BOLD Talks: Possibilities and implications of sensor data

Start date
End date
University of Leiden, Faculty of Social and Behavioral Sciences (Wassenaarseweg 52, 2333 AK Leiden), room 5A37

BOLD Talks



BOLD Talks: Possibilities and implications of sensor data 
By dr. Daniel Messinger (University Miami) and dr. Ed Baines (UCL)


11:30-12:15 – Presentation: School break and lunch times and young people's social lives in England: Results from 3 national surveys between 1995 and 2017 by Ed Baines (UCL)
12:15-13:00 – Presentation: Social Interaction in Context by Daniel Messinger (University of Miami)
14:00-16:00: Plenary Discussion

Ed Baines (UCL)
Title: School break and lunch times and young people's social lives in England: Results from 3 national surveys between 1995 and 2017

Abstract. School breaktimes are important social play settings for children and young people. In the past decade there have been changes to schools and education in England. However little recent data is available about children’s social lives in school over this period. Following similar surveys in 1995 and 2006, the Nuffield Foundation funded Breaktime and Social life in Schools (BaSiS) project reports on a national survey undertaken in 2017 of school breaktimes, children’s views on school breaks and their social lives in and outside of school. The BaSiS survey provides a snapshot of school life in relation to breaktimes in 2017 as well as insights into changes since 1995 and 2006. This presentation will report on findings from this project and select early findings from an international survey of school breaks.

Dr. Ed Baines is a senior Lecturer in Psychology and Education. He is a experienced researcher involved in a number of research projects focusing on teaching, learning and group work in classrooms; peer relations, friendships and social networks in school; school lunch and break times; peer interaction and dialogue in classroom contexts.


Daniel Messinger (University of Miami)
Title: Social Interaction in Context

Abstract.  Much early development occurs in the context of unstructured social interaction. New sensing technologies, combined with machine learning, may provide insight into the development of typically developing children and those with communication disorders such as autism and deafness. Automated detection of smiling and vocal turn-taking is shedding light on the diagnosis of autism. Automated analysis of classroom movement and vocal interaction is suggesting how language development occurs among peers. The talk will consider the strengths, challenges, and future of objective measurement and modeling of child behavior.  

Prof. Messinger investigates the temporal dynamics of communication to understand how infants and children develop in social relationships. His focus is social, emotional, and language development. Dr. Messinger is a behavioral imager who uses computer vision and other forms of machine learning to objectively measure what children do. He uses computational approaches including time-series analysis and network models to make sense of the big behavioral data that objective measures provide.  His current work focuses on children with communication disorders. He conducts research with children affected by autism spectrum disorder (ASD) and children with hearing loss. By understanding interaction, Dr. Messinger fosters pathways to healthy development. Specific projects include the emergence of secure attachment, sex differences in the development of autism, and language networks in inclusive classrooms.

Date & Place 
Tuesday 9 April, 11:30 - 13:00 (till 16:00 is optional
University of Leiden
Faculty of Social and Behavioral Sciences a
Wassenaarseweg 52, 2333 AK Leiden
Room 5A37