A Replicable Identity-Based Intervention Reduces the Black-White Suspension Gap at Scale

Nationally, educators suspend Black students at greater rates than any other group. This disproportionality is fueled by stereotypes casting Black students as “troublemakers”—a label students too often internalize as part of their identities. Across two independent double-blind randomized field trials involving over 2,000 seventh graders in 11 middle schools, we tested the efficacy of a brief intervention to buffer students from stereotypes and mitigate the racial suspension gap. The self-affirmation intervention helps students access positive aspects of their identities less associated with troublemaking in school. Confirmed in both trials, treatment effects cut Black-White suspension and office disciplinary referral gaps during seventh and eighth grade by approximately two thirds, with even greater impacts for Black students with prior infractions.

Tensor P-Spline Smoothing for Spatial Analysis of Plant Breeding Trials

Large agricultural field trials may display irregular spatial trends that cannot be fully captured by a purely randomization-based analysis. For this reason, paralleling the development of analysis-of-variance procedures for randomized field trials, there is a long history of spatial modelling for field trials, starting with the early work of Papadakis on nearest neighbour analysis, which can be cast in terms of first or second differences among neighbouring plot values. This kind of spatial modelling is amenable to a natural extension using P-splines, as has been demonstrated in recent publications in the field. Here, we consider the P-spline framework, focussing on model options that are easy to implement in linear mixed model packages. Two examples serve to illustrate and evaluate the methods. A key conclusion is that first differences are rather competitive with second differences. A further key observation is that second differences require special attention regarding the representation of the null space of the smooth terms for spatial interaction, and that an unstructured variance-covariance structure is required to ensure invariance to translation and rotation of eigenvectors associated with that null space. We develop a strategy that permits fitting this model with ease, but the approach is more demanding than that needed for fitting models using first differences. Hence, even though in other areas second differences are very commonly used in the application of P-splines, our main conclusion is that with field trials first differences have advantages for routine use.

Recombinant inbred lines derived from cultivars of pea for understanding the genetic basis of variation in breeders' traits

In order to gain an understanding of the genetic basis of traits of interest to breeders, the pea varieties Brutus, Enigma and Kahuna were selected, based on measures of their phenotypic and genotypic differences, for the construction of recombinant inbred populations. Reciprocal crosses were carried out for each of the three pairs, and over 200 F2 seeds from each cross advanced to F13. Bulked F7 seeds were used to generate F8–F11 bulks, which were grown in triplicated plots within randomized field trials and used to collect phenotypic data, including seed weight and yield traits, over a number of growing seasons. Genetic maps were constructed from the F6 generation to support the analysis of qualitative and quantitative traits and have led to the identification of four major genetic loci involved in seed weight determination and at least one major locus responsible for variation in yield. Three of the seed weight loci, at least one of which has not been described previously, were associated with the marrowfat seed phenotype. For some of the loci identified, candidate genes have been identified. The F13 single seed descent lines are available as a germplasm resource for the legume and pulse crop communities.

Research Committee: Research in Mathematics Education: Multiple Methods for Multiple Uses

I do not think any thoughtful researcher today believes that experiments or randomized field trials are the “gold standard” for addressing all the important questions in educational research. Yet, because these designs are now required by the 2001 No Child Left Behind Act (NCLB) and are being strongly encouraged in other federal legislation and funding initiatives, scholars, practitioners, parents, and researchers must devote time and energy to fighting these designs when they are inappropriate or irrelevant, which is often the case. Despite long-standing objections from prominent methodologists and reservations expressed by national groups and committees, key policymakers in the federal government are encouraging the pursuit of experimental designs primarily or exclusively (Eisenhart, 2005, p. 246).