How to Help Young Children Ask Better Questions?

The Efficiency of Question-Asking Strategies in a Real-World Visual Search Task

In recent years, a multitude of datasets of human-human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on human behavior and language use. We present a method that leverages the recent development of powerful computational models to obtain the fine-grained annotation required to apply metrics and techniques from Cognitive Science to large datasets. Previous work in Cognitive Science has investigated the question-asking strategies of human participants by employing different variants of the so-called 20-question-game setting and proposing several evaluation methods. In our work, we focus on GuessWhat, a task proposed within the Computer Vision and Natural Language Processing communities that is similar in structure to the 20-question-game setting. Crucially, the GuessWhat dataset contains tens of thousands of dialogues based on real-world images, making it a suitable setting to investigate the question-asking strategies of human players on a large scale and in a natural setting. Our results demonstrate the effectiveness of computational tools to automatically code how the hypothesis space changes throughout the dialogue in complex visual scenes. On the one hand, we confirm findings from previous work on smaller and more controlled settings. On the other hand, our analyses allow us to highlight the presence of "uninformative" questions (in terms of Expected Information Gain) at specific rounds of the dialogue. We hypothesize that these questions fulfill pragmatic constraints that are exploited by human players to solve visual tasks in complex scenes successfully. Our work illustrates a method that brings together efforts and findings from different disciplines to gain a better understanding of human question-asking strategies on large-scale datasets, while at the same time posing new questions about the development of conversational systems.

Preschoolers' information search strategies: Inefficient but adaptive

Although children's sensitivity to others' informativeness emerges early in life, their active information search becomes robustly efficient only around age 10. Young children's difficulty in asking efficient questions has often been hypothesized to be linked to their developing verbal competence and growing vocabulary. In this paper, we offer for the first time a quantitative analysis of 4- to 6-year-old children's information search competence by using a non-verbal version of the 20-questions game, to gain a more comprehensive and fair picture of their active learning abilities. Our results show that, even in this version, preschoolers performed worse than simulated random agents, requiring more queries to reach the solution. However, crucially, preschoolers performed better than the simulated random agents when isolating the extra, unnecessary queries, which are made after only one hypothesis is left. When additionally isolating all the unnecessary queries, children's performance looked on par with that of the simulated optimal agents. Our study replicates and enriches previous research, showing an increase in efficiency across the preschool-aged years, but also a general lack of optimality that seems to be fundamentally driven by children's strong tendency to make unnecessary queries, rather than by their verbal immaturity. We discuss how children's non-optimal, conservative information-search strategies may be adaptive, after all.

Children's failure to control variables may reflect adaptive decision-making

Changing one variable at a time while controlling others is a key aspect of scientific experimentation and a central component of STEM curricula. However, children reportedly struggle to learn and implement this strategy. Why do children's intuitions about how best to intervene on a causal system conflict with scientific practices? Mathematical analyses have shown that controlling variables is not always the most efficient learning strategy, and that its effectiveness depends on the "causal sparsity" of the problem, i.e., how many variables are likely to impact the outcome. We tested the degree to which 7- to 13-year-old children (n = 104) adapt their learning strategies based on expectations about causal sparsity. We report new evidence demonstrating that some previous work may have undersold children's causal learning skills: Children can perform and interpret controlled experiments, are sensitive to causal sparsity, and use this information to tailor their testing strategies, demonstrating adaptive decision-making.

An Introduction to Ecological Active Learning

This article introduces ecological active learning, a developmental framework that focuses on children’s ability to adapt and tailor their active-learning strategies to the particular structure and characteristics of a learning environment. Results of seminal studies indicate that efficient, adaptive search strategies emerge around 3 years of age, much earlier than previously assumed. This work highlights the importance of developing age-appropriate paradigms that capture children’s early competence to gain a more comprehensive and fair picture of their active-learning abilities. Also, it offers a process-oriented theoretical framework that can accommodate and reconcile a sparse but growing body of work documenting children’s active and adaptive learning. Three of the most promising avenues for future research on children’s ecological active learning are discussed.

Children’s Physical Gender Schemas: Acquisition and Features

Studies on how physical gender schemas develop in children have traditionally utilized forced-choice and close-ended tasks, finding that the ability to make gender-related distinctions develops in the first years of a child’s life. To reduce demand characteristics that reinforce gender binaries in children’s models of gender, we relied on open-ended discourse analysis to study children’s physical gender schemas. We focused on whether children’s ability to ask questions that distinguish gender groups was greater in older than younger children. Participants were 44 3–4-year-olds, 35 5–6-year-olds, and 23 7–8-year-old children in the U.K. who were led through a guessing game to elicit gender-related beliefs and compare their beliefs about gender to their beliefs about other entities such as living things. When asking questions to distinguish gender binary groups, older children judging gendered individuals were more likely to ask questions that stereotypically distinguished the gender groups than younger children. Older children were also more likely to focus on individuals’ biological properties, clothing, and hair length than were younger children. Thus, the development of a child’s understanding of physical gender schemas gender is discrete, developing gradually at least until the age of 8.

“What makes this a wug?” Relations among children’s question asking, memory, and categorization of objects

Children ask many questions, but do not always receive answers to the questions they ask. We were interested in whether the act of generating questions, in the absence of an answer, is related to children’s later thinking. Two experiments examined whether children retain the questions they ask in working memory, and whether the type of questions asked relate to their categorization. Four to ten-year-old children (N = 42 in Experiment 1, N = 41 in Experiment 2) were shown 12 novel objects, asked three questions about each, and did not receive answers to their questions. Children recalled their questions in the first experiment and categorized variants of the novel objects in the second experiment. We found that children have robust working memory for their questions, indicating that these questions may relate to their subsequent thinking. Additionally, children generalize category boundaries more narrowly or broadly depending on the type of question they ask, indicating that children’s questions may reflect an underlying bias in how they think about the world. These findings suggest that future research should examine questions in the absence of answers to understand how inquiry affects children’s cognitive development.