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This experiment extended previous findings on whether model characteristics affect attentional subprocesses and mediate performance changes in an observational learning setting. College women (N = 75) were randomly assigned to groups in a 2 x 2 (Cueing by Model Similarity) factorial design or to a no-model control group. To assess attentional differences, subjects were cued either prior to or subsequent to a demonstration as to model characteristics, and model similarity was manipulated by having subjects view a similar or dissimilar model. All subjects saw the same videotaped demonstration, only their perceptions of model characteristics were manipulated. Subjects performed 20 performance trials in Phase 1 with outcome knowledge of results (KR) and, after a 1-rnin rest period, were given 10 more performance trials without KR in Phase 2. The results from Phase 1 indicated that subjects performed better after watching a model they perceived to be similar than after one they perceived as dissimilar. Phase 2 data indicated that all subjects were performing similarly in terms of outcome scores but that the control group was using a different strategy than the demonstration groups. The investigation found support for performance differences dependent on model characteristics and pointed to the need to examine more than outcome scores when assessing observational learning effects.

The primary purpose of this experiment was to determine if model characteristics influence observer performance by exerting their prime influence on the attentional phase of observational learning as predicted by Bandura (1969). A second purpose was to determine whether model characteristics affected actual amount learned or whether merely performance levels were affected by this manipulation. There were two experimental phases. During phase 1, model status (high or low) and time of cueing (pre or post demonstration) were manipulated to test performance and attentional effects of model characteristics. During phase 2, subjects were offered an incentive before performance trials in an attempt to make a learning-versus-performance distinction. Phase 1 results indicated the subjects who viewed a high status model performed better than those viewing a low status model. The lack of any significant cueing effect suggested that model characteristics did not exert their prime influence on the attentional stage of observational learning. There were no group differences during phase 2, suggesting that performance but not actual amount learned was affected by the model status manipulation.

Although self-modeling has been effective in modifying behaviors in a variety of settings, little research has been completed in the physical domain. The purpose of this study was to test the effectiveness of self-modeling on performance and self-efficacy using a sport skill and to explore the cognitive processes underlying self-modeling. A multiple baseline single-subject design was used wherein five intermediate level volleyball players were given a self-modeling intervention. Performance outcome results indicated that self-modeling may contribute to increases in serve accuracy. Performance form and selfefficacy results were inconclusive. Using a think-aloud protocol, it was noted that although the participants found the images of themselves “shocking,” the images command cognitive resources. Postintervention interviews revealed that participants found the self-modeling intervention useful and that it led to changes in behavior and motivation.

The present study compared the effects of two types of modeling, self- and other-modeling, on learning elementary swimming skills. Specifically, potential differences between the two modeling conditions in swimming performance, swimming self-efficacy, and state anxiety were investigated. Participants were adult volunteers from a college community. Ages ranged from 20 to 58. Each participant took five individual swimming lessons. Results indicated that participants in the self-modeling condition demonstrated better swimming performance by the fourth swim session than participants in the other-modeling condition. No differences were found between modeling conditions on either swimming self-efficacy or state anxiety. Potential reasons for the difference in performance are identified and discussed.

The present study examined the potential interaction effects of using different instructional strategies with intrinsically and extrinsically motivated youths. Subjects whose motivation to participate in sports was either one of intrinsic mastery or extrinsic mastery were randomly placed in one of two instructional groups: knowledge of results (KR) or knowledge of performance (KP). All four groups received a videotaped, modeled demonstration of the skill to be learned, the tennis forehand. Subjects participated in a 3-day acquisition period and a 1-day testing phase, during which both form and outcome scores were recorded. Analysis of acquisition outcome scores yielded no significant differences between motivational orientation or instructional groups. Multivariate analysis of the test phase outcome and form scores revealed significant group differences, as well as significant group-by-motivation and group-by-blocks interactions. Subsequent discriminant analyses indicated that form scores were more affected than outcome scores by the instructional and motivational group manipulations. The interaction results of the test phase supported the prediction of different performance effects as a function of motivational orientation and instructional strategy.

Over the past decade, institutions of higher education have been forced to become more innovative and entrepreneurial, seeking creative solutions to budget challenges. This has been particularly important within kinesiology programs, which represent one of the largest growing sectors of higher education over the past 10–15 years. In preparation for the 2016 American Kinesiology Association (AKA) Leadership Workshop, a survey was administered by the AKA to capture key institutional classifications (i.e., Carnegie classification, institutional size, public vs. private designation) and department chair or designated administrator perceptions on entrepreneurial issues relevant to their unit. Sixty-eight of 881 units surveyed responded, yielding a response rate of 7.7%. The majority of respondents (67%) indicated a unit funding model that was based on the previous year’s level (i.e., historical budget model). While the majority of respondents reported that their unit is provided with “adequate to plentiful” resources (59%), this varied widely based on institutional classification. Specifically, baccalaureate institutions (Chi-square 18.054, p < .001) and institutions with < 5,000 students (Chi-square 10.433, p & .015) had the least favorable perceptions of unit resource allocation. For the majority of entrepreneurial activities and partnerships (5 of 8 targeted questions), ≥ 50% of the respondents reported “no involvement.” There was a significant mismatch between actual vs. expected time spent by the department chair on fundraising activities (Chi-square 4.627, p = .031), with higher expectations than actual time spent on fundraising. In summary, the AKA survey suggests that there is tremendous heterogeneity in perceptions of and participation in entrepreneurial activities within kinesiology, and that there remains strategic areas of opportunity within the field.

In 1988, Andersen and Williams proposed a model to explain the stress-injury relationship. The present study tested portions of this framework by investigating frequency and severity of injury occurrence in track and field athletes from four NCAA Division I and II universities. Personality characteristics (locus of control and sport competition trait anxiety), history of stressors (life stress, daily hassles, and past injury), and moderating variables (coping resources and social support) were assessed before the season began. Discriminant analyses indicated that four variables (coping resources, negative life stress, social support, and competitive anxiety) differentiated the severity groups. For injury frequency, coping resources and positive life stress differentiated the groups.

This paper offers direction and guidance to help departments develop fair and equitable search, evaluation, and retention strategies for their faculty. Included is how to attract a diverse candidate pool and successfully recruit diverse candidates. In addition, the paper provides guidelines about evaluating faculty members, emphasizing the need for formative evaluation that offers faculty ample opportunities, resources, and support systems for improving their performance before any summative evaluations administered by a department or college. Finally, the paper presents retention stratagems as guidelines to help departments support and retain their high-quality faculty members. Achieving the goals of recruitment, retention, and advancement requires the involvement and leadership of university officers, school deans, department chairs/heads, and faculty.