Measuring the Diversity Inclusivity of College Courses

Most studies of curricular diversity have focused on the effects of participation in diversity courses on student outcomes. Though the results have been positive, these studies have used limited measures of curricular diversity and there is a great need for a complimentary body of research demonstrating what faculty and what types of courses are more likely to include diversity. This study relies on 12 diversity inclusivity items derived from a comprehensive model of how diversity is included into a course to investigate how much diversity is being included in collegiate courses and what predicts diversity inclusivity, as measured by two scales: diverse grounding and inclusive learning. The results, based on 7,101 responses from faculty participating in the 2007 Faculty Survey of Student Engagement, suggest that most faculty are including diversity in their courses in some way, but that women and faculty of color tend to include diversity to a greater extent than their colleagues. Also, courses taught in the soft fields are more likely to be inclusive of diversity.     

Acting White: A Critical Review

The hypothesis of acting White has been heatedly debated and influential over the last 20 years or so in explaining the Black–White test score gap. Recently, economists have joined the debate and started providing new theoretical and empirical analyses of the phenomenon. This paper critically reviews the arguments that have been advanced to support and refute the hypothesis. This review particularly covers the analyses in economics because the economic analyses are relatively new and usually neglected in other disciplines. Also, nationally representative data are emphasized, whenever possible, to improve the generalizability of the arguments. This review concludes that although the analyses in both non-economics and economics are thought-provoking and compelling in some respect, a substantial body of empirical evidence is inconsistent with the assumptions of and results from the analyses.     

Evaluating research and researchers by the journal impact factor: Is it better than coin flipping?

The journal impact factor (JIF) is the average of the number of citations of the papers published in a journal, calculated according to a specific formula; it is extensively used for the evaluation of research and researchers. The method assumes that all papers in a journal have the same scientific merit, which is measured by the JIF of the publishing journal. This implies that the number of citations measures scientific merits but the JIF does not evaluate each individual paper by its own number of citations. Therefore, in the comparative evaluation of two papers, the use of the JIF implies a risk of failure, which occurs when a paper in the journal with the lower JIF is compared to another with fewer citations in the journal with the higher JIF. To quantify this risk of failure, this study calculates the failure probabilities, taking advantage of the lognormal distribution of citations. In two journals whose JIFs are ten-fold different, the failure probability is low. However, in most cases when two papers are compared, the JIFs of the journals are not so different. Then, the failure probability can be close to 0.5, which is equivalent to evaluating by coin flipping.     

Flocking motion in swarms with limited sensing radius and heterogeneous input constraints

This paper addresses the flocking motion problem for swarms of agents with two restrictions: limited communication/detection ranges and different input constraints. In this problem, the distance between pairs of agents determines if a communication/detection link exists among them, while each agent has a different control action bound. We use the notion of proximity graph to model communication/detection between agents and provide distributed controllers designed for leaderless and leader-followers flocking motion scenarios. Our proposed designs preserve the connectivity of the proximity graph while the control effort satisfies the bound of each particular agent. Unlike previous results, our protocols take advantage of the group’s input heterogeneity to use agents with a greater capacity to compensate for neighbors that are less capable of meeting the group’s requirements. Additionally, our designs are based only on local state errors and are robust to non-modeled edge failures. To illustrate the effectiveness of our proposal, we use numerical simulations of different flocking scenarios.     

Engineering the race car wing: application of the vortex panel numerical method

This study examined aerodynamic properties and boundary layer stability in five cambered airfoils operating at the low Reynolds numbers encountered in motor racing. Numerical modelling was carried out in the flow regime characterised by Reynolds numbers 0.82–1.29 × 10⁶. The design Reynolds number of 3 × 10⁶ was used as a reference. Aerodynamics variables were computed using AeroFoil 2.2 software, which uses the vortex panel method and integral boundary layer equations. Validation of AeroFoil 2.2 software showed very good agreement between calculated aerodynamic coefficients and wind tunnel experimental data. Drag polars, lift/drag ratio, pitching moment coefficient, chordwise distributions (surface velocity ratio, pressure coefficient and boundary layer thickness), stagnation point, and boundary layer transition and separation were obtained at angles of attack from −4° to 12°. The NASA NLF(1)-0414F airfoil offers versatility for motor racing with a wide low-drag bucket, low minimum profile drag, high lift/drag ratio, laminar flow up to 0.7 chord, rapid concave pressure recovery, high resultant pressure coefficient and stall resistance at low Reynolds numbers. The findings have implications for the design of race car wings.