This injury prevention program could potentially modify the flexibility, strength, and biomechanical properties associated with ACL injury and lower the athlete's risk for injury.

The purpose of this study was to investigate perceptions of the counseling needs of gifted children from the perspective of parents who sought help from a fee-based counseling center for gifted students. The counseling center provided assessment and educational and career guidance, as well as family social/emotional counseling, all of which were differentiated to meet the needs of gifted children ages 4-18. Participating parents completed intake forms that included a 47-item client problem inventory and were designed to assist the counseling process. One hundred and twenty of these problem inventories were analyzed to determine which counseling needs led parents to bring their children for counseling services and whether there were any differences in perceived needs among three different developmental levels of children (preschool, preadolescent, and adolescent). Results suggested that age had a statistically and practically significant effect on parent perceptions of career and child (psychosocial) concerns and a practically significant effect on school, family, and peer concerns. For all age groups, parents perceived their child’s greatest counseling need to be educational planning, followed closely by school concerns. Psychosocial concerns were also salient for parents of children older than 6. Career planning was important for parents of children older than 12. Peer and family concerns were less salient than the other categories of concern. The study suggests that gifted children do have unique needs for differentiated counseling services and that counseling services for gifted children should emphasize educational planning and be targeted to the needs of specific developmental levels.

A variety of theoretical perspectives describe the crucial behavioral roles of motivation and emotion, but how these interact with perceptions of social contexts and behaviors is less well understood. This study examined whether autonomous motivation mediated the relationship between perceived autonomy support and behavioral engagement in physical education and whether this mediating process was moderated by positive emotion. A sample of 592 Korean middle-school students (304 boys, 288 girls; M age = 14.0 yr., SD = 0.8) completed questionnaires. Autonomous motivation partially mediated the positive association between perceived autonomy support and behavioral engagement. Positive emotion moderated the relationship between autonomous motivation and behavioral engagement. This indirect link was stronger as positive emotion increased. These findings suggest the importance of integrating emotion into motivational processes to understand how and when perceived autonomy support is associated with behavioral engagement in physical education.

This study used a mailed questionnaire to examine the academic experiences of 497 international graduate students who were studying at an American university. Most students viewed their academic experience positively, although a majority did not believe the curriculum had an international focus. Fully 77% felt prepared to work in their home country following graduation, but only 32% planned to return home immediately after completing their degrees. Significant predictors of post-graduation plans included home region, field of study, and perceived preparedness to work at home and in the USA.

A substantial body of research has been conducted on variables relating to students' mathematics achievement with TIMSS. However, most studies have employed conventional statistical methods, and have focused on selected few indicators instead of utilizing hundreds of variables TIMSS provides. This study aimed to find a prediction model for students' mathematics achievement using as many TIMSS student and teacher variables as possible. Elastic net, the selected machine learning technique in this study, takes advantage of both LASSO and ridge in terms of variable selection and multicollinearity, respectively. A logistic regression model was also employed to predict TIMSS 2011 Korean 4th graders' mathematics achievement. Ten-fold cross-validation with mean squared error was employed to determine the elastic net regularization parameter. Among 162 TIMSS variables explored, 12 student and 5 teacher variables were selected in the elastic net model, and the prediction accuracy, sensitivity, and specificity were 76.06, 70.23, and 80.34%, respectively. This study showed that the elastic net method can be successfully applied to educational large-scale data by selecting a subset of variables with reasonable prediction accuracy and finding new variables to predict students' mathematics achievement. Newly found variables via machine learning can shed light on the existing theories from a totally different perspective, which in turn propagates creation of a new theory or complement of existing ones. This study also examined the current scale development convention from a machine learning perspective.