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891.
Kelly H. Ahuna Christine Gray Tinnesz Carol VanZile-Tamsen 《Innovative Higher Education》2011,36(4):249-259
In the late 1980s a large northeastern university implemented a critical thinking course for undergraduate students. Combining
insights from cognitive psychology and philosophy, this class was designed to give students concrete strategies to promote
self-regulated learning and ensure academic success. The analyses in this study are based on university warehouse data for
three consecutive entering freshmen cohorts, resulting in a sample of 9,665 students, 1900 of whom had successfully completed
the course. Results show these students are more likely to be retained or to exit successfully by the second, third, fourth,
and fifth year as compared to those students who do not complete the course. 相似文献
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HealthStages is a health promotion program of OASIS, a national arts and humanities, health, and volunteer organization for older adults. It was developed by a unique not-for-profit organization and university collaboration using state-of-the art curricula and current research to enhance successful aging. Rowe and Kahn's (1997) model of successful aging provided the overall framework for the project, and Prochaska and DiClemente (1983) Stages of Change component of the Transtheoretical Model of Behavior Change guided our curriculum development, research questions, and program evaluation. HealthStages uses evaluations of individual courses to assess participant expectations, new areas of interest, and appropriateness of courses. Outcome measures assess participants' changes as a result of particular courses within the program. Using a longitudinal survey design, a sample of HealthStages participants is compared to a random sample of older adults not involved in the program, comparisons are made on their health, health behavior, healthcare utilization, activity, and functioning over time. HealthStages is a comprehensive health promotion program designed to provide courses in a variety of topic areas at differing levels of readiness to change and to measure changes over time. The unique collaboration offers benefits to OASIS and its members as well as to faculty and students of Washington University. 相似文献
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Evenson KR Catellier DJ Gill K Ondrak KS McMurray RG 《Journal of sports sciences》2008,26(14):1557-1565
A calibration study was conducted to determine the threshold counts for two commonly used accelerometers, the ActiGraph and the Actical, to classify activities by intensity in children 5 to 8 years of age. Thirty-three children wore both accelerometers and a COSMED portable metabolic system during 15 min of rest and then performed up to nine different activities for 7 min each, on two separate days in the laboratory. Oxygen consumption was measured on a breath-by-breath basis, and accelerometer data were collected in 15-s epochs. Using receiver operating characteristic curve (ROC) analysis, cutpoints that maximised both sensitivity and specificity were determined for sedentary, moderate and vigorous activities. For both accelerometers, discrimination of sedentary behaviour was almost perfect, with the area under the ROC curve at or exceeding 0.98. For both the ActiGraph and Actical, the discrimination of moderate (0.85 and 0.86, respectively) and vigorous activity (0.83 and 0.86, respectively) was acceptable, but not as precise as for sedentary behaviour. This calibration study, using indirect calorimetry, suggests that the two accelerometers can be used to distinguish differing levels of physical activity intensity as well as inactivity among children 5 to 8 years of age. 相似文献
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Kelly de Jesus Helon Vicente Hultmann Ayala Leandro dos Santos Coelho João Paulo Vilas-Boas Ricardo Jorge Pinto Fernandes 《Journal of sports sciences》2019,37(13):1512-1520
We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networks (RBF) and linear models (LM) accuracy to predict the centre of mass (CM) horizontal speed at low-moderate, heavy and severe swimming intensities using physiological and biomechanical dataset. Ten trained male swimmers completed a 7 × 200 m front crawl protocol (0.05 m.s?1 increments and 30 s intervals) to assess expiratory gases and blood lactate concentrations. Two surface and four underwater cameras recorded independent images subsequently processed focusing a three-dimensional reconstruction of two upper limb cycles at 25 and 175 m laps. Eight physiological and 13 biomechanical variables were inputted to predict CM horizontal speed. MLP, RBF and LM were implemented with the Levenberg-Marquardt algorithm (feed forward with a six-neuron hidden layer), orthogonal least squares algorithm and decomposition of matrices. MLP revealed higher prediction error than LM at low-moderate intensity (2.43 ± 1.44 and 1.67 ± 0.60%), MLP and RBF depicted lower mean absolute percentage errors than LM at heavy intensity (2.45 ± 1.61, 1.82 ± 0.92 and 3.72 ± 1.67%) and RBF neural networks registered lower errors than MLP and LM at severe intensity (2.78 ± 0.96, 3.89 ± 1.78 and 4.47 ± 2.36%). Artificial neural networks are suitable for speed model-fit at heavy and severe swimming intensities when considering physiological and biomechanical background. 相似文献