Nicola Cutting

Making tools isn’t child’s play

Tool making evidences intelligent, flexible thinking. In Experiment 1, we confirmed that 4- to 7-year-olds chose a hook tool to retrieve a bucket from a tube. In Experiment 2, 3- to 5-year-olds consistently failed to innovate a simple hook tool. Eight-year-olds performed at mature levels. In contrast, making a tool following demonstration was easy for even the youngest children. In Experiment 3, childrens performance did not improve given the opportunity to manipulate the objects in a warm-up phase. Childrens tool innovation lags substantially behind their ability to learn how to make tools by observing others.

The puzzling difficulty of tool innovation: Why can't children piece their knowledge together?

Tool innovation-designing and making novel tools to solve tasks-is extremely difficult for young children. To discover why this might be, we highlighted different aspects of tool making to children aged 4 to 6 years (N=110). Older children successfully innovated the means to make a hook after seeing the pre-made target tool only if they had a chance to manipulate the materials during a warm-up. Older children who had not manipulated the materials and all younger children performed at floor. We conclude that childrens difficulty is likely to be due to the ill-structured nature of tool innovation problems, in which components of a solution must be retrieved and coordinated. Older children struggled to bring to mind components of the solution but could coordinate them, whereas younger children could not coordinate components even when explicitly provided.

The development of tool manufacture in humans: what helps young children make innovative tools?

We know that even young children are proficient tool users, but until recently, little was known about how they make tools. Here, we will explore the concepts underlying tool making, and the kinds of information and putative cognitive abilities required for children to manufacture novel tools. We will review the evidence for novel tool manufacture from the comparative literature and present a growing body of data from children suggesting that innovation of the solution to a problem by making a tool is a much more challenging task than previously thought. Childrens difficulty with these kinds of tasks does not seem to be explained by perseveration with unmodified tools, difficulty with switching to alternative strategies, task pragmatics or issues with permission. Rather, making novel tools (without having seen an example of the required tool within the context of the task) appears to be hard, because it is an example of an ‘ill-structured problem’. In this type of ill-structured problem, the starting conditions and end goal are known, but the transformations and/or actions required to get from one to the other are not specified. We will discuss the implications of these findings for understanding the development of problem-solving in humans and other animals.

Individual differences in children's innovative problem-solving are not predicted by divergent thinking or executive functions

Recent studies of childrens tool innovation have revealed that there is variation in childrens success in middle-childhood. In two individual differences studies, we sought to identify personal characteristics that might predict success on an innovation task. In Study 1, we found that although measures of divergent thinking were related to each other they did not predict innovation success. In Study 2, we measured executive functioning including: inhibition, working memory, attentional flexibility and ill-structured problem-solving. None of these measures predicted innovation, but, innovation was predicted by childrens performance on a receptive vocabulary scale that may function as a proxy for general intelligence. We did not find evidence that childrens innovation was predicted by specific personal characteristics.

Tool innovation may be a critical limiting step for the establishment of a rich tool-using culture: a perspective from child development.

Recent data show that human children (up to 8 years old) perform poorly when required to innovate tools. Our tool-rich culture may be more reliant on social learning and more limited by domain-general constraints such as ill-structured problem solving than otherwise thought.

Is tool-making knowledge robust over time and across problems?

In three studies, we explored the retention and transfer of tool-making knowledge, learnt from an adult demonstration, to other temporal and task contexts. All studies used a variation of a task in which children had to make a hook tool to retrieve a bucket from a tall transparent tube. Children who failed to innovate the hook tool independently saw a demonstration. In Study 1, we tested children aged 4–6 years (N = 53) who had seen the original demonstration 3 months earlier. Performance was excellent at the second time, indicating that children’s knowledge was retained over the 3 month period. In Studies 2 and 3 we explored transfer of the new knowledge to other tasks. In Study 2, children were given two variants of the apparatus that differed in surface characteristics (e.g., shape and color). Participants generalized their knowledge to these new apparatuses even though the new pipecleaner also differed in size and color. Five- to 6-year-olds (N = 22) almost always transferred their knowledge to problems where the same tool had to be made. Younger, 3- to 5-year-olds’ (N = 46), performance was more variable. In Study 3, 4- to 7-year-olds (N = 146) saw a demonstration of hook making with a pipecleaner, but then had to make a tool by combining pieces of wooden dowel (or vice versa: original training on dowel, transfer to pipecleaner). Children did not transfer their tool-making knowledge to the new material. Children retained tool-making knowledge over time and transferred their knowledge to new situations in which they needed to make a similar tool from similar materials, but not different materials. We concluded that children’s ability to use tool-making knowledge in novel situations is likely to depend on memory and analogical reasoning, with the latter continuing to develop during middle childhood.

Minding the Gap: A Comparative Approach to Studying the Development of Innovation

We often encounter problems in which our usual learned solutions are ineffective. In such situations, we may know what problem we face, and what we want to achieve, but we must generate new behavior to bridge the gap between the current situation and the desired result. In this chapter, we discuss why this process of innovation is important for humans and non-human animals, both when adapting to novel environments and for cultural transmission. We then review evidence for innovation from the comparative literature before discussing the kinds of conditions and attributes that may be required by successful innovators, such as physical cognition, causal reasoning, planning, sequencing actions and inhibitory control. Finally, we consider whether viewing innovation as part of a class of ‘ill-structured problems’ (in which the information required to solve them is missing) provides a useful framework for thinking about and testing innovation.

The effect of prior experience on children’s tool innovation

Spontaneous tool innovation to solve physical problems is difficult for young children. In three studies, we explored the effect of prior experience with tools on tool innovation in children aged 4-7years (N=299). We also gave children an experience more consistent with that experienced by corvids in similar studies to enable fairer cross-species comparisons. Children who had the opportunity to use a premade target tool in the task context during a warm-up phase were significantly more likely to innovate a tool to solve the problem on the test trial compared with children who had no such warm-up experience. Older children benefited from either using or merely seeing a premade target tool prior to a test trial requiring innovation. Younger children were helped by using a premade target tool. Seeing the tool helped younger children in some conditions. We conclude that spontaneous innovation of tools to solve physical problems is difficult for children. However, children from 4years of age can innovate the means to solve the problem when they have had experience with the solution (visual or haptic exploration). Directions for future research are discussed.

Chapter 10 – Minding the Gap: A Comparative Approach to Studying the Development of Innovation

We often encounter problems in which our usual learned solutions are ineffective. In such situations, we may know what problem we face, and what we want to achieve, but we must generate new behavior to bridge the gap between the current situation and the desired result. In this chapter, we discuss why this process of innovation is important for humans and non-human animals, both when adapting to novel environments and for cultural transmission. We then review evidence for innovation from the comparative literature before discussing the kinds of conditions and attributes that may be required by successful innovators, such as physical cognition, causal reasoning, planning, sequencing actions and inhibitory control. Finally, we consider whether viewing innovation as part of a class of ‘ill-structured problems’ (in which the information required to solve them is missing) provides a useful framework for thinking about and testing innovation.