Teaching outdoor and adventure activities: an investigation of a primary school physical education professional development p

 
Correlates of Physical Activity
Table 4.3 gives item examples and scoring information for all measures assessing the 
correlates of physical activity. The ‘School Day Affect’ measure asked children to rate, 
on a 4-point Likert scale how ‘another day of school’ made them feel first thing in the 
morning when they woke up. 
From a list of twelve subjects, children were asked to indicate their first second 
and third favourite school subject from a total of twelve choices - English, Art, Social 
Personal and Health Education (SPHE), Physical Education (PE), Maths, Music, Drama, 
Irish, Religion, Geography, History and Science. 
Enjoyment of pastimes (specified as games/activities) was first assessed using a 
six-item instrument. Children were asked to evaluate their feelings in relation to three 
sedentary activities, namely, watching TV, playing fun games like statues and playing 
computer games and three games/activities, namely, playing team games like basketball, 
playing running games like stuck in the mud or tag and getting out of breath while 
swimming, cycling or running. These findings are not reported here but are available in 
Appendix A.
Enjoyment of physical activity was assessed using an 8-item questionnaire.
Item one reads ‘You like playing games with your friends’, to which the child indicated 
their level of agreement with the statement on a 4 point scale with endpoints ranging 
from ‘no’ to ‘yes’. Level of enjoyment was determined by the aggregate score of all 
items (range 8-32), a high score indicated a high level of enjoyment.
 
Data Analysis 
Statistical analysis was undertaken using SPSS (Statistical Package for Social Sciences) 
for Windows, version 14.0. Data were manually and statistically searched for 
unexpected values and original data were consulted in order to clarify any unusual set.
Whole sample and where appropriate gender- and age-specific means and standard 
deviations were calculated. Data are presented as means, standard deviations and 
percentages where appropriate. The Pearson, chi square statistics with standardised 
residuals, was used to investigate any categorical relationships in the data. Relevant 
effect sizes were calculated and reported as r-value. An r-value of 0.10, 0.30 and 0.50 

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represented small, medium and large effect sizes respectively (Field, 2005). Mann-
Whitney tests were used to compare enjoyment levels by gender. Distance was entered 
into a bivariate logistic regression model that predicted active versus inactive 
commuting to school, and controlled for gender and age.