National Graduates Survey (NGS)
Detailed information for 2018 (class of 2015)
Every 5 years
The National Graduates Survey collected information from persons who graduated from public postsecondary educational institutions in Canada in 2015. The questions focused on academic path, funding for postsecondary education, including government-sponsored student loans, and transition into the labour market.
Data release - November 5, 2020
Data from this survey will be used to better understand the experiences and outcomes of graduates, and to improve government programs. The survey is designed to collect details on topics such as: i) the extent to which graduates of postsecondary programs have been successful in obtaining employment since graduation; ii) the relationship between the graduates' program of study and the employment subsequently obtained; iii) the type of employment obtained and qualification requirements; iv) sources of funding for postsecondary education; and v) government-sponsored student loans and other sources of student debt.
This information will be used by Statistics Canada, Employment and Social Development Canada (ESDC), provincial and territorial ministries of education, researchers and other interested organizations to examine various aspects such as educational pathways, postsecondary funding, mobility, school-to-work transitions, labour market outcomes and pursuit of further postsecondary studies.
Reference period: Calendar year.
Collection period: June through November of the year that is 3 years after the reference period.
- Education, training and learning
- Employment and unemployment
- Fields of study
- Outcomes of education
Data sources and methodology
The target population of the 2018 NGS consisted of all graduates from a recognized public postsecondary Canadian institution who graduated from their program sometime in 2015, and who were living in Canada at the time of the survey.
- graduates of university programs that lead to bachelor's, master's or doctoral degrees, or that lead to specialized certificates or diplomas
- graduates of post-secondary programs (that is, programs that normally require a secondary school completion or its equivalent for admission) in Colleges of Applied Arts and Technology (CAAT), Collèges d'enseignement général et professionnel (Technical CEGEP in Quebec), community colleges, technical schools or similar institutions
- graduates of skilled trades (that is, pre-employment programs that are normally three months or more in duration) from post-secondary institutions; many community colleges and technical institutes offer certificates or diplomas at the trade level
- graduates from private post-secondary institutions (for example, computer training and commercial secretarial schools)
- graduates who completed "continuing education" courses at universities and colleges (unless they led to a degree or diploma)
- graduates in apprenticeship programs
For the first time, the NGS was available for online self-completion, although respondents still had the option to complete the survey over the telephone assisted by a Statistics Canada interviewer. The 2018 questionnaire was modified in order to facilitate respondent self-reporting and alleviate respondent burden. This was done by updating the questions, response categories, introductory text, instructions, help text and examples. Several new questions were introduced to address new data needs, including a series of questions relating to work-integrated learning (WIL) and entrepreneurship.
The NGS used the same electronic questionnaire (EQ) for both respondent self-completion and computer-assisted telephone interviewing (CATI).
The NGS is a cross-sectional sample survey with a stratified simple random sample design. Two variables were used for stratification: i) province or territory of the institution; and ii) level of study (college, bachelor's, master's, doctorate). The sample selection of graduates within strata was done without replacement using a systematic method.
Data collection for this reference period: 2018-06-07 to 2018-11-09
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data collection for the 2018 NGS started on Thursday, June 7, 2018 and ended on Friday, November 9, 2018. Initial data collection was conducted exclusively online by respondent self-completion. Paper invitation letters were mailed on Thursday, June 7 and electronic invitation emails were sent on Thursday, June 14. Follow-up data collection by interviewer-administered CATI began on Monday, July 9. Over the course of the five-month period of data collection, three paper reminder letters were also mailed and four electronic reminder emails were also sent.
With respect to CATI operations, project supervisors and senior interviewers from each of the Statistics Canada regional offices came to head office for a one-day classroom training session just before the start of data collection. The training included presentations on subject matter and methodology, as well as mock interviews. Those managers then returned to their respective regional offices and conducted similar one-day training sessions for all interviewers. Interviewers were also provided with a detailed interviewer's manual that was prepared by head office for use as reference material during data collection.
Interviewers were instructed to make all reasonable attempts to obtain interviews with the selected graduates. Proxy responses were not allowed. When the timing of the interviewer's call was inconvenient, an appointment was arranged to call back at a more convenient time. For cases where there was no answer or no one home, additional call backs were made. When the graduate could not be reached through the available contact information, various tracing methods were used to try to locate them. For graduates who refused to participate, a paper letter was sent from the regional office stressing the importance of the survey and the graduate's participation. This was followed by another call attempt from an interviewer.
View the Questionnaire(s) and reporting guide(s) .
The electronic questionnaire (EQ) included automated logical flows to control the questions that were asked to respondents and a limited number of soft edits that checked for unusual values or inconsistencies.
The collected data was processed using the Social Survey Processing Environment (SSPE) that was developed at Statistics Canada. This included: i) coding of open-ended text entries to the appropriate standard classification system; ii) a series of detailed consistency edits to check for logical inconsistencies or extreme values; and iii) creating an extensive set of derived variables.
No imputation was done.
In order for estimates produced from survey data to be representative of the target population, and not just of the sample itself, users must incorporate the survey weights into their calculations. A survey weight is given to each person included in the final sample, that is, the sample of persons who responded to the survey questions. This weight corresponds to the number of persons represented by the respondent for the target population. If the frame used was perfect (covering exactly the population of interest) and all selected units were traced, contacted and completed the survey, then the design weight assigned to each unit, given by the inverse of the probability of selection of each unit in the sample, would represent accurately and exactly the number of graduates in the target population. In this situation, using this weight would yield unbiased estimates. However, this is not the case when surveys are faced with non-response and imperfect frames. Various weight adjustments techniques are available to compensate for these different issues.
It was observed that non-response did not occur randomly or uniformly within the population, since different response rates were obtained for different geographical regions or levels of certification. The chosen technique for the 2018 NGS was based on response homogeneous groups (RHGs). RHGs are developed with the premise of identifying factors that influence the likelihood to respond, and then grouping together the sample units with similar profiles as defined by these factors. Then, the weights of the non-responding units in an RHG are redistributed among the responding units in the same RHG. The factors used to define these RHGs can come from data from the frame, or from the collection process itself.
Final weights were created by calibrating the weights that were obtained after the non-response adjustment to the survey frame within post-stratification groups.
Quality assurance measures were implemented at every collection and processing step. Measures included recruitment of qualified interviewers, training provided to interviewers for specific survey concepts and procedures, procedures to ensure that coding errors were minimized, and edit quality checks to verify the processing logic. Data were verified to ensure internal consistency and were also compared to other sources when available.
Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
The survey outputs are disseminated through aggregate-level estimate tables that incorporate suitable rules to suppress estimates that do not meet minimum thresholds. The survey outputs also include a share file and a public-use microdata file, both of which incorporate suitable modifications to individual-level records and variables in order to fully protect the confidentiality of all individual-level respondent data.
Revisions and seasonal adjustment
This methodology type does not apply to this survey.
While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: sampling and non-sampling. Frame imperfection and non-response are important sources of non-sampling error.
The sample was designed to yield estimates of a minimal proportion of 5.5% with a maximum coefficient of variation (CV) of 10.47% within any stratum. There were two exceptions to this rule: all doctorate graduates and all graduates from the three territories were selected for the sample.
The response rate for the 2018 NGS was 63%.
There are many sources of non-sampling errors that are not related to sampling but may occur at almost any phase of a survey operation. Interviewers may misunderstand survey instructions, graduates may make a mistake in answering the questions, responses may be recorded in the questionnaire incorrectly, or errors may be made in the processing or tabulating of the data. For the 2018 NGS, quality assurance measures were implemented at each phase of the data collection process to monitor the quality of the data. These measures included precise interviewer training with respect to the survey procedures and questionnaire, extensive editing of respondent data, and statistical quality assurance for all automated and manual coding operations.
The survey has some under-coverage for graduates of colleges in some provinces since the data required to build the frame could not be obtained from a few institutions. Therefore, graduates from those institutions were not included on the frame and as a result could not be selected for the sample. No adjustment was made at the weighting stage to compensate for this under-coverage.