Dual identities: organizational negotiation in STEM-focused Catholic schools

In the last decade, STEM-focused schools have opened their doors nationally in the hope of meeting students’ contemporary educational needs. Despite the growth of these STEM-focused institutions, minimal research exists that follows how schools make a transition toward a STEM focus and what organizational structures are most conducive to a successful transition. The adoption of a STEM focus has clear implications for a school’s organizational identity. For Catholic schools, the negotiation of a new STEM focus is especially complex, as Catholic schools have been shown to generally possess a distinct religious and cultural organizational identity. The adoption of a second, STEM-focused identity raises questions about whether and how these identities can coexist. Framed by perspectives on organizational identity and existing conceptualizations of the cultural and religious hallmarks of Catholic schools, this study utilizes a multiple-case study design to explore the organizational transition of four Catholic K-8 institutions to Catholic STEM-focused schools. These cases demonstrate the particular challenges of negotiating multiple organizational identities. While variation existed in how the four schools accommodated these identities, the most promising environments for successful transition drew upon an aggregative model of identity negotiation, that is, when schools attended to both identities, but ensured that the original Catholic identity of the school remained foundational to all decisions. The least successful identity negotiations occurred when there was a lack of common understanding about what comprised a STEM-focused school, leading to minimal buy-in from stakeholders or when a school sought to make the transition for recruitment or marketing rather than mission-driven reasons. Discussion of the more successful identity aggregation provides a framework for schools within and beyond the religious sector that desire to adopt an additional STEM-focused identity.     

Rolling Back Zero Tolerance: The Effect of Discipline Policy Reform on Suspension Usage and Student Outcomes

Beginning in the early 1990s, states and districts enacted zero-tolerance discipline policies that relied heavily on out-of-school suspensions. Recently, districts nationwide have revised these policies in favor of more tempered disciplinary responses. In 2012–2013, Philadelphia reformed its discipline policy to limit suspensions for nonviolent student misconduct and granted principals greater discretion in responding to more serious occurrences of student misconduct. Employing a difference-in-differences approach, we find that Philadelphia's reform resulted in a modest decline in suspensions for nonviolent infractions in the year of reform; however, total suspensions remained unchanged while serious incidents of student misconduct increased. Further, the truancy rate increased and district math and English language arts achievement declined following the policy reform. These findings should inform policymakers and practitioners on the implications of district-level reforms for suspension usage and the potential consequences for student outcomes.     

Dealing with non‐normality: an introduction and step‐by‐step guide using R

The article presents some notes on normalization and illustrates these procedures using graphing functions in R. Using real data, the paper also presents an R package and online Shiny app that efficiently transforms variables in large datasets.     

Evaluating Intervention Effects in a Diagnostic Classification Model Framework

The evaluation of intervention effects is an important objective of educational research. One way to evaluate the effectiveness of an intervention is to conduct an experiment that assigns individuals to control and treatment groups. In the context of pretest/posttest designed studies, this is referred to as a control‐group pretest/posttest design. The transition diagnostic classification model (TDCM) was recently developed to assess growth, defined as change in attribute mastery status over time, in a diagnostic classification model framework. The TDCM, however, does not model multiple groups, and therefore is not able to analyze data from a control‐group pretest/posttest designed experiment. In this study, we extend the TDCM to model multiple groups, thereby enabling the examination of group‐differential growth in attribute mastery and the evaluation of intervention effects. The utility of the multigroup TDCM is demonstrated in the evaluation of an innovative instructional method in mathematics education.     

The influence of successive matches on match-running performance during an under-23 international soccer tournament: The necessity of individual analysis

This study investigated the effects of successive matches on match-running in elite under-23 soccer players during an international tournament. Match-running data was collected using a semi-automated multi-camera tracking system during an international under-23 tournament from all participating outfield players. Players who played 100% of all group stage matches were included (3 matches separated by 72 h, n = 44). Differences in match-running performance between matches were identified using a generalised linear mixed model. There were no clear effects for total, walking, jogging, running, high-speed running and sprinting distance between matches 1 and 3 (effect size (ES); ?0.32 to 0.05). Positional analysis found that sprint distance was largely maintained from matches 1 to 3 across all positions. Attackers had a moderate decrease in total, jogging and running distance between matches 1 and 3 (ES; ?0.72 to ?0.66). Classifying players as increasers or decreasers in match-running revealed that match-running changes are susceptible to individual differences. Sprint performance appears to be maintained over successive matches regardless of playing position. However, reductions in other match-running categories vary between positions. Changes in match-running over successive matches affect individuals differently; thus, players should be monitored on an individual basis.     

Six-year body composition change in male elite senior rugby league players

This study investigated the change in body composition and bone mineral content (BMC) of senior rugby league (RL) players between 2008 and 2014. Twelve male professional RL players (age, 24.6 ± 4.0 years; stature, 183.4 ± 8.4 cm) received a dual-energy X-ray absorptiometry scan during preseason in 2008 and 2014. Between 2008 and 2014, very likely increases in leg lean mass (LM), total trunk and leg BMC, and a likely increase in arm BMC and possible increases in body mass (BM), total and trunk fat mass (FM), and total, trunk and arm LM were observed. Unlikely decreases and unclear changes in leg and arm FM were also found. Large negative correlations were observed between age and BM (r = ?0.72), LM (r = ?0.70), FM (r = ?0.61) and BMC (r = ?0.84) change. Three participants (19.1 ± 1.6 years) increased LM by 7.0–9.3 kg. Younger players had the largest increases in LM during this period, although an older player (30-year old) still increased LM. Differences in body composition change were also observed for participants of the same age, thus contextual factors should be considered. This study demonstrates the individuality of body composition changes in senior professional rugby players, while considering the potential change in young athletes.     

Are habitual runners physically inactive?

The World Health Organisation’s (WHO) physical activity guidelines recommend 150min/week of moderate- to vigorous-intensity physical activity (MVPA) accumulated in 10 min bouts. To see whether people performing habitual exercise for recreation meet these guidelines, 25 long-distance runners [mean 67 km/wk], 25 joggers [mean 28 km/wk], and 20 sedentary adults wore an ActiGraph GT3X+ accelerometer for 7 days. Sedentary time and bouts were similar in runners and sedentary adults (p > 0.46). Sedentary adults performed 20 ± 16 min/day of MVPA (usual bout duration (W50%): 9.53 ± 3.45min), with joggers and runners performing 45 ± 31min (W50%: 16.92 ± 9.53min) and 83 ± 58min (W50%: 20.35 ± 8.85min), respectively (p ≤ 0.001 versus sedentary group). Data showed that 65% of the sedentary group, 32% of joggers and 4% of long-distance runners did not meet the WHO guideline for MVPA. Failure to meet the guideline was most prominent in, but not restricted to, runners who reported ≤50km running per week. Self-reported running does not ensure adults meet physical activity guidelines or offset daily sedentary behaviours. On the other hand, the sedentary group was very close in accumulating recommended bouts of MVPA in incidental activities. Future studies should assess whether modification of work and leisure physical activity would be more fruitful than encouraging recreational exercise per se in meeting physical activity guidelines.     

Differential training loads and individual fitness responses to pre-season in professional rugby union players

We aimed to compare differentiated training loads (TL) between fitness responders and non-responders to an eight-week pre-season training period in a squad of thirty-five professional rugby union players. Differential TL were calculated by multiplying player’s perceptions of breathlessness (sRPE-B) and leg muscle exertion (sRPE-L) with training duration for each completed session. Performance-based fitness measures included the Yo-Yo Intermittent Recovery Test Level 1 (YYIRTL1), 10-, 20-, and 30-m linear sprint times, countermovement jump height (CMJ) and predicted one-repetition maximum back squat (P1RM Squat). The proportion of responders (≥ 75% chance that the observed change in fitness was > typical error and smallest worthwhile change) were 37%, 50%, 52%, 82% and 70% for YYIRTL1, 20/30-m, 10-m, CMJ and P1RM Squat, respectively. Weekly sRPE-B-TL was very likely higher in YYIRTL1 responders (mean difference = 18%; ±90% confidence limits 11%), likely lower in 20/30-m (19%; ±20%) and 10-m (18%; ±17%) responders, and likely higher in CMJ responders (15%; ±16%). All other comparisons were unclear. Weekly sRPE-B discriminate between rugby union players who respond to pre-season training when compared with players who do not. Our findings support the collection of differential ratings of perceived exertion and the use of individual response analysis in team-sport athletes.     

The effects of acute carbohydrate and caffeine feeding strategies on cycling efficiency

To assess the effect of carbohydrate and caffeine on gross efficiency (GE), 14 cyclists (V?O_2max 57.6 ± 6.3 ml.kg^?1.min^?1) completed 4 × 2-hour tests at a submaximal exercise intensity (60% Maximal Minute Power). Using a randomized, counter-balanced crossover design, participants consumed a standardised diet in the 3-days preceding each test and subsequently ingested either caffeine (CAF), carbohydrate (CHO), caffeine+carbohydrate (CAF+CHO) or water (W) during exercise whilst GE and plasma glucose were assessed at regular intervals (~30 mins). GE progressively decreased in the W condition but, whilst caffeine had no effect, this was significantly attenuated in both trials that involved carbohydrate feedings (W = ?1.78 ± 0.31%; CHO = ?0.70 ± 0.25%, p = 0.008; CAF+CHO = ?0.63 ± 0.27%, p = 0.023; CAF = ?1.12 ± 0.24%, p = 0.077). Blood glucose levels were significantly higher in carbohydrate ingestion conditions (CHO = 4.79 ± 0.67 mmol·L^?1, p < 0.001; CAF+CHO = 5.05 ± 0.81 mmol·L^?1, p < 0.001; CAF = 4.46 ± 0.75 mmol·L^?1; W = 4.20 ± 0.53 mmol·L^?1). Carbohydrate ingestion has a small but significant effect on exercise-induced reductions in GE, indicating that cyclists’ feeding strategy should be carefully monitored prior to and during assessment.