Infant vocalizing and phenotypic outcomes in autism: Evidence from the first 2 years

Infant vocalizations are early-emerging communicative markers shown to be atypical in autism spectrum disorder (ASD), but few longitudinal, prospective studies exist. In this study, 23,850 infant vocalizations from infants at low (LR)- and high (HR)-risk for ASD (HR-ASD = 23, female = 3; HR-Neg = 35, female = 13; LR = 32, female = 10; 80% White; collected from 2007 to 2017 near Philadelphia) were analyzed at 6, 12, and 24 months. At 12 months, HR-ASD infants produced fewer vocalizations than HR-Neg infants. From 6 to 24 months, HR-Neg infants demonstrated steeper vocalization growth compared to HR-ASD and LR infants. Finally, among HR infants, vocalizing at 12 months was associated with language, social phenotype, and diagnosis at age 2. Infant vocalizing is an objective behavioral marker that could facilitate earlier detection of ASD.     

Musculoskeletal stiffness during hopping and running does not change following downhill backwards walking

Eccentric contractions that provide spring energy can also cause muscle damage. The aim of this study was to explore leg and vertical stiffness following muscle damage induced by an eccentric exercise protocol. Twenty active males completed 60 minutes of backward-walking on a treadmill at 0.67 m/s and a gradient of ? 8.5° to induce muscle damage. Tests were performed immediately before; immediately post; and 24, 48, and 168 hours post eccentric exercise. Tests included running at 3.35 m/s and hopping at 2.2 Hz using single- and double-legged actions. Leg and vertical stiffness were measured from kinetic and kinematic data, and electromyography (EMG) of five muscles of the preferred limb were recorded during hopping. Increases in pain scores (over 37%) occurred post-exercise and 24 and 48 hours later (p < 0.001). A 7% decrease in maximal voluntary contraction occurred immediately post-exercise (p = 0.019). Changes in knee kinematics during single-legged hopping were observed 168 hours post (p < 0.05). No significant changes were observed in EMG, creatine kinase activity, leg, or vertical stiffness. Results indicate that knee mechanics may be altered to maintain consistent levels of leg and vertical stiffness when eccentric exercise-induced muscle damage is present in the lower legs.     

Analyzing Contemporary Introductory Textbooks on Correctional Administration/Management/Organization: A Content Analysis

This book review essay discusses and analyzes how introductory textbooks on correctional administration, written primarily for the American university market, frame the discourse on this subject matter. The writer presents both quantitative and qualitative empirical evidence of coverage given to prison administration. In addition to traditional content analysis methods, the authors of these books were contacted and asked to explain the decision‐making processes they used for content inclusion, exclusion and/or minimization. The paper concludes with a handful of recommendations on improving texts in this subdiscipline.     

Dress rehearsal: a Bourdieusian analysis of body work in career portfolio programs

This article examines how career portfolio programs at two secondary schools establish corporeal regimes. Both programs require students to compose portfolios that plot their trajectories through school and into paid work. Prior to graduation, students defend their portfolios before panels of educators and businesspeople. Employing the Bourdieusian concepts of capital and habitus, this article investigates how these programs set up systems that value certain kinds of bodies. Further, it examines how students negotiate these systems and display different kinds of bodies in different kinds of ways. Ultimately, it is argued these disparate bodily performances are read by authorities as indicators of the types of paths students are travelling or should travel into the future.     

Applying computerized-scoring models of written biological explanations across courses and colleges: prospects and limitations

Our study explored the prospects and limitations of using machine-learning software to score introductory biology students’ written explanations of evolutionary change. We investigated three research questions: 1) Do scoring models built using student responses at one university function effectively at another university? 2) How many human-scored student responses are needed to build scoring models suitable for cross-institutional application? 3) What factors limit computer-scoring efficacy, and how can these factors be mitigated? To answer these questions, two biology experts scored a corpus of 2556 short-answer explanations (from biology majors and nonmajors) at two universities for the presence or absence of five key concepts of evolution. Human- and computer-generated scores were compared using kappa agreement statistics. We found that machine-learning software was capable in most cases of accurately evaluating the degree of scientific sophistication in undergraduate majors’ and nonmajors’ written explanations of evolutionary change. In cases in which the software did not perform at the benchmark of “near-perfect” agreement (kappa > 0.80), we located the causes of poor performance and identified a series of strategies for their mitigation. Machine-learning software holds promise as an assessment tool for use in undergraduate biology education, but like most assessment tools, it is also characterized by limitations.     

Harnessing technology to improve formative assessment of student conceptions in STEM: forging a national network

Concept inventories, consisting of multiple-choice questions designed around common student misconceptions, are designed to reveal student thinking. However, students often have complex, heterogeneous ideas about scientific concepts. Constructed-response assessments, in which students must create their own answer, may better reveal students' thinking, but are time- and resource-intensive to evaluate. This report describes the initial meeting of a National Science Foundation-funded cross-institutional collaboration of interdisciplinary science, technology, engineering, and mathematics (STEM) education researchers interested in exploring the use of automated text analysis to evaluate constructed-response assessments. Participants at the meeting shared existing work on lexical analysis and concept inventories, participated in technology demonstrations and workshops, and discussed research goals. We are seeking interested collaborators to join our research community.