This table contains 28 series, with data for years 2007/2008 - 2014/2015 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) Statistics (2 items: Expenditure per capita; Index of change).

Data on annual expenditure by educational institutions per student, in Canadian and American dollars, reference year 2021/2022. At the primary/secondary level, the amount spent on educational core services and ancillary services is also presented.

Financial information of public and private elementary and secondary education expenditures, by geography.

Financial information of school board expenditures, by geography.

The Canada Millennium Scholarship Foundation (the Foundation) undertook a survey of secondary school students across five provinces focusing on their post-secondary school expectations. This research involved the in-class administration of a survey to Grade 6 to 12 students in British Columbia, Alberta, Manitoba, New Brunswick, and Newfoundland and Labrador. This study was conducted by two independent research companies under contract to the Foundation: Prairie Research Associates (PRA) Inc. and R.A. Malatest & Associates Ltd. The in-class survey instrument was designed to collect information about how secondary school students view education, what they know about the various forms of funding available for post-secondary education and how students envision paying for their future education. The survey administered to Grade 6 to 8 students gathered approximately 65 pieces of information, while the one given to Grade 9 to 12 students collected about 110 pieces of information. To ensure consistent administration of the inclass survey for each student sample, a Survey Administration Guide was developed to recommend procedures to be followed. This dataset was received from the Canada Millennium Scholarship Foundation as is. Issues with value labels and missing values were discovered and corrected as best as possible with the documentation received. The variable -gasst: "Do you receive any government assistance?"- was not corrected due to lack of documentation about this variable. Some caution should be used with this dataset. This dataset was freely received from, the Canadian Millennium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. They were correct as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking information.

Abstract

PIRLS provides internationally comparative data on how well children read by assessing students’ reading achievement at the end of grade four. PIRLS 2016 is the fourth cycle of the study and collects considerable background information on how education systems provide educational opportunities to their students, as well as the factors that influence how students use this opportunity. In 2016 PIRLS was extended to include ePIRLS – an innovative assessment of online reading.

The results of PIRLS 2016 demonstrate a number of positive developments in reading literacy worldwide. For the first time in the history of the study, as many as 96 percent of fourth graders from over 60 education systems achieved above the PIRLS low international benchmark.

Geographic coverage

Nationally representative samples of approximately 4,000 students from 150 to 200 schools participated in PIRLS 2016. About 319,000 students, 310,000 parents, 16,000 teachers, and 12,000 schools participated in total.

Analysis unit

The unit of analysis describes:

• Schools

• Students

• Parents

• Teachers

Universe

All students enrolled in the grade that represents four years of schooling counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years.

All students enrolled in the target grade, regardless of their age, belong to the international target population and should be eligible to participate in PIRLS. Because students are sampled in two stages, first by randomly selecting a school and then randomly selecting a class from within the school, it is necessary to identify all schools in which eligible students are enrolled. Essentially, eligible schools for PIRLS are those that have any students enrolled in the target grade, regardless of type of school.

Kind of data

Sample survey data [ssd]

Sampling procedure

PIRLS is designed to provide valid and reliable measurement of trends in student achievement in countries around the world, while keeping to a minimum the burden on schools, teachers, and students. The PIRLS program employs rigorous school and classroom sampling techniques so that achievement in the student population as a whole may be estimated accurately by assessing just a sample of students from a sample of schools. PIRLS assesses reading achievement at fourth grade. The PIRLS 2016 cycle also included PIRLS Literacy-a new, less difficult reading literacy assessment, and ePIRLS-an extension of PIRLS with a focus on online informational reading.

PIRLS employs a two-stage random sample design, with a sample of schools drawn as a first stage and one or more intact classes of students selected from each of the sampled schools as a second stage. Intact classes of students are sampled rather than individuals from across the grade level or of a certain age because PIRLS pays particular attention to students’ curricular and instructional experiences, and these typically are organized on a classroom basis. Sampling intact classes also has the operational advantage of less disruption to the school’s day-to-day business than individual student sampling.

SAMPLE SIZE

For most countries, the PIRLS precision requirements are met with a school sample of 150 schools and a student sample of 4,000 students for each target grade. Depending on the average class size in the country, one class from each sampled school may be sufficient to achieve the desired student sample size. For example, if the average class size in a country were 27 students, a single class from each of 150 schools would provide a sample of 4,050 students (assuming full participation by schools and students). Some countries choose to sample more than one class per school, either to increase the size of the student sample or to provide a better estimate of school level effects.

For countries choosing to participate in both PIRLS and PIRLS Literacy, the required student sample size is doubled-i.e., around 8,000 sampled students. Countries could choose to select more schools or more classes within sampled schools to achieve the required sample size. Because ePIRLS is designed to be administered to students also taking PIRLS, the PIRLS sample size requirement remains the same for countries choosing also to participate in ePIRLS.

PIRLS STRATIFIED TWO-STAGE CLUSTER SAMPLE DESIGN

The basic international sample design for PIRLS is a stratified two-stage cluster sample design, as follows:

• First Sampling Stage. For the first sampling stage, schools are sampled with probabilities proportional to their size (PPS) from the list of all schools in the population that contain eligible students. The schools in this list (or sampling frame) may be stratified (sorted) according to important demographic variables. Schools for the field test and data collection are sampled simultaneously using a systematic random sampling approach. Two replacement schools are also pre-assigned to each sampled school during the sample selection process, and these replacement schools are held in reserve in case the originally sampled school refuses to participate. Replacement schools are used solely to compensate for sample size losses in the event that the originally sampled school does not participate. School sampling is conducted for each country by Statistics Canada with assistance from IEA Hamburg, using the sampling frame provided by the country’s National Research Coordinator.

• Second Sampling Stage. The second sampling stage consists of the selection of one (or more) intact class from the target grade of each participating school. Class sampling in each country is conducted by the National Research Coordinator using the Within-School Sampling Software (WinW3S) developed by IEA Hamburg and Statistics Canada. Having secured a sampled school’s agreement to participate in the assessment, the National Research Coordinator requests information about the number of classes and teachers in the school and enters it in the WinW3S database.

Classes smaller than a specified minimum size are grouped into pseudo-classes prior to sampling. The software selects classes with equal probabilities within schools. All students in each sampled class participate in the assessment. Sampled classes that refuse to participate may not be replaced.

For countries participating in both PIRLS and PIRLS Literacy, students within a sampled class are randomly assigned either a PIRLS or PIRLS Literacy booklet through a booklet rotation system. This is done to ensure that PIRLS and PIRLS Literacy are administered to probabilistically equivalent samples. In countries taking part in ePIRLS, all students assessed in PIRLS are expected to participate in ePIRLS.

STRATIFICATION

Stratification consists of arranging the schools in the target population into groups, or strata, that share common characteristics such as geographic region or school type. Examples of stratification variables used in PIRLS include region of the country (e.g., states or provinces); school type or source of funding (e.g., public or private); language of instruction; level of urbanization (e.g., urban or rural area); socioeconomic indicators; and school performance on national examinations.

In PIRLS, stratification is used to:

• Improve the efficiency of the sample design, thereby making survey estimates more reliable

• Apply different sample designs, such as disproportionate sample allocations, to specific groups of schools (e.g., those in certain states or provinces)

• Ensure proportional representation of specific groups of schools in the sample School stratification can take two forms: explicit and implicit. In explicit stratification, a separate school list or sampling frame is constructed for each stratum and a sample of schools is drawn from that stratum. In PIRLS, the major reason for considering explicit stratification is disproportionate allocation of the school sample across strata. For example, in order to produce equally reliable estimates for each geographic region in a country, explicit stratification by region may be used to ensure the same number of schools in the sample for each region, regardless of the relative population size of the regions.

Implicit stratification consists of sorting the schools by one or more stratification variables within each explicit stratum, or within the entire sampling frame if explicit stratification is not used. The combined use of implicit strata and systematic sampling is a very simple and effective way of ensuring a proportional sample allocation of students across all implicit strata. Implicit stratification also can lead to improved reliability of achievement estimates when the implicit stratification variables are correlated with student achievement.

National Research Coordinators consult with Statistics Canada and IEA Hamburg to identify the stratification variables to be included in their sampling plans. The school sampling frame is sorted by the stratification variables prior to sampling schools so that adjacent schools are as similar as possible. Regardless of any other explicit or implicit variables that may be used, the school size is always included as an implicit stratification variable.

SCHOOL SAMPLING FRAME

One of the National Research Coordinator’s most important sampling tasks is the construction of a school sampling frame for the target population. The sampling frame is a list of all schools in the country that have students enrolled in the target grade and is the list from which the school sample is drawn. A well-constructed sampling frame provides complete coverage of the national target population without being contaminated by incorrect or duplicate entries or entries that refer to elements that are not

Data about the operating grants issued to universities and publicly assisted colleges of applied arts and technology by the Ministry of Advanced Education and Skills Development. Major grant types include: * basic operating grants and enrolment funding * northern institution and French language or bilingual programs * grants for programs for Aboriginal education, students with disabilities and first generation students * health human resource programs special purpose and other organization grants

Student enrolment data by school and grade as reported by school boards in the Ontario School Information System (OnSIS), October submission for the specified academic year.

The data includes:

• board number and name
• school number, name, type, level and language
• Enrolment by grade

The following elementary and secondary school types are included:

• public
• Catholic

The data excludes, private, publicly funded hospital and provincial schools, care and/or treatment, Education and Community Partnership Program (ECPP) facilities, summer schools, night schools and adult continuing education day schools.

Includes Temporary Remote Learning Schools (TRLS).

To protect privacy, numbers are suppressed in categories with less than 10 students. Numbers that represent 10 or more students are rounded to the nearest count of five.

This statistic shows the average annual tuition fees for full-time Canadian undergraduate students in Canada for the academic year 2024/25, by province. In the 2024/25 school year, Canadian undergraduate students in Ontario paid an average of ***** Canadian dollars.

Snapshot img

Canada Private Tutoring Market Size 2025-2029

The Canada private tutoring market size is forecast to increase by USD 5.36 billion at a CAGR of 10% between 2024 and 2029.

The private tutoring market is experiencing significant growth, driven by several key trends. One of the primary factors fueling market expansion is the increasing emphasis on Science, Technology, Engineering, and Mathematics (STEM) education. With the rising importance of these subjects in the workforce, parents are investing in private tutoring to ensure their children receive a strong foundation in these areas. Data analytics and personalized learning approaches are transforming the industry, catering to the unique needs of students. The market also encompasses career-oriented courses, edutainment, educational tourism, and emerging technologies like augmented and virtual reality games. Another trend shaping the market is the growing popularity of mobile applications and connected devices in private tutoring. These technologies enable flexible learning and personalized instruction, making private tutoring more accessible and convenient for students. Additionally, the availability of open-source educational materials has reduced the cost of private tutoring, making it an affordable option for more families. These trends are expected to continue driving market growth in the coming years.

What will be the Size of the Market During the Forecast Period?

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The private tutoring market continues to experience significant growth, driven by the increasing demand for personalized learning solutions in STEM education. Online private tutoring has emerged as a popular alternative to traditional in-person sessions, with mobile applications and connected devices enabling flexibility and convenience. My Tutor Source and Nirvana Tutoring are among the notable players in this intensely competitive landscape. Parents, particularly those with children in primary learning, are increasingly adopting private tutoring services due to their effectiveness in enhancing academic performance.
Moreover, online booking systems have streamlined the process, making private tutoring more accessible and affordable for a wider audience. However, the high cost remains a barrier for lower-income families.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Curriculum-based learning
  Test preparation


Learning Method

  Online
  Blended
  Classroom-based


End-User

  Preschool And Primary Students
  Middle School Students


Geography

  Canada

By Type Insights

The curriculum-based learning segment is estimated to witness significant growth during the forecast period.

The market has experienced growth, particularly in the segment offering services for STEM subjects. The increasing focus on practical, hands-on learning in educational institutions, driven by the importance of STEM education, has fueled this trend. Parents in Canada are recognizing the value of private tutoring in ensuring their children gain a strong foundation in STEM concepts from an early age. This demand stems from the increasing job opportunities in STEM-based fields and the cultural capital associated with academic success. Despite potential financial compromises for some households, the alternative educational approach continues to gain popularity. A Harvard study supports the effectiveness of private tutoring, highlighting improved exam results for students receiving one-on-one instruction. Private tutoring centers catering to academic private tutors have emerged to meet this demand, serving affluent households and communities alike.

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Market Dynamics

Our Canada Private Tutoring Market researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise in adoption of Canada Private Tutoring Market?

Growing emphasis on STEM education is the key driver of the market.

The private tutoring market is experiencing significant growth due to the increasing focus on STEM education and the proliferation of online private tutoring services. Connected devices and technological advancements have made online learning more accessible and convenient for parents and children, leading to increased adoption of digital tutorial platforms. Personalized learning is a key feature of these platforms, allowing private tutors to provide customized instruction based on students' indi

Weighted average tuition fees for full-time Canadian and international undergraduate and graduate students. Data are collected from all publicly funded Canadian degree-granting institutions.