Challenges and Opportunities Related to Child Well-Being Data and Indicators I

Friday, 11 July 2025: 09:00-10:45
Location: FSE007 (Faculty of Education Sciences (FSE))
RC55 Social Indicators (host committee)

Language: English

Despite recent progress, major efforts are needed to improve child well-being data and indicators. For example, policymakers need the data to design, implement and monitor effective child well-being policies. However, mostly countries do not have good data on which to base their child well-being policies or a strong data infrastructure to monitor these policies. For the first time, children will be considered in OECD’s new guidelines on how to measure subjective well-being. This session calls for papers addressing different challenges and opportunities related to child well-being data and indicators. Challenges can be related, but not only, with data collection from children in general, including ethical and data protection issues; development of new child indicators; data collection specifically from more vulnerable children (e.g. children under 7-years-old, in disability, migrant background, not living with biological parent(s)) and development of objective/subjective indicators for these groups; child well-being data fragmentation and difficulties in their use. Opportunities can be related, but not only, with new ways to collect data from and about children; development and use of international, national and/or sub-national cross-sectoral child well-being monitoring systems and indicator sets; the accessibility and usability increase of child well-being data and indicators through data portals, dashboards etc. Theoretical, empirical and also discussion papers are welcome.
Session Organizer:
Oliver NAHKUR, University of Tartu, Estonia
Chair:
Kristi ASSER, University of Tartu, Estonia
Oral Presentations
Are Self-Reported Measures of Well-Being Reliable and Valid?
Haridhan GOSWAMI, Manchester Metropolitan University, United Kingdom; M. Ibrahim KHALIL, Government Brojomohan College, Bangladesh
A Machine Learning and Life-Course Approach to Protecting Student Trajectories
Patricio RODRÍGUEZ, CIAE/IE - Universidad de Chile, Chile; Alexis VILLANUEVA VILLANUEVA, Chile; Claudio ALLENDE, Universidad de Chile, Chile; Francisco Javier MENESES RIVAS, Universidad de Chile, Chile; Juan Pablo VALENZUELA, Universidad de Chile, Chile
See more of: RC55 Social Indicators
See more of: Research Committees