An Integrated Real-Time Approach to the Development of Human Problem Solving

Problem solving is ubiquitous across every age and culture-how to navigate a cluttered environment, use a tool, and so on. As our bodies, skills, and environments change, new problems emerge and require new means to solve them. Solvers cannot perform the same habitual actions over and over by rote because real-world environments are variable, unpredictable, and full of novel situations. The overarching goal of the proposed project is to understand (and intervene on) processes that underlie the development of human problem-solving skills.

Traditionally, developmental research takes a normative, outcome-oriented approach by identifying the ages at which children succeed in solving various problems. This outcome-oriented approach established that motor problem solving begins in infancy and improves with age and experience. Yet, critical knowledge gaps exist: how do perception, cognition, and action unfold from moment to moment to enable efficient solutions? What experiences facilitate early motor problem-solving skills? And does motor problem-solving at a younger age predict subsequent high-order cognitive skills?

To answer these questions, we adopt a unique integrative approach combining perspectives and methods from developmental psychology, neuroscience, artificial intelligence, electrical engineering, and motor control. Our guiding hypothesis is that the variability in children's daily flux of a changing body in a variable world facilitates motor problem-solving skills by calibrating a real-time interactive system of perceptual, neural, and motor processes, which in turn facilitates subsequent cognitive skills.

We will test this hypothesis in a longitudinal study by using object manipulation as a model system. Aim 1 of the proposed research will determine how children's efficiency, flexibility, stability, and generalisability during problem solving rely on the timing of real-time cascade - from gathering information about the task, to neural differentiation of task-relevant information, to the recruitment of relevant muscles, and finally movement execution. Aim 2 will manipulate the variety of children's everyday experiences during object play in their home, quantify it across one year using unique custom-built toys, and determine the contribution of early variable experiences to subsequent problem-solving skills. Aim 3 will assess the developmental relations between motor problem-solving skills and subsequent high-order cognitive skills, including reasoning, planning, and executive functioning.

By uncovering the origins of motor problem solving, the proposed work has broad implications for understanding foundational learning-related processes such as planning, organisation, attention, behavioural flexibility, executive function, and self-regulation. Identifying factors that promote problem solving can support practices, programs, and policies to improve children's outcomes and make them reach their full potential, whatever their background, family income, or place of living. Moreover, this work will provide insights into how individuals solve the problem in real-time and thereby distinguish whether causes of deficits result from lack of perceptual information, neural processing, and/or motor dexterity. Thus, findings may have translational implications for understanding disorders related to deficits in problem solving and may support educational interventions. By knowing the source of deficit in individuals, interventions can be tailored to their specific needs.

Finally, the proposed work will advance international research on learning and development through open sharing of rich data, methods (experimental protocols, machine-learning algorithms, analysis scripts), findings (videos, physiological data), and engineering protocols (intelligent toys) in established repositories. The proposed project promises to pave the way for research in STEM and other disciplines to explain and promote children's outcomes.