Evidence for systematicity in infant and toddler curiosity-driven object exploration 2017-2018

Twomey, Katherine and Ke, Han and Westermann, Gert (2020). Evidence for systematicity in infant and toddler curiosity-driven object exploration 2017-2018. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-853717

As parents know, babies are curious learners. The vast majority of infants' time is spent freely exploring (Oudeyer and Smith, in press), at home, at nursery or at playgroup. By sampling their learning environment based on their own curiosity infants quickly acquire two fundamental components of cognition without which they would never engage effectively with the world: categories and words. Understanding early category learning and how it interacts with word learning is therefore critical to teasing apart the complex processes by which infant cognition develops into an adult-like understanding of the world. However, although curiosity-driven exploration accounts for almost all of infants' experience, our understanding of category and word learning comes almost entirely from tightly-controlled, highly structured experiments. Decades of elegantly-designed studies show that these interacting phenomena are exquisitely sensitive to features of the environment (e.g., Younger, 1983; Plunkett, Hu and Cohen, 2008; Quinn, Eimas and Rosenkrantz, 1993). Because these experiments typically take place in artificial laboratory conditions, however, we do not know how babies themselves choose to learn, and as a consequence, we do not know the best way to help them do so.
Here I propose the first studies of infants' curiosity-based exploration and word learning. Using cutting-edge head-mounted eyetrackers I will record typically-developing infants interacting freely with objects, generating the first detailed description of curiosity-based exploration and laying the foundation for future research in atypical exploration. Objects will be custom-designed to vary systematically (e.g., in shape), allowing me to record exploratory sequences to reveal what level of complexity infants prefer to learn from. Half the infants will hear labels for the objects and be tested on their word learning, revealing how categorisation and word learning interact in an infant-centred, rather than adult-designed, environment.
For a complete understanding of infants' exploration, however, we not only need to know what infants do, but also how they do it: what mechanisms drive curiosity? Computational models can clarify the cognitive processes underlying a behaviour (McClelland et al., 2010). However, as yet we have no model of infants' curiosity-driven exploration and word learning. Based on my existing modelling work (Twomey and Westermann, 2015), I will develop the first testable, mechanistic theory of curiosity-based exploration and word learning in infants.
As the first investigation of human infants' curiosity-driven category and word learning this research has clear academic impact (papers, conferences, future studies of atypical exploration, collaborations). It also has societal impact: my findings will inform policymakers' understanding of development, help designers create evidence-based books and toys that facilitate learning, and equip parents and early years practitioners with the knowledge they need to support babies' cognitive development. There will be numerous opportunities to build networks and develop my knowledge exchange skills (e.g., data sharing, publications, conferences, talks) and public engagement experience (e.g., writing news articles, organising public engagement events).

Data description (abstract)

The overall goal of this award was to understand how babies learn when allowed to explore their environment based on their own curiosity, outside the constrained experimental setting typical of most research in early cognitive development. We were also interested in how this curiosity-based exploration might be influenced by language. This goal was approached in two ways: first using computational modelling to examine the potential learning mechanisms involved in curiosity; and second, experimentally, to develop a picture of what babies and toddlers do when engaged in curiosity-driven learning. In our computational work we developed the first model of babies curiosity-driven learning inspired by the mechanisms known to exist in the human brain. This model predicted that when allowed to freely choose what to learn from and when, young children should learn best from an environment which is neither too simple nor too complex; that is, medium difficulty should best support learning, and importantly, children should be able to generate this level of difficulty themselves without adults structuring their learning environment on their behalf.
Our empirical work aimed to test the predictions from the model. In Study 1 we showed 12- and 28-month-old toddlers 2D image and recorded where they looked and for how long. Both groups of children generated patterns of looking which were of intermediate complexity (Twomey, Malem, Ke & Westermann, in prep.). In Study 2, we allowed 12-, 18- and 24-month-old infants to play freely with custom-designed, 3D printed categories of novel objects. Again, children of all ages generated explored the objects in an order which led to medium complexity (Ke, Westermann & Twomey, in prep[a]). This study also generated a video dataset from the 12-month-old participants showing their field of view (Ke, Westermann & Twomey, in prep[b]). This dataset will allow us to conduct fine-grained analyses of their how young children visually explore the object they’re playing with, linking the findings from Studies 1 and 2. Overall the empirical data support the predictions of the model, providing the first evidence that not only do infants learn best from intermediate difficulty input, but critically also that they are capable of generating this level of difficulty independently. Put differently, rather than passive learners or random explorers, infants are active learners who are capable of independently tailoring their learning environment in a way that best supports their own development.

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