning environments. However, such environments typically require qualitative or observation-based research approaches that may fall outside the scope of the ESP. In the meantime, early learning and child care data are limited in informing the multilateral commitment to increase the quality of early learning and child care. The ESP is also less capable of capturing dimensions of academic achievement to inform trend analysis for policy development and monitoring because much of this information is entirely owned by its partners, who conduct this work. For example, PCAP's triennial cycle of rotating assessments of academic subjects covers only a sample of Grade 8 students and excludes the territories, preventing granular comparisons across or within jurisdictions over time.^{Footnote 6} Similarly, with PISA being an OECD survey, its focus on international benchmarks—instead of on provincial curriculum goals—reduces its usefulness for provincial monitoring and policy making. Statistics Canada is currently reviewing the policy on posting other parties' data on its website.

Additional gaps identified by data users for each thematic area are summarized in Table 4. Some of the identified gaps reflect areas where data either do not exist or are not accessible to the ESP and, therefore, fall outside the ESP's control.

The ESP's reliance on provincial and territorial data and predominantly federal funding is shaped by intergovernmental agreements, jurisdictional priorities and budget cycles. This reliance helps to ensure alignment with FPT policy needs but does not always reflect the evolving needs of the research and academic community. This dependency also constrains the ESP's flexibility and responsiveness, limiting its ability to address broader data gaps; pursue innovation; or react quickly to emerging, time-sensitive data needs. For example, updating surveys often requires several years before data collection can occur.

Amid current socioeconomic and policy shifts, users also identified several emerging needs in education statistics, such as understanding the impacts of artificial intelligence on learning and skills development, as well as pressures on education systems stemming from government caps on immigration. Program representatives noted an awareness of these emerging needs; however, addressing them depends largely on continued consultations with partners to explore feasible solutions, options that frequently depend on the availability of funding within a cost-recovery model.

Performance

The ESP continues to deliver high-quality statistical information on education; however, variability across jurisdictions and declining response rates create comparability challenges that the program works to address through ongoing harmonization efforts.

Overall, evidence indicates that the ESP delivers high-quality statistical information across its thematic areas. Most surveyed data users and key interviewees reported high levels of satisfaction with the accuracy and reliability of ESP data, while recognizing that there are some use-related challenges.

With respect to accuracy, program records show that, since fiscal year 2022/2023, no major errors have been identified in ESP-related releases (i.e., data tables and publications on the Statistics Canada website), and only four minor issues—primarily quality control or editing errors—were found and promptly corrected. While most ESP surveys and data collections are administrative or census-based, declining response rates for some voluntary education surveys (e.g., NGS, SPFR, PIAAC) may pose a long-term risk to data accuracy, though this trend is not unique to education statistics.

Administrative or mandatory data collections, such as those from FINESS and ESES, provide near-complete coverage. However, these data sources can create comparability challenges when jurisdictions collect or report information differently. For example, variations in the granularity of high school graduation data across provinces and territories require the ESP to standardize the data. This involves making and defining certain assumptions, such as student transfers, and applying these uniformly across all datasets to develop indicators. As a result, this can distort graduation rates and make it difficult for provinces and territories with more detailed data to compare their own results with other jurisdictions or national estimates. This specific comparability challenge was reported to fall largely outside the agency's control, and users generally reported that the differences were well explained through the program's methodological notes. To strengthen comparability, the ESP has also taken steps such as harmonizing the expenditure-per-student data from the PSIS and aligning the NGS questionnaire with other Statistics Canada social surveys.

While statistical information on education is accessible through multiple channels, users' experiences accessing it vary. Some challenges relate to users' capacity, resource constraints and limited awareness of available products, while others stem from difficulties navigating the ELMLP. Partners also face broader systemic barriers that affect timely and efficient access to data, reducing these partners' ability to fully leverage the value of the data.

The ESP provides multiple ways for users to access data, including through analytical reports, data tables, interactive dashboards and linked longitudinal outcomes. Users typically obtain information through the Statistics Canada website, The Daily releases, microdata files and custom products. While ESP information on the website is generally considered accessible when users know what they are looking for, many found that the website's search function was difficult to use because of the large volume of similar files and tables, making it challenging to quickly locate specific information.^{Footnote 8}

Accessibility challenges were also linked to users' capacity and resource levels. For example, data accessed through Statistics Canada's virtual data labs are reported to be useful primarily to experienced data analysts, a resource that not all organizations possess. A few users also noted that greater promotion of the ESP's data products could help increase awareness and uptake.

Some partners and data users identified additional barriers in accessing and using education data efficiently. The processes to access data through the research data centres were described as inefficient, because each output requires manual vetting prior to release, resulting in significant delays. Accessing data through the ELMLP was similarly seen as challenging, particularly when information is needed quickly, because it requires an approved research proposal. Some users also found that the ELMLP interface was difficult to navigate and less accessible for those with limited analytical expertise. A few users suggested establishing a community of practice to help provincial and territorial partners better understand and use ELMLP datasets.

Other limitations include restricted opportunities to review and update administrative data because of concerns around disrupting time series and comparability. As a result, some administrative data evolve slowly relative to user needs. Some partners also reported duplicative costs, noting that difficulties maintaining ongoing access to previously sponsored datasets sometimes required them to repay for access. In addition, the cost of custom data products was cited as a barrier for users and partners with limited budgets.

Timeliness varies across ESP deliverables, with extended release cycles and jurisdiction‑dependent constraints limiting the usefulness of some data, particularly in fast‑moving policy and labour market contexts.

While some interviewees expressed the need to improve the timeliness of ESP data, almost all users indicated that they were unwilling to compromise on accuracy for faster release. Timeliness challenges were most evident for some of the postsecondary and adult learning deliverables. For example, PSIS data are released two years after the reference academic year, and NGS results are published approximately one year after collection. Because the NGS targets graduates three years after graduation, the resulting four-year lag was reported to reduce the usefulness of the data.

Timeliness has improved for RAIS data, which are now released one year after the reference period. By contrast, PIAAC is administered only once every 10 years, resulting in long intervals between releases. A few users noted, however, that more frequent PIAAC cycles would not necessarily strengthen trend analysis, as relevant changes typically occur over longer periods. Similar to comparability issues, some timeliness constraints fall outside Statistics Canada's control because they depend on the timing and quality of data submitted by jurisdictions and institutions.

Lags in some surveys, particularly the PSIS, were reported to affect program and policy analysis in fast-moving fields such as STEM, where up-to-date information on graduates is essential to understand labour market supply and demand and to inform consultations on rapidly evolving areas such as artificial intelligence. Delays in postsecondary data were also reported to limit the ability to assess the impacts of major policy changes and events, such as the federal cap on international students and the COVID-19 pandemic.

According to Statistics Canada's 2023 Client Experience Index, clients who contacted the agency about education, training and learning services reported the lowest satisfaction with both timeliness and ease of access, compared with other program areas. Evaluation survey results also indicate that 32% of respondents who requested a custom education data product or service from Statistics Canada found the turnaround time too long.

Pan-Canadian governance for education statistics supports consistent working-level collaboration and information sharing, but limited strategic oversight and varying jurisdictional capacities continue to affect progress on shared priorities.

Pan-Canadian education statistics operate within a complex, consensus-based governance environment that shapes how the ESP advances its work and responds to evolving user needs. Within this context, the evaluation found that, although the governance model supports strong collaboration—particularly through project-level committees—and facilitates strong information sharing across organizations, several structural factors continue to limit progress on shared priorities.

CESC remains the central priority-setting body for pan-Canadian education statistics. However, since 2021, it has operated only through desk-based processes and has not convened formally. This has reduced opportunities to revisit priorities, provide strategic direction on emerging issues or advance initiatives requiring multi-jurisdictional alignment. As a result, progress on several identified priorities has been limited. For example, online learning and distance education were designated as priority areas, but there was insufficient support to advance related work through the SMC working groups.

In response to the limited activity at the CESC level, a few key interviewees noted that the SMC has taken steps to move beyond its traditional information-sharing role by contributing to priority setting, with support from the CMEC Secretariat in gathering jurisdictional perspectives. However, because priority setting relies on consensus among provincial and territorial partners with differing capacities, mandates and data environments, it remains challenging to reassess priorities or address emerging issues. In addition, SMC members do not always have the authority to make jurisdiction-wide decisions, and this can limit the committee's ability to advance CESC's strategic priorities.

Key interviewees noted that, while the SMC provides a valuable venue for provinces and territories to engage with one another and with Statistics Canada, differences in statistical capacity, resource limitations, a wide and evolving agenda, and the rapid pace of data needs make it challenging to sustain deeper discussions, reach consensus and maintain momentum. Interviewees also noted that some jurisdictions are represented by individuals from different departments, which can reduce engagement. The breadth of the agenda and the virtual format of meetings also limit opportunities for informal interactions that help build shared understanding across partners.

Despite these constraints, the SMC has enabled progress on several CESC priorities identified in 2019, such as microcredentials, longitudinal indicators and pan-Canadian Indigenous education data. Except for online and distance learning, where interest declined across several jurisdictions, these priorities have advanced through work undertaken in the PSIS and the ELMLP.

By continuing to leverage its unique role, the CCES can help advance pan‑Canadian education statistics. Strengthening coordination with partner divisions within Statistics Canada would also support a more consistent and transparent experience for stakeholders.

Interviewees noted that the CCES's visibility and subject-matter expertise across governance forums strengthen its ability to identify emerging needs and initiate strategic discussions. The SMC and other key partners highlighted that many priorities arise through working‑level exchanges and ad hoc agreements, where the CCES plays a central role in guiding and advancing discussions.

Given its technical expertise, long-standing relationships with FPT partners, and involvement across the education and labour market domains, the CCES is well positioned to help strengthen coordination. Enhancing communication channels, facilitating more systematic information sharing and encouraging more frequent review of emerging issues could help maintain a shared understanding of priorities, particularly in the absence of regular senior‑level oversight. These efforts may also help address long-standing information needs, including data gaps and timeliness challenges.

Because education statistics are cross-cutting, effective coordination within Statistics Canada requires collaboration across several divisions. For instance, the early learning and child care theme intersects with early education, child development, health and family well-being, spanning multiple subject-matter areas across the Social, Health and Labour Statistics Field (Field 8); the Economic Statistics Field; and the Strategic Data Management, Methods and Analysis Field. To manage this cross-cutting structure and leverage the mix of expertise, participating divisions maintain ongoing communication to clarify responsibilities and determine the appropriate lead division. The CCES Analytical Committee, an internal forum for exchanging analysis-related expertise on education, also supports coordination by conducting peer reviews of analytical projects, overseeing data releases and providing methodological guidance in collaboration with partner divisions.

Stakeholders reported positive interactions with the CCES and with experts in other divisions. However, a few stakeholders noted that when multiple divisions engage with the same users, ambiguity can arise, particularly at early stages of engagement. Questions often come up about the primary point of contact, how communication is coordinated and how follow-up will occur. External stakeholders do not always distinguish between divisions within Statistics Canada, so this lack of clarity can influence their overall perception of the agency. Given the relatively small stakeholder community, greater transparency around roles and activities—along with stronger cross-divisional coordination—could help support a more consistent and coherent experience for partners.

Project‑level governance supports effective oversight and progress when clear structures and partner alignment are in place; however, inconsistent governance frameworks and differing priorities can limit advancement, including for initiatives related to the ELMLP.

Statistics Canada responds effectively to SMC priorities at the project level when jurisdictions clearly articulate their needs and when the necessary data are available. The work on graduate mobility was highlighted as a positive example, where close collaboration between provinces and territories and Statistics Canada enabled the development of a pilot project linking mobility information with the ELMLP. Other projects have shown similar responsiveness, though progress can be constrained when they lack a formal multi‑partner governance structure to reconcile varying jurisdictional priorities.

Projects pertaining to adult learning statistics benefited from well-established governance mechanisms that provide operational oversight and support priority setting. For example, PIAAC is guided by international and national governance structures, as well as by an internal steering committee at the director general (DG) level within Statistics Canada. This structure has been effective in advancing the survey. Similarly, the Canadian Council of Directors of Apprenticeship Research Committee sets research priorities, provides guidance to Statistics Canada and monitors deliverables for the RAIS.

By contrast, efforts to establish an ELMLP governance committee with provinces and territories were unsuccessful because of differing partner priorities. While jurisdictions were consulted during the initial indicator development, there is no evidence of ongoing engagement through a formal governance body.

Collaboration with ESDC reflects both strong working-level relationships and some structural complexities. While ESDC does not participate in the main governance bodies (i.e., CESC or the SMC), it engages with CMEC on international initiatives such as PIAAC and PISA and plays a central role in labour market and apprenticeship-related projects, like the RAIS. Interviewees indicated that these partnerships help ensure ESDC remains informed about provincial and territorial priorities, and that the department's involvement is often more effective at the project level, where roles and responsibilities are more clearly defined. At the same time, jointly establishing priorities for cost-recovery projects can be complex because of ESDC's internal structure and the need to balance diverse mandates and priorities. Despite these factors, once priorities are agreed upon, ESP deliverables generally meet user needs. Coordination for multi-year cost-recovery projects, such as the ELMLP, has improved in recent years through adjustments to the annual work cycle and increased alignment facilitated by the Chief Data Officer Branch within ESDC.

The ESP's budget constraints and reliance on cost-recovery funding, primarily through one funder, introduce structural vulnerabilities that affect program stability and long-term planning.

Broader contextual factors, including budget constraints and significant reliance on cost-recovery funding, also affect the ESP's operations. These conditions limit the program's capacity to plan over longer horizons, adapt to emerging needs and balance funder‑specific requests with its mandate to serve all Canadians.

From fiscal years 2020/2021 to 2024/2025, cost-recovery funding accounted for 55% to 64% of annual salary expenditures. Because most of this funding comes from one federal partner, shifts in that partner's budget cycles or priorities can affect program work. While the cost-recovery model enables targeted responsiveness, it also introduces volatility. Changes in funder interests or the discontinuation of funded products, such as the Youth in Transition Survey and the NAS, have contributed to coverage gaps that many data users continue to highlight, though the ELMLP is expected to help address some of them.

Balancing funder-specific priorities with Statistics Canada's broader mandate can also be challenging, particularly when funders request narrowly scoped data for their own program needs. The CCES takes this dynamic into account and takes steps to ensure that data collection and analysis remain aligned with organizational objectives and the needs of Canadians.

Operational budget pressures also require the CCES to be more selective about its projects. These constraints have reduced opportunities for international travel, which previously supported greater awareness of global developments and strengthened international comparability. While virtual participation in international forums enables the CCES to remain informed of formal discussions, it limits the agency's ability to influence education data development at the international level. For example, Statistics Canada was removed as the chair of an OECD working group as a result of only being able to attend meetings virtually. Having only a virtual presence offers fewer opportunities for informal exchanges that can help identify emerging directions and create opportunities to influence discussions.

The CCES faces wide-ranging pressures to maintain workforce sustainability but is mitigating these challenges through strengthened succession planning and knowledge transfer practices to support continuity.

Given current fiscal constraints and the specialized nature of the workforce, succession planning and knowledge transfer are critical to sustaining CCES capacity. Results from the 2024 Public Service Employee Survey show a decline in CCES employees' satisfaction with their work environment relative to 2022, and 35% of CCES employees indicated an intention to leave within two years. Upcoming fiscal measures and potential early retirement incentives may also affect workforce stability.

Because the program relies on a highly specialized and adaptable workforce, the CCES has invested in cross-training, knowledge transfer planning and detailed documentation to support future program cycles. Maintaining and further strengthening these practices will be essential as the agency adapts to upcoming changes.

How to improve the program

Management considerations

The evaluation identified a few considerations for management that the assistant chief statistician (ACS) of Field 8 may wish to reflect on, rather than formal recommendations, to help strengthen pan-Canadian governance and support a more responsive delivery of education-related statistical information.

At the strategic level, opportunities were noted for the CCES to leverage its unique position to foster more effective coordination and information sharing across FPT partners. Strengthening these practices could help address evolving information needs, including those related to timeliness and data gaps. For instance, management could explore opportunities to support the SMC's governance role in ways that would allow emerging priorities and issues to be reviewed more regularly and reflected in strategic direction and oversight.

In addition, given upcoming organizational changes and some stakeholders' lack of clarity regarding the respective roles of multiple divisions, management may wish to consider measures to clarify key points of contact and reinforce cross-divisional coordination. These steps could support greater transparency and contribute to a more consistent stakeholder experience and understanding.

Recommendation

Given the ELMLP's potential to increase data sources, broaden and deepen coverage, expand partnerships and user groups, and diversify funding, a formal recommendation focused on strengthening the platform was identified.

The ACS of Field 8 should ensure that the ELMLP's governance, engagement and analytical capacity are strengthened. Key actions should include

1. revisiting the establishment of a governance body (e.g., composition, operations) and updating it to ensure appropriate representation and fit for purpose
2. improving data users' and stakeholders' awareness of, and engagement with, the ELMLP to further support platform use and data interpretation
3. continuing to work with stakeholders to prioritize integrated and analytical products that reflect the needs and priorities of data users, such as longitudinal data.