Talking Through the Problems: A Study of Discourse in Peer-Led Small Groups

Increasingly, studies are investigating the factors that influence student discourse in science courses, and specifically the mechanisms and discourse processes within small groups, to better understand the learning that takes place as students work together. This paper contributes to a growing body of research by analyzing how students engage in conversation and work together to solve problems in a peer-led small-group setting. This qualitative study evaluates video of Peer-Led Team Learning (PLTL) sessions in general chemistry, with attention to both the activity structures and the function of discourse as students undertook different types of problems across one semester. Our findings suggest that students talk their way through the problems; practicing a combination of regulative and instructional language to manage the group dynamics of their community of peer learners while developing and using specific disciplinary vocabulary. Additionally, student discourse patterns revealed a focus on the process of complex problem-solving, where students engage in joint decision-making by taking turns, questioning and explaining, and building on one another’s ideas. While students in our study engaged in less of the deeper, meaning-making discourse than expected, these observations about the function of language in small-group learning deepens an understanding of how PLTL and other types of small-group learning based on the tenets of social constructivism may lead to improvements in science education, with implications for the structure of small-group learning environments, problem design, and training of peer group leaders to encourage students to engage in more of the most effective discourse in these learning contexts

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Residential Segregation Across Metro St. Louis School Districts: Examining the Intersection of Two Spatial Dimensions

The present study employs a geospatial analytical approach to studying the evenness-clustering and isolation-exposure dimensions of segregation in the context of the St. Louis, Missouri, metropolitan region. In contrast to global indicators of segregation, this approach focuses on the evenness and isolation dimensions at the local level to visualize how they interact across neighborhoods. While not traditionally thought of as a method for theory testing, geographic information systems (GIS) can contribute to the validation process by displaying how constructs interact when applied in an actual geographic context. We examined separately the segregation dimension of racial evenness-exposure and its intersection with Black isolation and poverty isolation. The study used data from 446 census tracts that represent 65 St. Louis area school districts. When visualizing segregation dimensions through spatial mapping, it becomes apparent that communities that appear diverse may have neighborhoods where individuals or groups remain isolated