Digital video and the early learning lab
Dr Annette Henderson, Senior Lecturer, Department of Psychology
Background
The Early Learning Lab, Auckland (ELLA) is a research group in The School of Psychology at The University of Auckland devoted to better understanding infant and child development based on groups of children rather than on individuals (Fig 1). Their studies often involve playing interactive games, watching videos, solving puzzles, or discussions about actions and events they’ve observed. At ELLA the goal is to use this knowledge to give our society’s youngest members a brighter future.
Current studies include deconstructing early communication investigating the characteristics that are unique to how infants and parents communicate with one another via a digital interface; family resilience and wellbeing over a two-year time span; an ongoing longitudinal cooperation study that examines the development of prosocial behaviours (helping, sharing, and cooperating) in young children; and second language development study in early childhood and cross-cultural research. to test the effectiveness of a new language-learning tool.
Anyone interested in participating in these studies can find more information on their website – https://www.earlylearning.ac.nz/
Picture of the Lab group.
The Lab
The Early Learning lab contains a series of rooms including a warm-up room where children play a few games to build rapport and trust before a session begins. After that, a caregiver and child accompany the experimenter to one of the observation rooms where the experiment begins. These include:
- a dedicated video lab where the children are shown a sequence of different short scenes.
- A hidden video camera records each child’s response to the scenes played onscreen, measuring “looking time” – the length of attention paid to each scene.
- a multi-camera room where children play with a peer or … where behaviours and interactions are recorded
- an eye tracking room where infants watch videos (e.g. of two people interacting or cooperating) and gaze attention is measured through eye-tracker technology.
Recording and Encoding behaviour
Responses are recorded and analysed using a dedicated software programme. Working with Science Application Specialists and the Centre for eResearch, ELLA have designed a multi-video input recording system, mechanisms to analyse the behaviours and then store and share the information on local network drives and Dropbox. The lab have also worked with CeR around adopting data management practises for file storage and sharing. Initially DVD’s were created where participants requested a copy of their child’s data and posted through the mail. This information is now shared electronically using password protected private links using the university’s Dropbox enterprise system and shared only with the participants for a limited time period, saving researcher’s time and providing a simple means of access for participants.
For more information visit https://media.preziusercontent.com/converted/b/9/d/caaf3ad7327fe27c6e2d3406a70e9b15160ec.mp4
Picture of the rooms.
See more case study projects
Our Voices: using innovative techniques to collect, analyse and amplify the lived experiences of young people in Aotearoa
Painting the brain: multiplexed tissue labelling of human brain tissue to facilitate discoveries in neuroanatomy
Detecting anomalous matches in professional sports: a novel approach using advanced anomaly detection techniques
Benefits of linking routine medical records to the GUiNZ longitudinal birth cohort: Childhood injury predictors
Using a virtual machine-based machine learning algorithm to obtain comprehensive behavioural information in an in vivo Alzheimer’s disease model
Mapping livability: the “15-minute city” concept for car-dependent districts in Auckland, New Zealand
Travelling Heads – Measuring Reproducibility and Repeatability of Magnetic Resonance Imaging in Dementia
Novel Subject-Specific Method of Visualising Group Differences from Multiple DTI Metrics without Averaging
Re-assess urban spaces under COVID-19 impact: sensing Auckland social ‘hotspots’ with mobile location data
Aotearoa New Zealand’s changing coastline – Resilience to Nature’s Challenges (National Science Challenge)
Proteins under a computational microscope: designing in-silico strategies to understand and develop molecular functionalities in Life Sciences and Engineering
Coastal image classification and nalysis based on convolutional neural betworks and pattern recognition
Determinants of translation efficiency in the evolutionarily-divergent protist Trichomonas vaginalis
Measuring impact of entrepreneurship activities on students’ mindset, capabilities and entrepreneurial intentions
Using Zebra Finch data and deep learning classification to identify individual bird calls from audio recordings
Automated measurement of intracranial cerebrospinal fluid volume and outcome after endovascular thrombectomy for ischemic stroke
Using simple models to explore complex dynamics: A case study of macomona liliana (wedge-shell) and nutrient variations
Fully coupled thermo-hydro-mechanical modelling of permeability enhancement by the finite element method
Modelling dual reflux pressure swing adsorption (DR-PSA) units for gas separation in natural gas processing
Molecular phylogenetics uses genetic data to reconstruct the evolutionary history of individuals, populations or species
Wandering around the molecular landscape: embracing virtual reality as a research showcasing outreach and teaching tool