s 2010 pp 1_110.indd 39 2/12/2010 5:40:14 PM A0 RQES: March 2010 Supplement ing physical education and sport. Although several reviews have examined the use of ABA principles in sport and physical education, this effect has been uncertain. The purposes of the current meta-analysis were (a) to examine the effect of interventions based in ABA on acquiring skills in both sport and physical education settings, and (b) to identify if moderating variables influenced the overall effect of the interventions. Six electronic databases (i.e., WilsonWeb, ProQuest, Google Scholar, Psyc Info, Academic Search Premier, and Oregon PDF in Health and Performance) and reference lists of included articles were searched. Also, known behavior analysis journals (e.g., Journal of Applied Behavior Analysis; Behavior Modification; and Journal of Behavioral Education) were searched. The main keywords used in the search were: behavior analysis, physical education, sport, and athlete/athletic. Of the 49 studies identified, 22 fit the inclusion criteria. From these studies, 188 effect sizes (ES) were calculated using the odds ratio formula. A random effects model was used to calculate the mean ES and the 95% CI. Moderator analyses on gender, age, ABA principal used, setting, and type of skill were also conducted. The overall ES log odds ratio (ESLOR) was 1.49 (95% confidence interval = 1.34, 1.65), indicating ABA interventions had a large effect on participants’ skill acquisition. The overall ESLOR was heterogeneous (Q = 1235.62, df = 187, p < .001) indicating the necessity to analyze moderator variables. Moderator analyses found ABA interventions produced greater effects on male participants (ESLOR = 1.59) than female participants (1.41) and greater effects on college and adults (1.81) than on elementary or secondary school-age participants (1.18 and 1.40, respectively). Also, goal setting interventions had the greatest effect (1.90) while peer-based interventions had the lowest (1.31). Interventions to improve tennis skills had a greater effect (2.06) than for football (1.75), other (1.57), basketball (1.02), and volleyball skills (0.35). And, interventions implemented in mainstream physical education settings had a greater effect (1.55) than those implemented in sport (1.51), other (1.28), or integrated physical education settings (1.19). The current meta-analysis indicated ABA interventions had a large effect on the acquisition of skills in athletic and physical education settings. Both coaches and physical educators should note that methods of instruction based in ABA can positively influence the skill acquisition of their athletes and students. Congruence of Physical Education Policy With Practice in Alabama Eugene F. Asola and Matthew Curtner-SmithF, The University of Alabama (efasola@bama.ua.edu) Case study work on the occupational socialization of physical education teachers in Alabama suggests that there is a major incongruence between how official policy describes physical education should be and actual practice. To counter the negative effects of occupational socialization and break the cycle of nonteaching in the subject, Curtner-Smith (2009) suggested that sport pedagogists follow the lead of John Evans and Dawn Penney in the United Kingdom (e.g., see Penney, 2008) and Judith Rink and her associates in the United States (e.g., see Rink & Mitchell, 2002) and take more of an activist approach in their work by engaging in research with a political/policy focus. The purposes of this study, therefore, were to: (a) describe what was occurring in the name of physical education in the state of Alabama, and (b) illustrate discrepancies between teachers’ practice and national and state policy texts. Two hundred forty-eight physical education teachers completed the Physical Education in Alabama Survey (PEAS), a 20-item instrument designed to obtain demographic and programmatic information about physical education teachers and physical education teaching in Alabama. One hundred and thirty seven of these teachers worked in elementary schools, 74 worked in middle schools, and 37 worked in high schools. Frequency counts were made and percentages calculated for questions on the PEAS requiring a forced-choice answer. Analytic induction was used to code and categorize data generated by open-ended questions. Frequency counts were then made and percentages calculated for each inductive category. Key findings were that physical education programs in Alabama were often congruent with national and state policy in terms of teachers’ role emphasis, stated goals and objectives, and assessment techniques when formal evaluation was carried out. Time allocated for the subject was also equal to or exceeded national and state minimums at the elementary and middle school levels. Conversely, areas of noncompliance or which often contradicted national and state policy texts were formal grading criteria, the allocation of time for pupils to engage in “free play,” and content. The number of teachers not certified to teach physical education or conducting formal evaluations was also a concern. Class sizes were much larger than suggested or required maximums at many elementary and middle schools. Major implications included the need for improved physical education teacher education, the state to enforce its own existing policy, and the state to provide more rigorous guidelines regarding content and curriculum models. Training and Use of FITNESSGRAM® by Inservice Physical Educators Debra Ballinger, Towson University (dballinger@towson.edu) Many teachers and programs have adopted the use of FITNESSGRAM® as the assessment tool of choice. Although the reliability and validity of the program has been well established, what hasn’t been systematically determined are the practices employed by inservice teachers, once the assessments have been made. Specifically, the purpose of this project was to determine, through a survey of physical education teachers (N = 65), the common practices employed using the FITNESSGRAM 8.0 battery, compare the knowledge and practice of physical education teachers by years of teaching, formal training, and experience, and examine the strategies employed by teachers to prepare students (physically and motivationally) for FITNESSGRAM. Following IRB approval, a survey was developed, piloted, revised, and disseminated via direct contact, district physical education supervisor recruitment, and the state professional association newsletter, to teachers. An incentive for completion was provided. Although the results are subject to self-report bias, it was established that age and years of service were not significant predictors of use. Although the data are descriptive, implications for future training are evidenced by these results: while 97% of the teachers had a computer in their office, 28% Abstracts 2010 pp 1_110.indd 40 2/12/2010 5:40:14 PMs 2010 pp 1_110.indd 40 2/12/2010 5:40:14 PM RQES: March 2010 Supplement A1 of the respondents had never received formal training in FITNESSGRAM®; less than half (47%) reported using Physical Best Activities more than twice annually; 82% didn’t give homework related to fitness; 82% used goal setting strategies based on fitness scores; and 70% reported that fitness scores were not incorporated into their grading schema. The barriers to implementation were: teacher time for testing (46%) and entering scores (41%), and computer accessibility for students (59%). This was further exemplified by 52% of teachers reporting they did not allow students to use computers for entering scores or printing reports, yet 63% reportedly would do so if they had the web based program for student access, and 41% stated that students like using the computers. With respect to usage, over 90% of respondents used test protocols for curl-ups, push-ups, flexibility and the Progressive Aerobic Cardiovascular Endurance Run tests, but 89% failed to assess BMI, skinfolds, or other indices of body composition. Most teachers didn’t use Activity Gram or Activity Log programs, which implies the programs are used for assessment but not for monitoring physical activity. From these data, advanced training is warranted for experienced teachers for full implementation of the tools available from FITNESSGRAM®, specifically with respect to ancillary use for monitoring physical activity, promoting self-responsibility and self-assessment, and for monitoring body composition. Examining Students’ Conceptions of Exercise Intensity: A Mental Models Perspective Marina Bonello, Manhattanville College, and Catherine D. EnnisF, University of North Carolina–Greensboro (drmarinabonello@gmail.com) Students’ learning of concepts, such as the FITT principle (frequency, intensity, time, type), can enhance their adoption of physically active lifestyles (Corbin, 2002). Yet, scholars (Stewart & Mitchell, 2003) documented that students’ understanding of the “intensity” concept central to current fitness recommendations is problematic. Ennis (2007) maintains scholars’ use of new cognitive learning theories utilized in Science can inform examinations into students’ science-based fitness conceptions. In Framework Theory of Conceptual Change (FTTC), Vosniadou (2002) hypothesizes students’ contextbased academic beliefs (ontological, epistemic) unconsciously influence the mental models they create to represent their knowledge. In physical education (PE), little is known about the academic beliefs students hold and how these influence students’ developing mental models. The purpose of this study was to apply FTTC to a contextualized examination of sixthgrade students’ mental models of “intensity” and academic beliefs. Nine students from two schools (N = 18) completed multimethod interviews before and after their sports-based fitness units. Contextual data collection included document collection, field observations (n = 24), and teacher interviews. Data were analyzed inductivel
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