Whose reality counts? Local educators as researchers on the quality of primary education

This article describes a methodology that local educators can use to conduct structured analytic research on the quality of primary education. The methodology has been developed by four twenty-person teams of local educators who carried out studies in rural regions of Madagascar, Mozambique, Tanzania and Uganda. In addition to describing the methodology, the article presents short summaries of the researchers’ conclusions and recommendations. However, its main purpose is to share the methodology that has evolved. The methodology is qualitative, but a simple quantitative measure of relationship between binary variables (Yule’s Q) was used to test the researchers’ qualitative findings. It is this tool that provoked the most significant reflection among the researchers in each group. In general, the results of the four studies corroborate other research on the factors that influence student outcomes in primary schools in Sub-Saharan Africa. More importantly, the studies’ results demonstrate that the methodology offers practicing educators a tool that helps them define, collect, and rigorously analyse empirical information to reach shared insights about their schools and then to formulate practical recommendations about what to do to improve student learning.     

Disruption of temporal discrimination and the choose-short effect

The present experiment examined the effects of several disruptors on temporal discrimination. Pigeons responded under a 0-delay symbolic matching-to-sample procedure in which responses to one key color were reinforced following the presentation of four shorter sample durations, and responses to another key color were reinforced following the presentation of four longer sample durations. Steady-state performance was disrupted by presession feeding, intertrial-interval food, visual distraction, and extinction. All disruptors decreased temporal-discrimination accuracy. Analyses of the fitted cumulative normal functions indicated that decreases in accuracy were produced mainly by decreases in overall stimulus control rather than specific effects on timing. In addition, all disruptors selectively decreased accuracy on long-sample trials—a choose-short effect. This effect is interpreted in terms of decreased attention to the samples under disruption. Current theories of the choose-short effect do not appear to easily account for these results.     

Building next generation video game collections in academic libraries

Most academic libraries do not yet have gaming collections, let alone gaming services and facilities that support the unique and growing teaching and research needs of campus environments. Academic libraries in particular need to start thinking about developing the next generation of gaming collections and services. This article examines the experiences in developing an academic library gaming initiative at a large research university, and works towards identifying the questions academic libraries need to be asking and the issues that need investigating in order to map out a path for developing next generation gaming collections that will meet the needs of academic instructors and researchers in the coming decade, and take advantage of the unique opportunities gaming and gaming technology provide.     

A Sport Education Fitness Season’s Impact on Students’ Fitness Levels,Knowledge, and In-Class Physical Activity

Purpose: The purpose of this study was to determine the extent to which a sport education season of fitness could provide students with recommended levels of in-class moderate-to-vigorous physical activity (MVPA) while also increasing students’ fitness knowledge and fitness achievement. Method: One hundred and sixty-six 5th-grade students (76 boys, 90 girls) participated in a 20-lesson season called “CrossFit Challenge” during a 4-week period. The Progressive Aerobic Cardiovascular Endurance Run, push-ups, and curl-ups tests of the FITNESSGRAM® were used to assess fitness at pretest and posttest, while fitness knowledge was assessed through a validated, grade-appropriate test of health-related fitness knowledge (HRF). Physical activity was measured with Actigraph GT3X triaxial accelerometers. Results: Results indicated a significant time effect for all fitness tests and the knowledge test. Across the entire season, the students spent an average of 54.5% of lesson time engaged in MVPA, irrespective of the type of lesson (instruction, free practice, or competition). Conclusions: The results suggest that configuring the key principles of sport education within a unit of fitness is an efficient model for providing students with the opportunity to improve fitness skill and HRF knowledge while attaining recommended levels of MVPA.     

Bone mineral density in triathletes over a competitive season

There is evidence from previous cross-sectional studies that high volumes of certain sports, including running, swimming and cycling, may have a negative impact on bone mineral density. The aim of the present study was to evaluate prospectively the effects of high athletic training in individuals who engage in high volumes of all three of these activities (triathletes). Bone mineral density for the total body, arms and legs was determined by dual-energy X-ray absorptiometry in 21 competitive triathletes (9 men, 12 women) at the beginning of the training season and 24 weeks later. Age, body mass index, calcium intake and training volume were also recorded to examine potential mediators of bone mineral density change. Men had greater bone mineral density at all sites than women. No significant changes were observed over the 24 weeks for either total body or leg bone mineral density. Bone mineral density in both arms increased by approximately 2% in men ( P ? 0.03), but no change was observed for women. Change in bone mineral density at all sites was unrelated to age, body mass index, calcium intake and training volume. The results suggest that adverse changes in bone mineral density do not occur over the course of 6 months of training in competitive triathletes.