How might we organize the volume of quality documents that contain data during the pandemic years 2020 and 2021 into a digital format for analysis and identify the units of analysis based on the seminal resources associated with ELCC quality (e.g., HDLH) to provide evidence to inform planning and decision-making for Canada-Wide ELCC?
Context:
Hamilton’s Early Learning and Child Care (ELCC) is historically shifting to a universal service model. Canada-wide ELCC is anticipated to result in service system expansion related to affordable child care for eligible children. Increases in service operators and demands for service from families with children 0-6 years of age is expected. The Hamilton ELCC Quality Program supports operators who have funding agreements with the City. The Quality Program was maintained throughout the COVID-19 pandemic with primary data collection that requires analysis to inform the future. Evidence-informed planning and decision-making to support managing and maintaining continuity in Hamilton’s high-quality ELCC service delivery is a priority over the next year.
Problem:
Determine how Hamilton’s past quality priorities will inform priorities in the future with expected service expansion and service demands. A repository of data from 2020 and 2021 requires additional support to expand the City’s capacity with managing and analysing the volume of data that was collected during the pandemic.
Objectives:
Organize documents into a digital data format
Determine units of analysis based on seminal resources
Analyse the data including reliability/validation controls
Generate data output
Present key findings
Generate a report
Student Team: Daniel Buckler, Andrew Davies, Kevin Estriga, Josh Hidalgo, Joanne Kim, Hayley Koens, Eric Meandro, Cassandra Roque, Hrithik Sharma, Ryan Van Hoesel and Dania Wood
Faculty & Course: Emily Scherzinger, PHD, McMaster University, Social Entrepreneurship Capstone - IBH 4AB6
City Staff: Marion Trent-Kratz, Early Years Senior Research Advisor, Healthy and Safe Communities
