Rhonda Douglas Brown

Empirical validation of the triple-code model of numerical processing for complex math operations using functional MRI and group Independent Component Analysis of the mental addition and subtraction of fractions

The suitability of a previously hypothesized triple-code model of numerical processing, involving analog magnitude, auditory verbal, and visual Arabic codes of representation, was investigated for the complex mathematical task of the mental addition and subtraction of fractions. Functional magnetic resonance imaging (fMRI) data from 15 normal adult subjects were processed using exploratory group Independent Component Analysis (ICA). Separate task-related components were found with activation in bilateral inferior parietal, left perisylvian, and ventral occipitotemporal areas. These results support the hypothesized triple-code model corresponding to the activated regions found in the individual components and indicate that the triple-code model may be a suitable framework for analyzing the neuropsychological bases of the performance of complex mathematical tasks.

Social demand characteristics in children's and adults' eyewitness memory and suggestibility: the effect of different interviewers on free recall and recognition

Shortly after viewing a video of a theft, 5- and 7-year-old children and adults were interviewed with free recall and either misleading or unbiased-leading questions. After a 2-day delay, participants were interviewed with free recall and recognition questions administered by either the same or a different interviewer. Results from day 1 replicate previous findings with levels of recall and resistance to suggestibility increasing with age. Counter to predictions, correct recognition performance on day 2 was greater for some participants interviewed by the same as opposed to a different interviewer, and incorrect recognition was greater for all groups of participants for those interviewed by a different as opposed to the same interviewer. Results are discussed in terms of the role of context dependence on memory performance. Copyright

Making Memories: A Cross-Sectional Investigation of Episodic Memory Encoding in Childhood Using fMRI

In adults, the neural substrate associated with encoding memories connected to a specific time and place include the prefrontal cortex and medial temporal lobe (MTL). Using functional magnetic resonance imaging, this research studied the developmental trajectory of this frontal-MTL system by comparing 7- and 8-year-old children to those who were 10 or older in conditions that promoted episodic encoding. In 1 condition, participants generated verbs from nouns heard; in another, they listened to short stories for comprehension. Regions in which brain activation predicted subsequent recognition memory performance were identified. These included the left prefrontal cortex, but not MTL, in the verb generation condition for both age groups. In the story comprehension condition, activation in left posterior MTL predicted subsequent memory performance in both age groups, and activation in left anterior MTL (including the hippocampus proper) and left prefrontal cortex predicted subsequent memory only for the older children. These results illustrate both similarities and differences in how brain systems interact in development to mediate the formation of episodic memories.

Preschool Teachers' Use of Assessments and Curricula: A Statewide Examination

Preschool teachers in Ohio, representing Head Start, Preschool Special Education, and Public School Preschool programs, completed a survey designed to examine their use of assessments and curricula. The 586 preschool teachers provided a range of responses, including reported use of 21 commercial assessments and self-developed and program-developed checklists. A majority of teachers listed curriculum-based measures acceptable in linking assessment and intervention. Teachers also provided a range of curricular responses, including six that met our definition of an actual curriculum. Differences were found between the three types of teachers with respect to their level of education and the total number of assessments and curricula responses, and the number of assessments (including self-developed checklists) and actual curricula used, but not years of experience.

Connecting Neuroscience, Cognitive, and Educational Theories and Research to Practice: A Review of Mathematics Intervention Programs

Research Findings: This article describes major theories and research on math cognition across the fields of neuroscience, cognitive psychology, and education and connects these literatures to intervention practices. Commercially available math intervention programs were identified and evaluated using the following questions: (a) Did neuroscience research inform the development of the program? or Is the program consistent with neuroscience theory and research? (b) Which cognitive processes are targeted by the program? and (c) What kinds of research support the program? A detailed review is provided for each program supported by empirical, peer-reviewed research. Practice or Policy: Twenty commercially available math intervention programs designed for pre-kindergarten through 3rd-grade students were identified. Three programs had publisher-reported use of neuroscience research in their development: Fluency and Automaticity through Systematic Teaching with Technology (FASTT Math), Number Worlds, and The Number Race. Five programs reported empirical, peer-reviewed research and are reviewed in detail: Accelerated Math, Corrective Mathematics, FASTT Math, Number Worlds, and The Number Race. Results indicate that although a great number of programs are available, few have been validated through empirical, peer-reviewed research. Practitioners should carefully review programs prior to their implementation, paying particular attention to targeted cognitive processes and the research base supporting the programs efficacy.

The Biologizing of Cognition, Development, and Education: Approach with Cautious Enthusiasm

In our commentary, we propose the current research from the field of developmental neuroscience can be incorporated within the theoretical perspectives advocated by evolutionary psychologists and advocates of the developmental systems approach. We then describe research on memory and the relationship between spatial-temporal reasoning and mathematical abilities as examples of literatures that have benefitted from the neuroscience approach. We conclude by expressing enthusiasm for the recent neuroscience findings, but caution that developmental neurosciences focus on infancy and preschool children should not result in an overemphasis on early development and education at the expense of later development and education.

Neural Correlates of Memory Development and Learning: Combining Neuroimaging and Behavioral Measures to Understand Cognitive and Developmental Processes

This special issue includes 4 articles addressing the general theme of neural correlates of memory development and learning. Taken together, the articles represent a broad range of development, including infants, children, adolescents, and adults as participants. Each line of research examines relations between brain activity and cognitive functions using both physiological measures, event-related potentials or functional magnetic resonance imaging, and behavioral measures of memory and learning. This introduction sets the stage by briefly reviewing historical trends in memory development research, discussing major issues associated with neuroimaging research, and providing an integrated perspective of some specific contributions of the investigations included in this special issue, arguing that combining neuroimaging and behavioral measures advances research on memory development and learning in terms of understanding cognitive and developmental processes. The article concludes with a brief discussion of potential future directions for this type of research.

Preschoolers Learning Science: Myth or Reality?

ion, because the fact’s relevant pieces of information are readily accessible in a single event. By contrast, the idea that caterpillars turn into butterflies is more abstract: caterpillars and butterflies need to be conceptually connected, while differences between the two need to be ignored (e.g., shape, behavior). Similarly, the idea that water can turn into ice is less abstract than the idea that materials consist of particles that are invisible to the naked eye. The latter requires the learner to ignore salient features of an object (e.g., the shape or size of a material), and instead note underlying patterns of how materials interact and change. Can young children learn low-abstraction science facts? This question is relatively trivial, as one might guess from every-day experiences with children (e.g., Cumming, 2003). For example, preschoolers can learn with little effort the names of new species, the names of the planets, and even the terms associated with material properties and chemical change (e.g., Fleer & Hardy, 1993). However, educators sometimes worry that children’s learning of facts is no more than passive rote memorization, far from reflecting ‘truly understanding’ the facts. At the crux of this concern is that young children might not be able to go beyond mere facts to interconnect them under a common concept. Even though there is evidence of spontaneous abstractions in young children (e.g., Hickling & Gelman 1995; Hickling & Current Topics in Childrens Learning and Cognition 48 Wellman, 2001), higher-order concepts pertinent to science knowledge might be too abstract for them. The more central question, therefore, is whether young children can learn abstract concepts. There is an interesting drawback when it comes to learning abstract concepts. Unlike what one would expect, findings show that overly detailed and richly embedded learning materials have a negative impact on children’s ability to abstract underlying concepts (e.g., Goldstone & Sakamoto, 2003; Goldstone, & Son; 2005; Kaminski, Sloutsky, & Heckler, 2008; Ratterman, Gentner, & DeLoache, 1990; Son, Smith, & Goldstone, 2008). For example, when the learning materials were colored shaped intricately, children had more difficulty discovering an abstract mathematical rule than when the materials were black-and-white simple shapes (Kaminski et al., 2008). When the shapes were such that they helped children intuit the rules, learning improved, but transfer to a new task nevertheless suffered, compared to using none-specific and generic shapes (see also DeLoache, 1995; Bassok & Holyoak, 1989; Mix, 1999; Ratterman & Gentner, 1998; Sloutsky, Kaminski, & Heckler, 2005; Uttal, Liu, & DeLoache, 1999; Uttal, Scudder, & DeLoache, 1997). Taken together, there seems to be a pronounced advantage of sparse contexts when learning abstract concepts. The advantage lies in minimizing distraction, undermining the possibility of forming mistaken ideas, and highlighting relevant pieces of information. Of course, when it comes to young children, a motivational factor needs to be taken into account (cf., Mantzicopoulos, Patrick, & Samarapungavan 2008; Zembylas, 2008). A setting without rich details might fail to engage the child sufficiently to prompt learning. For example, a young child might not be inclined to explore objects unless they vary in color, shape, and texture in interesting ways. Therefore, to make abstract ideas accessible to young children, it might not be possible to strip the context of any unnecessary complexity. A different approach to instruction is needed, one that helps make abstract ideas visible to children, while, at the same time, retaining a richly detailed context. Such approach might require a pedagogy that bootstraps the understanding of abstract ideas, rather than waiting for young children to detect them by themselves. Findings show that such approach is indeed possible. Take for example the abstract idea of object conservation, the idea that matter exists, even when it is not visible with the naked eye. To understand this concept, children have to ignore their phenomenological experience of an object’s presence and therefore engage in abstract reasoning. Immersing children into a richly detailed environment might not make this abstract idea salient. On the other hand, providing children with the opportunity to reflect on guided explorations of material transformation improved their understanding of object conservation (Acher, Arca & Sanmarti, 2007). In particular, 7to 8-year-olds were asked to observe possible changes in materials (e.g., stones, wood, water, metal) when they were trying to break them down, mix them in water, or burn them. After each manipulation, children were encouraged to draw the changes they observed in the materials. They also participated in group discussions designed to help them conceptualize their experiences. Findings show not only that children were able to express opinions and counter arguments, Preschoolers Learning Science: Myth or Reality? 49 but also that they could understand object conservation. Even 5-year-old preschoolers can appreciate the idea that water, when invisible to the naked eye, is nevertheless still present in some form (Tytler & Peterson, 2000). Replacing Existing Beliefs. Learning about a new science concept can be problematic, beyond the required abstract-reasoning skills. This is because in some cases, children’s naïve ideas about the domain conflict with the pertinent science concept. The detrimental power of mistaken ideas has been recognized for decades, leading to extensive research into understanding both the nature of the misconceptions across ages and how they can be changed (e.g., see Ohlsson, 2011; Vosniadou, 2008, for an extensive discussion). Indeed, existing misconceptions appear to be very difficult to change (e.g., Anderson & Smith, l987; Gunstone, Champagne, & Klopfer, 1981; Hannust, & Kikas, 2007; Kloos & Somerville, 2001; Linn & Burbules, 1988; Schneps, 1987). In many instances, children prefer mistaken ideas over correct ideas, even after extensive training and even after shortcomings of mistaken ideas have been pointed out explicitly. Take for example findings with 5to 7-year-olds who participated in an astronomy curriculum on the spherical properties of the earth (Hannust, & Kikas, 2007). The four-week curriculum involved hands-on mini-lessons designed to target several apparent contractions, for example why the earth is perceived to be flat, or why people living on the “down-side” of the earth do not fall off. Yet, despite this relatively extensive intervention, children’s understanding did not change significantly over the course of the instruction. While their performance on a pretest was below chance (11% correct), it stayed low even after the lessons (15% correct). In fact, results show that children relied more heavily on their phenomenological experience after instruction than before (see also Kloos & Van Orden, 2005 for similar counter effects of teaching interventions). Given such resistance to change, one might speculate that a child’s mistaken ideas are innate. But upon closer look into the nature of beliefs, it turns out that misconceptions arise when misleading pieces of information are more salient than pieces of information that are relevant to the particular science concept (cf., Kloos, Fisher, & Van Orden, 2010). Therefore, to change a child’s mistaken ideas in a science domain, a pedagogical approach is needed that can change the salience of relevant compared to irrelevant pieces of information (i.e., increase the salience of science-relevant pieces of information). With such change in making relevant information salient, misconceptions might be avoided altogether. Indeed, children who have benefitted from focused instruction seem to harbor fewer misconceptions in later years at school (cf., Novak & Gowin, 1984.) A promising approach in this regard is the use of conceptual models, also known as conceptual schemas, mental models, or scientific models (e.g., Glynn & Duit, 1995; Kenyon, Schwarz, & Hug, 2008; Mayer, 1989, Penner, Giles, Lehrer, & Schauble, 1997; Smith, Snir, & Grosslight, 1992; Smith & Unger, 1997, for a review see Vosniadou, 2008). Conceptual models are abstract representations of a science phenomenon – external diagrams of some sort that children can internalize. Models do not represent the real world in its full degree of complexity. Instead, they are schematics of the real world, designed to highlight only a selected number of relations (the ones that are relevant to the science concept of interest), Current Topics in Childrens Learning and Cognition 50 while downplaying other relations (ones that are less relevant or misleading). Importantly, models represent predictive and explanatory rules, thus making visible the components of science phenomenon that are difficult to be perceived on the basis of phenomenological experience alone. As such, they make relevant science facts salient, in effect decreasing the salience of irrelevant pieces of information. There are several studies that show the effectiveness of conceptual models in young children (e.g., Gobert & Buckley, 2000; Kenyon et al. 2008; Wiser & Smith, 2008; Baker, Haussmann, Kloos, & Fisher, 2011). An illustrative example uses the science domain of material density, a concept that is defined by the ratio of the two highly salient dimensions of mass and volume. Predictably, children often ignore density and use instead perceived heaviness of an object as the sole predictor of the object’s buoyancy (e.g., Piaget & Inhelder, 1974; Kloos et al., 2010). To help children overcome this mistaken focus on an object’s heaviness, a conceptual model of density was developed, also known as dot-per-box (e.g., Smith & Unger, 1997; Wiser & Smith, 2008). It involves a display in which the volume of an object is represented as a certain number of boxes, and mass is represented

Medical Team Training: Using Simulation as a Teaching Strategy for Group Work.

Described is an innovative approach currently being used to inspire group work, specifically a medical team training model, referred to as The Simulation Model, which includes as its major components: (1) Prior Training in Group Work of Medical Team Members; (2) Simulation in Teams or Groups; (3) Multidisciplinary Teamwork; (4) Team Leader Selection; and (5) a Facilitated Group Debriefing Process. This approach involves multidisciplinary medical teams and their leaders responding to changes in critical, stress-filled environments by organizing their approach to patient care through simulated practice sessions, using human patient simulators which mimic actual patients in the health care environment.

Theories for Understanding the Neuroscience of Mathematical Cognitive Development

Throughout history, humans have invented and used mathematics to solve meaningful problems critical to survival and prosperity. To advance our understanding of mathematical cognitive development and achievement, it is important to place research within theoretical frameworks that allow us to interpret and apply results. In this chapter, I discuss evolutionary developmental psychology as a meta-theory for considering important questions relevant to understanding neuroscience research on mathematical cognitive development. Then, I use a developmental systems approach to describe how genetics, neural activity, and experiences in environmental niches dynamically interact in the development of evolved probabilistic cognitive mechanisms. As an example, I describe biologically primary mathematical abilities that may have been selected for in evolution to solve recurrent problems, passed on via genetics, and instantiated in human brain development. The process of their development into biologically secondary mathematical abilities, which are cultural inventions that build upon biologically primary abilities, is then described. I present Dehaene and colleagues’ triple-code model of numerical processing as the predominant neuroscience-based theory of mathematical cognition. I conclude by arguing that there is a place for neuroscience in the field of cognitive development and advocating for the integration of scientific findings across levels of analysis.