Learning by thinking and the development of abstract reasoning
- Author(s): Walker, Caren Michelle;
- Advisor(s): Gopnik, Alison;
- Lombrozo, Tania
- et al.
As adults, we have coherent, abstract, and highly structured causal representations of the world. We also learn those representations, as children, from the fragmented, concrete and particular evidence of our senses. How do young children learn so much about the world so quickly and accurately? One classic answer points to the similarities between children’s learning and scientific learning. In particular, researchers have proposed that children, like scientists, implicitly formulate hypotheses about the world and then use evidence to test and rationally revise those hypotheses. In testing these claims, the vast majority of research in this area has investigated children’s developing abilities to draw causal inferences from observed data. However, we know much less about the human ability to build abstract knowledge that extends beyond their observations, simply by thinking. In the current dissertation, I examine a suite of activities that involve learning by thinking in the causal domain, and consider how these activities impose unique, top-down constraints on the processes underlying causal learning and inductive inference. First, in chapter 1, I situate this work within the theoretical context of rational constructivism that has recently emerged in the field of cognitive development. Chapter 2 then presents a series of experiments demonstrating very young children’s ability to infer the abstract relations “same” and “different” in a novel causal reasoning task. I conclude this chapter by considering the implications of these findings for our understanding of the nature of relational and causal reasoning, and their evolutionary origins. Chapter 3 extends this paradigm to describe a surprising developmental pattern: younger children outperform older children in inferring these abstract relations. I provide evidence that this failure may be explained by appealing to the role of learned biases in constraining causal judgments. The second part of this chapter explores how prompts to explain during learning facilitate children’s ability to override a preference to attend to object properties, and instead reason about abstract relations. Chapter 4 presents empirical findings further examining the particular effects of explanation on the mechanisms underlying causal inference in preschool-aged children. In particular, results demonstrate that explanation prompts children to ignore salient superficial properties and consider inductively rich properties that are likely to generalize to novel cases. Finally, in Chapter 5, I discuss the implications for this body of work as a whole, and suggest a variety of future directions. Taken together, this research contributes to our understanding of the cognitive processes that influence early learning and inference in early childhood.