Utility of Students' Fitness Levels to Predict Academic Achievement: A Hierarchical Multiple Regression Analysis

California and many other states require students to pass an exit examination as a high school graduation requirement. Coupled with the exit examination requirement is school accountability to the state and the federal government. Despite academic interventions, many students continue to fail the exit examination resulting in not earning a diploma. The purpose of the study was to examine the possible utility of using ninth grade FITNESSGRAM results to predict 10th grade California High School Exit Examination (CAHSEE) scores in mathematics and English Language Arts (ELA). The results of the dissertation can be one data element used by school administrators to either give additional or less support for physical activity programs at school. The quantitative dissertation used a historical non-experimental design with a multiple hierarchical regression analysis while controlling for gender and ethnicity to either retain or reject the hypotheses. The participants were students in a suburban high school located in Southern California who completed the FITNESSGRAM in the ninth grade and at least one CAHSEE test in 10th grade. The predictor variable was FITNESSGRAM results and the outcome variables were CAHSEE mathematics and ELA scores. Hierarchical multiple regressions were computed to determine the level of predictor outcomes. Results supported each FITNESSGRAM event passed had a B = 8.06 for CAHSEE mathematics (p < .0005) and a B = 6.78 for CAHSEE ELA (p < .0005). The implications for this study suggest the utility of using fitness as a predictor of CAHSEE scores. The analysis supports retaining both alternative hypotheses while fulfilling the purpose of determining the utility of using FITNESSGRAM results to predict CAHSEE scores.