Contemporary debates about the nature of semantic reference have tended to focus on two competing approaches: theories which emphasize the importance of descriptive information associated with a referring term, and those which emphasize causal facts about the conditions under which the use of the term originated and was passed on. Recent empirical work by Machery and colleagues suggests that both causal and descriptive information can play a role in judgments about the reference of proper names, with findings of cross-cultural variation in judgments that imply differences between individuals with respect to whether they favor causal or descriptive information in making reference judgments. We extend this theoretical and empirical line of inquiry to views of the reference of natural and nominal kind concepts, which face similar challenges to those concerning the reference of proper names. In two experiments, we find evidence that both descriptive and causal factors contribute to judgments of concept reference, with no reliable differences between natural and nominal kinds. Moreover, we find evidence that the same individuals’ judgments can rely on both descriptive and causal information, such that variation between individuals cannot be explained by appeal to a mixed population of “pure descriptive theorists” and “pure causal theorists.” These findings suggest that the contrast between descriptive and causal theories of reference may be inappropriate; intuitions may instead support a hybrid theory of reference that includes both causal and descriptive factors. We propose that future research should focus on the relationship between these factors, and describe several possible frameworks for pursuing these issues. Our findings have implications for theories of semantic reference, as well as for theories of conceptual structure.
Wrong or merely prohibited: Special treatment of strict liability in intuitive moral judgment. Law and Human Behavior , 40 (6), 707-720.Abstract(2016).
Most crimes in America require that the defendant have mens rea, Latin for "guilty mind." However, mens rea is not legally required for strict liability crimes, such as speeding, for which someone is guilty even if ignorant or deceived about her speed. In 3 experiments involving participants responding to descriptive vignettes, we investigated whether the division of strict liability crimes in the law reflects an aspect of laypeople's intuitive moral cognition. Experiment 1 (N = 396; 236 male, 159 female, 1 other; M = 30) found evidence that it does: ignorance and deception were less mitigating for strict liability crimes than for "mens rea" crimes. Experiments 2 (N = 413; 257 male, 154 female, 2 other; M = 31) and 3 (N = 404; 183 male, 221 female, M = 35) revealed that strict liability crimes are not treated as pure moral violations, but additionally as violations of convention. We found that for strict liability crimes, ratings of moral wrongness and punishment were influenced to a greater extent by the fact that a rule had been violated, even when harm was kept constant, mirroring the legal distinction of malum prohibitum (wrong as prohibited) versus malum in se (wrong in itself). Further, we found that rules prohibiting strict liability crimes were judged more arbitrary than corresponding rules for "mens rea" crimes, and that this judgment was related to the role of mental states. Jointly, the findings suggest a surprising correspondence between the law and laypeople's intuitive judgments. (PsycINFO Database Record
Explanatory preferences shape learning and inference. Trends in Cognitive Sciences , 20 (10), 748-759. https://doi.org/10.1016/j.tics.2016.08.001Abstract(2016).
Explanations play an important role in learning and inference. People often learn by seeking explanations, and they assess the viability of hypotheses by considering how well they explain the data. An emerging body of work reveals that both children and adults have strong and systematic intuitions about what constitutes a good explanation, and that these explanatory preferences have a systematic impact on explanation-based processes. In particular, people favor explanations that are simple and broad, with the consequence that engaging in explanation can shape learning and inference by leading people to seek patterns and favor hypotheses that support broad and simple explanations. Given the prevalence of explanation in everyday cognition, understanding explanation is therefore crucial to understanding learning and inference.
Sources of developmental change in the efficiency of information search. Developmental Psychology , 52 (12), 2159-2173. http://dx.doi.org/10.1037/dev0000240Abstract(2016).
Children are active learners: they learn not only from the information people offer and the evidence they happen to observe, but by actively seeking information. However, children's information search strategies are typically less efficient than those of adults. In two studies, we isolate potential sources of developmental change in how children (7- and 10-year-olds) and adults search for information. To do so, we develop a hierarchical version of the 20-questions game, in which participants either ask questions (Study 1) or test individual objects (Study 2) to discover which category of objects within a nested structure (e.g., animals, birds, or owls) has a novel property. We also develop a computational model of the task, which allows us to evaluate performance in quantitative terms. As expected, we find developmental improvement in the efficiency of information search. In addition, we show that participants' performance exceeds random search, but falls short of optimal performance. We find mixed support for the idea that children's inefficiency stems from difficulty thinking beyond the level of individual objects or hypotheses. Instead, we reveal a previously undocumented source of developmental change: Children are significantly more likely than adults to continue their search for information beyond the point at which a single hypothesis remains, and thus to ask questions and select objects associated with zero information gain. This suggests that one crucial source of developmental change in information search efficiency lies in children's "stopping rules." (PsycINFO Database Record
Depth and deference: When and why we attribute understanding. Philosophical studies , 173 (2), 373–393 . Springer. https://doi.org/10.1007/s11098-015-0497-yAbstract(2016).
Four experiments investigate the folk concept of ‘‘understanding,’’ in particular when and why it is deployed differently from the concept of knowledge. We argue for the positions that (1) people have higher demands with respect to explanatory depth when it comes to attributing understanding, and (2) that this is true, in part, because understanding attributions play a functional role in identifying experts who should be heeded with respect to the general field in question. These claims are supported by our findings that people differentially withhold attributions of understanding (rather than knowledge) when the object of attribution has minimal explanatory information. We also show that this tendency significantly correlates with people’s willingness to defer to others as potential experts. This work bears on a pressing issue in epistemology concerning the place and value of understanding. Our results also provide reason against positing a simple equation of knowledge(- why) and understanding(-why). We contend that, because deference plays a crucial role in many aspects of everyday reasoning, the fact that we use understanding attributions to demarcate experts reveals a potential mechanism for achieving our epistemic aims in many domains.
Children adapt their questions to achieve efficient search. Cognition , 143, 203-216. https://doi.org/10.1016/j.cognition.2015.07.004Abstract(2015).
One way to learn about the world is by asking questions. We investigate how younger children (7- to 8-year-olds), older children (9- to 11-year-olds), and young adults (17- to 18-year-olds) ask questions to identify the cause of an event. We find a developmental shift in children's reliance on hypothesis-scanning questions (which test hypotheses directly) versus constraint-seeking questions (which reduce the space of hypotheses), but also that all age groups ask more constraint-seeking questions when hypothesis-scanning questions are least likely to pay off: When the solution is one among equally likely alternatives (Study 1) or when the problem is difficult (Studies 1 and 2). These findings are the first to demonstrate that even young children dynamically adapt their strategies for inquiry to increase the efficiency of information search.
Inference to the best explanation (IBE) versus explaining for the best inference (EBI). Science & Education , 24 (9-10), 1059–1077 . Springer. https://doi.org/10.1007/s11191-015-9784-4Abstract(2015).
In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with ‘‘Inference to the Best Explanation’’ (IBE) and ‘‘Explaining for the Best Inference’’ (EBI), respectively. We also provide some initial support for EBI and identify promising directions for future research.
Selective effects of explanation on learning during early childhood. Journal of Experimental Child Psychology , 126, 198-212. https://doi.org/10.1016/j.jecp.2014.03.001Abstract(2014).
Two studies examined the specificity of effects of explanation on learning by prompting 3- to 6-year-old children to explain a mechanical toy and comparing what they learned about the toy's causal and non-causal properties with children who only observed the toy, both with and without accompanying verbalization. In Study 1, children were experimentally assigned to either explain or observe the mechanical toy. In Study 2, children were classified according to whether the content of their response to an undirected prompt involved explanation. Dependent measures included whether children understood the toy's functional-mechanical relationships, remembered perceptual features of the toy, effectively reconstructed the toy, and (for Study 2) generalized the function of the toy when constructing a new one. Results demonstrate that across age groups, explanation promotes causal learning and generalization but does not improve (and in younger children can even impair) memory for causally irrelevant perceptual details.
Explanation and inference: mechanistic and functional explanations guide property generalization. Frontiers in Human Neuroscience , 8 700. https://doi.org/10.3389/fnhum.2014.00700Abstract(2014).
The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations.
Explaining prompts children to privilege inductively rich properties. Cognition , 133 (2), 343-57. https://doi.org/10.1016/j.cognition.2014.07.008Abstract(2014).
Four experiments with preschool-aged children test the hypothesis that engaging in explanation promotes inductive reasoning on the basis of shared causal properties as opposed to salient (but superficial) perceptual properties. In Experiments 1a and 1b, 3- to 5-year-old children prompted to explain during a causal learning task were more likely to override a tendency to generalize according to perceptual similarity and instead extend an internal feature to an object that shared a causal property. Experiment 2 replicated this effect of explanation in a case of label extension (i.e., categorization). Experiment 3 demonstrated that explanation improves memory for clusters of causally relevant (non-perceptual) features, but impairs memory for superficial (perceptual) features, providing evidence that effects of explanation are selective in scope and apply to memory as well as inference. In sum, our data support the proposal that engaging in explanation influences children's reasoning by privileging inductively rich, causal properties.
'Folk theories' about the causes of insomnia. Cognitive Therapy and Research , 37 (5). https://doi.org/10.1007/s10608-013-9543-2Abstract(2013).
The present study investigates 'folk theories' about the causes of insomnia. Participants with insomnia ( = 69) completed a qualitative and quantitative assessment of their folk theories. The qualitative assessment was to speak aloud for 1 minute in response to: 'What do you think causes your insomnia?'. The quantitative assessment involved completing the 'Causal Attributions of My Insomnia Questionnaire' (CAM-I), developed for this study. The three most common folk theories for both the causes of one's own insomnia as well as insomnia in others were 'emotions', 'thinking patterns' and 'sleep-related emotions'. Interventions targeting these factors were also perceived as most likely to be viable treatments. Seventy-five percent of the folk theories of insomnia investigated with the CAM-I were rated as more likely to be alleviated by a psychological versus a biological treatment. The results are consistent with research highlighting that folk theories are generally coherent and inform a range of judgments. Future research should focus on congruence of 'folk theories' between treatment providers and patients, as well as the role of folk theories in treatment choice, engagement, compliance and outcome.
The hazards of explanation: overgeneralization in the face of exceptions. Journal of Experimental Psychology: General , 142 (4), 1006-14. 10.1037/a0030996Abstract(2013).
Seeking explanations is central to science, education, and everyday thinking, and prompting learners to explain is often beneficial. Nonetheless, in 2 category learning experiments across artifact and social domains, we demonstrate that the very properties of explanation that support learning can impair learning by fostering overgeneralizations. We find that explaining encourages learners to seek broad patterns, hindering learning when patterns involve exceptions. By revealing how effects of explanation depend on the structure of what is being learned, these experiments simultaneously demonstrate the hazards of explaining and provide evidence for why explaining is so often beneficial. For better or for worse, explaining recruits the remarkable human capacity to seek underlying patterns that go beyond individual observations.
Review: Evolution challenges – Integrating research and practice in teaching and learning about evolution. Reports of the National Center for Science Education , 33 (5).(2013).
Explanation and prior knowledge interact to guide learning. Cognitive Psychology , 66 (1), 55-84. https://doi.org/10.1016/j.cogpsych.2012.09.002Abstract(2013).
How do explaining and prior knowledge contribute to learning? Four experiments explored the relationship between explanation and prior knowledge in category learning. The experiments independently manipulated whether participants were prompted to explain the category membership of study observations and whether category labels were informative in allowing participants to relate prior knowledge to patterns underlying category membership. The experiments revealed a superadditive interaction between explanation and informative labels, with explainers who received informative labels most likely to discover (Experiments 1 and 2) and generalize (Experiments 3 and 4) a pattern consistent with prior knowledge. However, explainers were no more likely than controls to discover multiple patterns (Experiments 1 and 2), indicating that effects of explanation are relatively targeted. We suggest that explanation recruits prior knowledge to assess whether candidate patterns are likely to have broad scope (i.e., to generalize within and beyond study observations). This interpretation is supported by the finding that effects of explanation on prior knowledge were attenuated when learners believed prior knowledge was irrelevant to generalizing category membership (Experiment 4). This research provides evidence that explanation can serve as a mechanism for deploying prior knowledge to assess the scope of observed patterns.
Occam's rattle: children's use of simplicity and probability to constrain inference. Developmental Psychology , 48 (4), 1156-64. https://doi.org/10.1037/a0026471Abstract(2012).
A growing literature suggests that generating and evaluating explanations is a key mechanism for learning and inference, but little is known about how children generate and select competing explanations. This study investigates whether young children prefer explanations that are simple, where simplicity is quantified as the number of causes invoked in an explanation, and how this preference is reconciled with probability information. Both preschool-aged children and adults were asked to explain an event that could be generated by 1 or 2 causes, where the probabilities of the causes varied across conditions. In 2 experiments, it was found that children preferred explanations involving 1 cause over 2 but were also sensitive to the probability of competing explanations. Adults, in contrast, responded on the basis of probability alone. These data suggest that children employ a principle of parsimony like Occam's razor as an inductive constraint and that this constraint is employed when more reliable bases for inference are unavailable.
Concept possession, experimental semantics, and hybrid theories of reference. Philosophical Psychology , 25 (5), 717–742. https://doi.org/10.1080/09515089.2011.627538Abstract(2012).