Despite increasing emphasis in the United States on promoting student engagement and achievement inscience, technology, engineering, and mathematics (STEM) fields, the origins of scientific literacy remainpoorly understood. We begin to address this limitation by considering the potential contributions oftwo distinct domain-general skills to early scientific literacy. Given their relevance to making predic-tions and evaluating evidence, we consider the degree to which causal reasoning skills relate to scientificliteracy (as measured by an adaptive standardized test specifically designed for preschoolers). We alsoconsider executive function (EF) as a potentially more fundamental contributor. While previous researchhas demonstrated that EF is predictive of achievement in other core academic domains like reading andmath, its relationship to scientific literacy, particularly in early childhood, has received little attention. Toexamine how causal reasoning and EF together potentially relate to the development of scientific literacyin young children, we recruited 125 3-year-olds to complete three causal reasoning tasks, three EF tasks,and the aforementioned measure of scientific literacy. Results from a series of hierarchical regressionsrevealed that EF, and one measure of causal reasoning (causal inferencing) were related to scientific liter-acy, even after controlling for age, ethnicity, maternal education, and vocabulary knowledge. Moreover,causal inferencing ability was a significant partial mediator between EF and scientific literacy. Althoughadditional research will be required to further specify the nature of these relationships, the current worksuggests that EF has the potential to support scientific literacy, perhaps in part, by scaffolding causalreasoning skills.
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Relations Between Executive Functions and Causal Reasoning in Young Children
Despite the early development of causal reasoning (CR), and its potential for shaping scientific literacy, we have little understanding of its structural origins. Specifically, is CR a unique capability that develops relatively independently or is it largely dependent on broader, more fundamental, cognitive abilities? Executive Functioning (EF) is an especially promising contributor to CR based on its already established role in related skills like planning and problem solving (e.g., Diamond, 2013). To begin exploring this potential relationship, we assessed 123 three (Mage = 3.42 years) and 64 five year olds’ (Mage = 5.36 years) performance on two CR tasks (counterfactual reasoning and causal inference), each of which we expected might be influenced in different ways by distinct EF skills. The counterfactual reasoning task (Guajardo & Turley-Ames, 2004) required children to generate alternative courses of action that would lead to different outcomes in fictional vignettes. The causal inference task (Das Gupta & Bryant, 1989) required children to compare pictures taken before and after a transformation (e.g., broken flowerpot and intact flowerpot) and to select a tool (e.g., glue) that could have caused it. We measured EF with three tasks: flanker (inhibition), count and label (working memory), and dimensional change card sort (cognitive flexibility). Finally, we measured children’s vocabulary and processing speed. To explore the relationship between EF and CR, we conducted a series of four linear regressions predicting causal inference and counterfactual reasoning ability in 3 and 5 year olds. Of all our measures, only vocabulary and inhibitory control emerged as significant predictors of causal inference ability for both 3 (βvocab = .04, p = .002, and βinhib = .04, p = .04) and 5 year olds (βvocab = .03, p = .01, and βinhib = .02, p = .04). Similarly, inhibitory control emerged as the only significant predictor of counterfactual reasoning in 3 year olds, βinhib = .03, p = .03. In contrast, for 5 year olds, working memory was the only significantly predictor of counterfactual reasoning, βWM = .71, p = .02. These results suggest that causal inference skills are stably supported by inhibitory control throughout early childhood. The story for counterfactual reasoning, however, appears to be somewhat more complex. Consistent with previous work (Beck, Riggs & Gorniak, 2009), inhibitory control supported counterfactual reasoning ability in our 3-year-old sample. However, inhibitory control did not significantly predict counterfactual reasoning in 5 year olds, it was supported by working memory instead. One explanation for this difference might have to do with the sophistication of children’s counterfactual reasoning skills at these different ages. Taken together, these results suggest that CR does not develop as a unique capacity, but instead likely relies on EFs that influence different CR skills in distinct ways across development. This represents an initial step in understanding early CR skills, which are promising contributors to emerging scientific literacy.
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- Award ID(s):
- 1762158
- NSF-PAR ID:
- 10196732
- Date Published:
- Journal Name:
- AERA
- ISSN:
- 1502-9115
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Expert testimony varies in scientific quality and jurors have a difficult time evaluating evidence quality (McAuliff et al., 2009). In the current study, we apply Fuzzy Trace Theory principles, examining whether visual and gist aids help jurors calibrate to the strength of scientific evidence. Additionally we were interested in the role of jurors’ individual differences in scientific reasoning skills in their understanding of case evidence. Contrary to our preregistered hypotheses, there was no effect of evidence condition or gist aid on evidence understanding. However, individual differences between jurors’ numeracy skills predicted evidence understanding. Summary Poor-quality expert evidence is sometimes admitted into court (Smithburn, 2004). Jurors’ calibration to evidence strength varies widely and is not robustly understood. For instance, previous research has established jurors lack understanding of the role of control groups, confounds, and sample sizes in scientific research (McAuliff, Kovera, & Nunez, 2009; Mill, Gray, & Mandel, 1994). Still others have found that jurors can distinguish weak from strong evidence when the evidence is presented alone, yet not when simultaneously presented with case details (Smith, Bull, & Holliday, 2011). This research highlights the need to present evidence to jurors in a way they can understand. Fuzzy Trace Theory purports that people encode information in exact, verbatim representations and through “gist” representations, which represent summary of meaning (Reyna & Brainerd, 1995). It is possible that the presenting complex scientific evidence to people with verbatim content or appealing to the gist, or bottom-line meaning of the information may influence juror understanding of that evidence. Application of Fuzzy Trace Theory in the medical field has shown that gist representations are beneficial for helping laypeople better understand risk and benefits of medical treatment (Brust-Renck, Reyna, Wilhelms, & Lazar, 2016). Yet, little research has applied Fuzzy Trace Theory to information comprehension and application within the context of a jury (c.f. Reyna et. al., 2015). Additionally, it is likely that jurors’ individual characteristics, such as scientific reasoning abilities and cognitive tendencies, influence their ability to understand and apply complex scientific information (Coutinho, 2006). Methods The purpose of this study was to examine how jurors calibrate to the strength of scientific information, and whether individual difference variables and gist aids inspired by Fuzzy Trace Theory help jurors better understand complicated science of differing quality. We used a 2 (quality of scientific evidence: high vs. low) x 2 (decision aid to improve calibration - gist information vs. no gist information), between-subjects design. All hypotheses were preregistered on the Open Science Framework. Jury-eligible community participants (430 jurors across 90 juries; Mage = 37.58, SD = 16.17, 58% female, 56.93% White). Each jury was randomly assigned to one of the four possible conditions. Participants were asked to individually fill out measures related to their scientific reasoning skills prior to watching a mock jury trial. The trial was about an armed bank robbery and consisted of various pieces of testimony and evidence (e.g. an eyewitness testimony, police lineup identification, and a sweatshirt found with the stolen bank money). The key piece of evidence was mitochondrial DNA (mtDNA) evidence collected from hair on a sweatshirt (materials from Hans et al., 2011). 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They filled this questionnaire out again after a 45-minute deliberation. Measures We measured Attitudes Toward Science (ATS) with indices of scientific promise and scientific reservations (Hans et al., 2011; originally developed by National Science Board, 2004; 2006). We used Drummond and Fischhoff’s (2015) Scientific Reasoning Scale (SRS) to measure scientific reasoning skills. Weller et al.’s (2012) Numeracy Scale (WNS) measured proficiency in reasoning with quantitative information. The NFC-Short Form (Cacioppo et al., 1984) measured need for cognition. We developed a 20-item multiple-choice comprehension test for the mtDNA scientific information in the cases (modeled on Hans et al., 2011, and McAuliff et al., 2009). Participants were shown 20 statements related to DNA evidence and asked whether these statements were True or False. The test was then scored out of 20 points. Results For this project, we measured calibration to the scientific evidence in a few different ways. We are building a full model with these various operationalizations to be presented at APLS, but focus only on one of the calibration DVs (i.e., objective understanding of the mtDNA evidence) in the current proposal. We conducted a general linear model with total score on the mtDNA understanding measure as the DV and quality of scientific evidence condition, decision aid condition, and the four individual difference measures (i.e., NFC, ATS, WNS, and SRS) as predictors. Contrary to our main hypotheses, neither evidence quality nor decision aid condition affected juror understanding. However, the individual difference variables did: we found significant main effects for Scientific Reasoning Skills, F(1, 427) = 16.03, p <.001, np2 = .04, Weller Numeracy Scale, F(1, 427) = 15.19, p <.001, np2 = .03, and Need for Cognition, F(1, 427) = 16.80, p <.001, np2 = .04, such that those who scored higher on these measures displayed better understanding of the scientific evidence. In addition there was a significant interaction of evidence quality condition and scores on the Weller’s Numeracy Scale, F(1, 427) = 4.10, p = .04, np2 = .01. Further results will be discussed. Discussion These data suggest jurors are not sensitive to differences in the quality of scientific mtDNA evidence, and also that our attempt at helping sensitize them with Fuzzy Trace Theory-inspired aids did not improve calibration. Individual scientific reasoning abilities and general cognition styles were better predictors of understanding this scientific information. These results suggest a need for further exploration of approaches to help jurors differentiate between high and low quality evidence. Note: The 3rd author was supported by an AP-LS AP Award for her role in this research. Learning Objective: Participants will be able to describe how individual differences in scientific reasoning skills help jurors understand complex scientific evidence.more » « less
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Whether and to what extent kindergarten children's executive functions (EF) constitute promising targets of early intervention is currently unclear. This study examined whether kindergarten children's EF predicted their second‐grade academic achievement and behavior. This was done using (a) a longitudinal and nationally representative sample (N = 8,920, Mage = 97.6 months), (b) multiple measures of EF, academic achievement, and behavior, and (c) extensive statistical control including for domain‐specific and domain‐general lagged dependent variables. All three measures of EF—working memory, cognitive flexibility, and inhibitory control—positively and significantly predicted reading, mathematics, and science achievement. In addition, inhibitory control negatively predicted both externalizing and internalizing problem behaviors. Children's EF constitute promising targets of experimentally evaluated interventions for increasing academic and behavioral functioning.more » « less
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Background Inhibitory control, or inhibition, is one of the core executive functions of humans. It contributes to our attention, performance, and physical and mental well-being. Our inhibitory control is modulated by various factors and therefore fluctuates over time. Being able to continuously and unobtrusively assess our inhibitory control and understand the mediating factors may allow us to design intelligent systems that help manage our inhibitory control and ultimately our well-being. Objective The aim of this study is to investigate whether we can assess individuals’ inhibitory control using an unobtrusive and scalable approach to identify digital markers that are predictive of changes in inhibitory control. Methods We developed InhibiSense, an app that passively collects the following information: users’ behaviors based on their phone use and sensor data, the ground truths of their inhibition control measured with stop-signal tasks (SSTs) and ecological momentary assessments (EMAs), and heart rate information transmitted from a wearable heart rate monitor (Polar H10). We conducted a 4-week in-the-wild study, where participants were asked to install InhibiSense on their phone and wear a Polar H10. We used generalized estimating equation (GEE) and gradient boosting tree models fitted with features extracted from participants’ phone use and sensor data to predict their stop-signal reaction time (SSRT), an objective metric used to measure an individual’s inhibitory control, and identify the predictive digital markers. Results A total of 12 participants completed the study, and 2189 EMAs and SST responses were collected. The results from the GEE models suggest that the top digital markers positively associated with an individual’s SSRT include phone use burstiness (P=.005), the mean duration between 2 consecutive phone use sessions (P=.02), the change rate of battery level when the phone was not charged (P=.04), and the frequency of incoming calls (P=.03). The top digital markers negatively associated with SSRT include the standard deviation of acceleration (P<.001), the frequency of short phone use sessions (P<.001), the mean duration of incoming calls (P<.001), the mean decibel level of ambient noise (P=.007), and the percentage of time in which the phone was connected to the internet through a mobile network (P=.001). No significant correlation between the participants’ objective and subjective measurement of inhibitory control was found. Conclusions We identified phone-based digital markers that were predictive of changes in inhibitory control and how they were positively or negatively associated with a person’s inhibitory control. The results of this study corroborate the findings of previous studies, which suggest that inhibitory control can be assessed continuously and unobtrusively in the wild. We discussed some potential applications of the system and how technological interventions can be designed to help manage inhibitory control.more » « less
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.3102/1315192
