Michelle R. Ellefson

Learning to label letters by sounds or names: A comparison of England and the United States

Learning about letters is an important foundation for literacy development. Should children be taught to label letters by conventional names, such as /bi/ for b, or by sounds, such as /b/? We queried parents and teachers, finding that those in the United States stress letter names with young children, whereas those in England begin with sounds. Looking at 5- to 7-year-olds in the two countries, we found that U.S. children were better at providing the names of letters than were English children. English children outperformed U.S. children on letter-sound tasks, and differences between children in the two countries declined with age. We further found that children use the first-learned set of labels to inform the learning of the second set. As a result, English and U.S. children made different types of errors in letter-name and letter-sound tasks. The childrens invented spellings also differed in ways reflecting the labels they used for letters.

Toward a theory of variability discrimination: finding differences

We sketch the outlines of a theory of variability discrimination that aggregates localized differences to mediate variability discrimination. This Finding Differences Model was compared to a Positional Entropy Model across four different data sets. Although the two models provide strong and similar fits across three of the data sets, only the Finding Differences Model is applicable to investigations involving multidimensional variability. Furthermore, the Finding Differences Model is based on an activation map that has been shown to have utility for visual search tasks, thus establishing its generality across task domains.

A theory of variability discrimination: Finding differences

Visual variability discrimination requires an observer to categorize collections of items on the basis of the variability in the collection; such discriminations may be vital to the adaptive actions of both humans and other animals. We present a theory of visual variability discrimination that aggregates localized differences between nearby items, and we compare this finding differences model with a previously proposed positional entropy model across several data sets involving both people and pigeons. We supplement those previously published data sets with four new experiments, three of which involve arrays comprising items entailing systematic, quantitative differences. Although both theories provide strong and similar fits of the published data sets, only the finding differences model is applicable to investigations involving quantitative item differences, providing excellent fits in these new experiments.

Design-Based Learning for Biology: Genetic Engineering Experience Improves Understanding of Gene Expression.

Gene expression is a difficult topic for students to learn and comprehend, at least partially because it involves various biochemical structures and processes occurring at the microscopic level. Designer Bacteria, a design‐based learning (DBL) unit for high‐school students, applies principles of DBL to the teaching of gene expression. Throughout the 8‐week unit, students genetically engineer bacteria to meet a need in their own lives. Through a series of investigations, discussions, and design modifications, students learn about the molecular processes and structures involved in gene expression, and how these processes and structures are dependent upon various environmental variables. This article is intended to describe the Designer Bacteria unit and report preliminary results of student progress and performance on pre‐unit and post‐unit assessments. Teacher experiences and student progress indicate that Designer Bacteria successfully taught core aspects of gene expression through DBL.

Inquiry-based training improves teaching effectiveness of biology teaching assistants

Graduate teaching assistants (GTAs) are used extensively as undergraduate science lab instructors at universities, yet they often have having minimal instructional training and little is known about effective training methods. This blind randomized control trial study assessed the impact of two training regimens on GTA teaching effectiveness. GTAs teaching undergraduate biology labs (n = 52) completed five hours of training in either inquiry-based learning pedagogy or general instructional “best practices”. GTA teaching effectiveness was evaluated using: (1) a nine-factor student evaluation of educational quality; (2) a six-factor questionnaire for student learning; and (3) course grades. Ratings from both GTAs and undergraduates indicated that indicated that the inquiry-based learning pedagogy training has a positive effect on GTA teaching effectiveness.

The joint contributions of shape and color to variability discrimination

Abstract Two experiments examined college students’ discrimination of complex visual displays that involved different degrees of variability or “entropy.” Displays depicted 16 line drawings of various shapes and colors; the participants needed to learn to classify a display in terms of its variability in shape or color while discounting variability in the other dimension (Experiment 1), or to classify based on both shape and color variability (Experiment 2). The participants’ accuracy and reaction time scores on a two-alternative forced-choice discrimination disclosed that people can learn to discount variability in an irrelevant dimension when necessary, but this variability does affect performance. Our data further suggest that variability discrimination depends on degrees of similarity across multiple dimensions thus underscoring the shortcomings of a measure of categorical variability (e.g., entropy) that only considers whether items are identical or different.

Efficiency of Executive Function: A Two-Generation Cross-Cultural Comparison of Samples From Hong Kong and the United Kingdom:

Although Asian preschoolers acquire executive functions (EFs) earlier than their Western counterparts, little is known about whether this advantage persists into later childhood and adulthood. To address this gap, in the current study we gave four computerized EF tasks (providing measures of inhibition, working memory, cognitive flexibility, and planning) to a large sample (n = 1,427) of 9- to 16-year-olds and their parents. All participants lived in either the United Kingdom or Hong Kong. Our findings highlight the importance of combining developmental and cultural perspectives and show both similarities and contrasts across sites. Specifically, adults’ EF performance did not differ between the two sites; age-related changes in executive function for both the children and the parents appeared to be culturally invariant, as did a modest intergenerational correlation. In contrast, school-age children and young adolescents in Hong Kong outperformed their United Kingdom counterparts on all four EF tasks, a difference consistent with previous findings from preschool children.

Under What Conditions Can Recursion Be Learned? Effects of Starting Small in Artificial Grammar Learning of Center-Embedded Structure

Abstract It has been suggested that external and/or internal limitations paradoxically may lead to superior learning, that is, the concepts of starting small and less is more (Elman, 1993; Newport, 1990). In this paper, we explore the type of incremental ordering during training that might help learning, and what mechanism explains this facilitation. We report four artificial grammar learning experiments with human participants. In Experiments 1a and 1b we found a beneficial effect of starting small using two types of simple recursive grammars: right‐branching and center‐embedding, with recursive embedded clauses in fixed positions and fixed length. This effect was replicated in Experiment 2 (N = 100). In Experiment 3 and 4, we used a more complex center‐embedded grammar with recursive loops in variable positions, producing strings of variable length. When participants were presented an incremental ordering of training stimuli, as in natural language, they were better able to generalize their knowledge of simple units to more complex units when the training input “grew” according to structural complexity, compared to when it “grew” according to string length. Overall, the results suggest that starting small confers an advantage for learning complex center‐embedded structures when the input is organized according to structural complexity.