Approximating the ZPD? Young children's judgements of appropriate task level for learning

This research examined how 3-6-year-olds judge appropriate levels of counting games based on a person's ability, desire for learning and degree of difficulty. Study 1 found that 3-year-olds did not consider a character's ability or desire, whereas older children gave high ability characters large number games and low ability characters small number games when the characters wanted to play a manageable game. However, older children gave large number games to characters who wanted to learn counting, regardless of their ability. In Study 2, in addition to a similar developmental change of jointly considering a character's ability and desire, it was found that 5-and 6-year-olds were more sensitive to the degree of difficulty. They were more careful than younger children to choose exceedingly large number games given the character's ability and desire. Implications for children's understanding of the Zone of Proximal Development (ZPD) and goal orientation are discussed.

Optimizing competence in the service of collaboration

In order to efficiently divide labor with others, it is important to understand what our collaborators can do (i.e., their competence). However, competence is not static-people get better at particular jobs the more often they perform them. This plasticity of competence creates a challenge for collaboration: For example, is it better to assign tasks to whoever is most competent now, or to the person who can be trained most efficiently "on-the-job"? We conducted four experiments (N=396) that examine how people make decisions about whom to train (Experiments 1 and 3) and whom to recruit (Experiments 2 and 4) to a collaborative task, based on the simulated collaborators' starting expertise, the training opportunities available, and the goal of the task. We found that participants' decisions were best captured by a planning model that attempts to maximize the returns from collaboration while minimizing the costs of hiring and training individual collaborators. This planning model outperformed alternative models that based these decisions on the agents' current competence, or on how much agents stood to improve in a single training step, without considering whether this training would enable agents to succeed at the task in the long run. Our findings suggest that people do not recruit and train collaborators based solely on their current competence, nor solely on the opportunities for their collaborators to improve. Instead, people use an intuitive theory of competence to balance the costs of hiring and training others against the benefits to the collaboration.

Young children's adaptive partner choice in cooperation and competition contexts

Choosing adequate partners is essential for cooperation, but how children calibrate their partner choice to specific social challenges is unknown. In two experiments, 4- to 7-year-olds (N = 189, 49% girls, mostly White, data collection: 03.2021-09.2022) were presented with partners in possession of different positive qualities. Children then recruited partners for hypothetical tasks that differed with respect to the quality necessary for success. Children and the selected partner either worked together toward a common goal or competed against each other. From age 5, children selectively chose individuals in possession of task-relevant qualities as cooperative partners while avoiding them as competitors. Younger children chose partners indiscriminately. Children thus learn to strategically adjust their partner choice depending on context-specific task demands and different social goals.

The Emergence of Specialized Roles Within Groups

Humans routinely form groups to achieve goals that no individual can accomplish alone. Group coordination often brings to mind synchrony and alignment, where all individuals do the same thing (e.g., driving on the right side of the road, marching in lockstep, or playing musical instruments on a regular beat). Yet, effective coordination also typically involves differentiation, where specialized roles emerge for different members (e.g., prep stations in a kitchen or positions on an athletic team). Role specialization poses a challenge for computational models of group coordination, which have largely focused on achieving synchrony. Here, we present the CARMI framework, which characterizes role specialization processes in terms of five core features that we hope will help guide future model development: Communication, Adaptation to feedback, Repulsion, Multi-level planning, and Intention modeling. Although there are many paths to role formation, we suggest that roles emerge when each agent in a group dynamically allocates their behavior toward a shared goal to complement what they expect others to do. In other words, coordination concerns beliefs (who will do what) rather than simple actions. We describe three related experimental paradigms-"Group Binary Search," "Battles of the Exes," and "Find the Unicorn"-that we have used to study differentiation processes in the lab, each emphasizing different aspects of the CARMI framework.

Learning with certainty in childhood

Learners use certainty to guide learning. They maintain existing beliefs when certain, but seek further information when they feel uninformed. Here, we review developmental evidence that this metacognitive strategy does not require reportable processing. Uncertainty prompts nonverbal human infants and nonhuman animals to engage in strategies like seeking help, searching for additional information, or opting out. Certainty directs children's attention and active learning strategies and provides a common metric for comparing and integrating conflicting beliefs across people. We conclude that certainty is a continuous, domain-general signal of belief quality even early in life.

Mini managers: Children strategically divide cognitive labor among collaborators, but with a self-serving bias

Strategic collaboration according to the law of comparative advantage involves dividing tasks based on the relative capabilities of group members. Three experiments (N = 405, primarily White and Asian, 45% female, collected 2016-2019 in Canada) examined how this strategy develops in children when dividing cognitive labor. Children divided questions about numbers between two partners. By 7 years, children allocated difficult questions to the skilled partner (Experiment 1, d = 1.42; Experiment 2, d = 0.87). However, younger children demonstrated a self-serving bias, choosing the easiest questions for themselves. Only when engaging in a third-party collaborative task did 5-year-olds assign harder questions to the more skilled individual (Experiment 3, d = 0.55). These findings demonstrate early understanding of strategic collaboration subject to a self-serving bias.

Deciding What to Do: Developments in Children’s Spontaneous Monitoring of Cognitive Demands

How do children decide which tasks to take on? Understanding whether and when children begin to monitor cognitive demands to guide task selection is important as children gain increasing independence from adults in deciding which tasks to attempt themselves. In this article, we review evidence suggesting a developmental transition in children's consideration of cognitive demands when making choices about tasks: Although younger children are capable of monitoring cognitive demands to guide task selection, spontaneous monitoring of cognitive demands begins to emerge around 5-7 years. We describe frameworks for understanding when and why children begin to monitor cognitive demands, and propose additional factors that likely influence children's decisions to pursue or avoid cognitively demanding tasks.

Young children consider the expected utility of others' learning to decide what to teach

Direct instruction facilitates learning without the costs of exploration, yet teachers must be selective because not everything can nor needs to be taught. How do we decide what to teach and what to leave for learners to discover? Here we investigate the cognitive underpinnings of the human ability to prioritize what to teach. We present a computational model that decides what to teach by maximizing the learner's expected utility of learning from instruction and from exploration, and we show that children (aged 5-7 years) make decisions that are consistent with the model's predictions (that is, minimizing the learner's costs and maximizing the rewards). Children flexibly considered either the learner's utility or their own, depending on the context, and even considered costs they had not personally experienced, to decide what to teach. These results suggest that utility-based reasoning may play an important role in curating cultural knowledge by supporting selective transmission of high-utility information.