The Effects of Motion Math: Bounce on Students’ Fraction Knowledge

National assessments suggest that many students do not display proficiency with fractions. Considering that time and materials are precious resources, many educators are looking to use technology to provide supplemental instruction with low demand on the instructor. The current study utilized a multiple-baseline design to examine the effects of the Motion Math: Bounce application on the fraction quantity comparison and number line placement skills of three fifth-grade students. Results indicate that Motion Math: Bounce improved the quantity comparison skills of all three participants and the number line skills of one participant. Additionally, all three participants made improvements from pre- to posttest on a measure of general fraction knowledge. Implications for future research and intervention implementation are discussed.     

Accelerometer and GPS Data to Analyze Built Environments and Physical Activity

ABSTRACT

Purpose: Most built environment studies have quantified characteristics of the areas around participants’ homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1–4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.     

Test–retest reliability of a battery of field-based health-related fitness measures for adolescents

Abstract

The main aim of this study was to determine the test–retest reliability of existing tests of health-related fitness. Participants (mean age 14.8 years, s = 0.4) were 42 boys and 26 girls who completed the study assessments on two occasions separated by one week. The following tests were conducted: bioelectrical impedance analysis (BIA) to calculate percent body fat, leg dynamometer, 90° push-up, 7-stage sit-up, and wall squat tests. Intra-class correlation (ICC), paired samples t-tests, and typical error expressed as a coefficient of variation were calculated. The mean percent body fat intra-class correlation coefficient was similar for boys (ICC = 0.95) and girls (ICC = 0.93), but the mean coefficient of variation was considerably higher for boys than girls (22.2% vs. 12.2%). The boys' coefficients of variation for the tests of muscular fitness ranged from 9.0% for the leg dynamometer test to 26.5% for the timed wall squat test. The girls' coefficients of variation ranged from 17.1% for the sit-up test to 21.4% for the push-up test. Although the BIA machine produced reliable estimates of percent body fat, the tests of muscular fitness resulted in high systematic error, suggesting that these measures may require an extensive familiarization phase before the results can be considered reliable.