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Exploring an Automatic Enrolment Model for the Canada Learning Bond

Format: Papers, RSD12, Topic: Learning & Education

Anastasia Chebakova, Sonia Chwalek, Flynn Gottselig, Nadiya Safonova, and Megan Strazds-Esenbergs

Developing an automatic enrolment model for the Canada Learning Bond (CLB) would streamline access to education savings and support early aspirations for post-secondary education for children in families with low income in Canada. The current rules around accessing CLB present significant barriers to families with low income and can prevent them from receiving the financial support for which they are eligible. This is reflected by staggering statistics indicating that 2.25 million children in Canada, nearly 60% of the eligible population, are not enrolled in the program (Government of Canada, Office of the Auditor General, 2022).

Families with low income often struggle to contribute the additional time, effort, cognitive and financial resources to access the CLB. This may decrease the likelihood that children attend post-secondary education. This is a significant concern because post-secondary education has the potential to help break the cycle of poverty for many families (Elliott, 2018). Over the years, communities of stakeholders have called for an automatic enrolment model for the CLB to address persistent barriers to access and low uptake of the CLB. An automatic enrolment model is an innovative and novel approach to benefit delivery that is currently being explored internationally. Automatic enrolment models commonly achieve near full enrolment. In response, this project explored the potential of using an automatic enrolment model. The project maximised the feasibility of this innovative approach by engaging community organisations and Canadians in designing the model’s core elements.

KEYWORDS: education savings, access to post-secondary education, automatic enrolment, education aspirations, families with low income, design

RSD TOPIC: Learning & Education

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Citation Data

Author(s): Anastasia Chebakova, Sonia Chwalek, Flynn Gottselig, Nadiya Safonova, and Megan Strazds-Esenbergs
Year: 2023
Title: Exploring an Automatic Enrolment Model for the Canada Learning Bond
Published in: Proceedings of Relating Systems Thinking and Design
Volume: RSD12
Article No.: pre-release
URL: https://rsdsymposium.org/canada-learning-bond-model
Host: Georgetown University
Location: Washington DC, USA
Symposium Dates: October 6–20, 2023
First published: 30 September 2023
Last update: no update
Publisher Identification: ISSN 2371-8404
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