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Inferential comprehension is necessary to connect ideas in a text together in a meaningful manner. There have been multiple studies on inferential comprehension involving texts of different genres (narrative and expository), but not a coherent overview of the findings of inferential comprehension by genre. The purpose of this study is to provide a coherent overview by conducting a meta-analysis of the findings of inferential comprehension by genre. A systematic review of the literature yielded 18 reports with 19 independent studies involving 1714 participants in which inferential comprehension was compared by genre. Based on robust variance estimation, scores on measures of inferential comprehension were higher for narrative texts than expository texts (g = .36, p = .02). This effect did not vary depending on whether inferential comprehension was assessed during or after reading, whether the texts for each genre were matched for readability, whether the reader was an adult or child, and whether the inference connected different ideas in the text (text connecting) or the text to background knowledge (knowledge based). Potential explanations of genre differences in inferential comprehension and future directions for research are discussed.

Background Large-scale genetic studies of common human diseases have focused almost exclusively on the independent main effects of single-nucleotide polymorphisms (SNPs) on disease susceptibility. These studies have had some success, but much of the genetic architecture of common disease remains unexplained. Attention is now turning to detecting SNPs that impact disease susceptibility in the context of other genetic factors and environmental exposures. These context-dependent genetic effects can manifest themselves as non-additive interactions, which are more challenging to model using parametric statistical approaches. The dimensionality that results from a multitude of genotype combinations, which results from considering many SNPs simultaneously, renders these approaches underpowered. We previously developed the multifactor dimensionality reduction (MDR) approach as a nonparametric and genetic model-free machine learning alternative. Approaches such as MDR can improve the power to detect gene-gene interactions but are limited in their ability to exhaustively consider SNP combinations in genome-wide association studies (GWAS), due to the combinatorial explosion of the search space. We introduce here a stochastic search algorithm called Crush for the application of MDR to modeling high-order gene-gene interactions in genome-wide data. The Crush-MDR approach uses expert knowledge to guide probabilistic searches within a framework that capitalizes on the use of biological knowledge to filter gene sets prior to analysis. Here we evaluated the ability of Crush-MDR to detect hierarchical sets of interacting SNPs using a biology-based simulation strategy that assumes non-additive interactions within genes and additivity in genetic effects between sets of genes within a biochemical pathway. Results We show that Crush-MDR is able to identify genetic effects at the gene or pathway level significantly better than a baseline random search with the same number of model evaluations. We then applied the same methodology to a GWAS for Alzheimer’s disease and showed base level validation that Crush-MDR was able to identify a set of interacting genes with biological ties to Alzheimer’s disease. Conclusions We discuss the role of stochastic search and cloud computing for detecting complex genetic effects in genome-wide data.

Purpose: Complex features of science texts present idiosyncratic challenges for middle grade readers, especially in a post-Common Core educational world where students' learning is dependent on understanding informational text. The primary aim of this study was to explore how middle school readers process science texts and whether such comprehension processes differed due to features of complexity in two science texts. Method: Thirty 7th grade students read two science texts with different profiles of text complexity in a think-aloud task. Think-aloud protocols were coded for six comprehension processes: connecting inferences, elaborative inferences, evaluative comments, metacognitive comments, and associations. We analyzed the quantity and type of comprehension processes generated across both texts in order to explore how features of text complexity contributed to the comprehension processes students produced while reading. Results: Students made significantly more elaborative and connecting inferences when reading a text with deep cohesion, simple syntax, and concrete words, while students made more evaluative comments, paraphrases, and metacognitive comments when reading a text with referential cohesion, complex syntax, and abstract words. Conclusions: The current study provides exploratory evidence for features of text complexity affecting the type of comprehension processes middle school readers generate while reading science texts. Accordingly, science classroom texts and materials can be evaluated for word, sentence, and passage features of text complexity in order to encourage deep level comprehension of middle school readers.

Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students ( N = 218 ) reading narrative texts were hand-coded for inferences. These data were also processed with a computer text analysis tool, Linguistic Inquiry and Word Count, for percentages of word use in the following categories: cognitive mechanism words, nonfluencies, and nine types of function words. Findings indicate that cognitive mechanisms were an independent, positive predictor of connections to background knowledge (i.e., elaborative inference generation) and nonfluencies were an independent, negative predictor of connections within the text (i.e., bridging inference generation). Function words did not provide unique variance towards predicting inference generation. These findings are discussed in the context of a cognitive reflection model and the differences between bridging and elaborative inference generation. In addition, potential practical implications for intelligent tutoring systems and computer-based methods of inference identification are presented.

This article describes an ongoing project to develop a formative, inferential reading comprehension assessment of causal story comprehension. It has three features to enhance classroom use: equated scale scores for progress monitoring within and across grades, a scale score to distinguish among low-scoring students based on patterns of mistakes, and a reading efficiency index. Instead of two response types for each multiple-choice item, correct and incorrect, each item has three response types: correct and two incorrect response types. Prior results on reliability, convergent and discriminant validity, and predictive utility of mistake subscores are briefly described. The three-response-type structure of items required rethinking the item response theory (IRT) modeling. IRT-modeling results are presented, and implications for formative assessments and instructional use are discussed.

This study reviewed 4,457 articles from 1998 to 2007 in American Counseling Association division‐affiliated journals to identify research articles published in counseling; 1,139 articles (25.6%) were quantitatively research based. The authors provide details related to quantitative research publications, including individual journal contribution to the research base, focus areas for research, and independent and dependent variables highlighted by researchers. One summary finding was that only 6% of counseling research articles explored effectiveness of counseling interventions.

PurposeComplex features of science texts present idiosyncratic challenges for middle grade readers, especially in a post–Common Core educational world where students' learning is dependent on understanding informational text. The primary aim of this study was to explore how middle school readers process science texts and whether such comprehension processes differed due to features of complexity in two science texts.MethodThirty 7th grade students read two science texts with different profiles of text complexity in a think-aloud task. Think-aloud protocols were coded for six comprehension processes: connecting inferences, elaborative inferences, evaluative comments, metacognitive comments, and associations. We analyzed the quantity and type of comprehension processes generated across both texts in order to explore how features of text complexity contributed to the comprehension processes students produced while reading.ResultsStudents made significantly more elaborative and connecting inferences when reading a text with deep cohesion, simple syntax, and concrete words, while students made more evaluative comments, paraphrases, and metacognitive comments when reading a text with referential cohesion, complex syntax, and abstract words.ConclusionsThe current study provides exploratory evidence for features of text complexity affecting the type of comprehension processes middle school readers generate while reading science texts. Accordingly, science classroom texts and materials can be evaluated for word, sentence, and passage features of text complexity in order to encourage deep level comprehension of middle school readers.

Over the last decade, Field Museum staff have worked to build enduring partnerships with local Filipinx-American community members. These partnerships engage participants in the stewardship of the collection, reinterpreting entangled object meanings and connecting the Museum’s collection to the lived experiences of modern communities. Through collaborative digitization efforts and events the Philippine Co-Curation partnership works to confront a colonial past while offering a gathering space for local Filipinx-Americans. As an emerging approach to collections management, it aims to embody the ideals of modern museology, bringing both partners and staff into uncertain territory and inspiring important questions about how collaborative relationships negotiate authority, recognize expertise, and navigate the institutional contexts shaping their execution. In this way, the Field Museum’s Philippine Co-Curation partnership represents an important case study into the potential and pitfalls of long-term collaborative partnerships, and their ability to make museums more accessible, locally relevant, and respectful of diverse traditions.