The central aim of the present investigation is to empirically investigate the impact of Arts participation on students’ academic and non-academic outcomes (see Figure 1.7). In the context of the study, the proposed hypothesised model features Arts participation constructs, academic outcomes, non-academic outcomes, covariates, and prior variance. Arts participation is categorised into three areas:
1. School Arts participation (i.e., in-school Arts tuition);
2. Home Arts participation (i.e., parent-child Arts interaction and home-based Arts resources); and
3. Community Arts participation (i.e., receptive Arts participation, active Arts participation, and external Arts tuition).
The academic outcomes consist of nine constructs:
1. adaptive motivation 2. impeding motivation 3. maladaptive motivation 4. personal best (PB) goals 5. academic intentions 6. academic buoyancy 7. school enjoyment 8. class participation 9. homework completion
The non-academic outcomes consist of five constructs:
1. peer relations 2. self-esteem 3. life meaning 4. life satisfaction 5. poor mental health
The study also controls for the presence of six covariates:
1. gender 2. age 3. language background 4. parental/caregiver education 5. Aboriginality 6. prior achievement
Finally, the study’s longitudinal design controls for prior variance via two sets of constructs: academic outcomes and non-academic outcomes.
The hypothesised model is assessed cross-sectionally at two time points, approximately one year apart. Analysis then assesses the Arts model via a longitudinal design. There are then three sets of analyses, each assessing a different aspect of time: cross-sectional Time 1, cross- sectional Time 2, and longitudinal (matched) Time 1 and Time 2.
There are likewise three interconnected components of hypothesis testing within the current project. The first concerns the cross-sectional testing of the hypothesised Arts model (i.e., Time 1 sample and Time 2 sample). The second component relates to the longitudinal testing of the hypothesised Arts model (i.e., matched Time 1 and Time 2 sample). The third is the cross- sectional and longitudinal construct validation of the quantitative instrumentation. Hypotheses under each of these components are presented below.
Cross-sectional testing of the hypothesised Arts model
The Literature Review has traversed the research terrain, suggesting that Arts
participation is associated with a range of academic and non-academic outcomes. Accordingly, a main aim of this study is to test hypothesised relations between Arts participation factors and students’ academic and non-academic outcomes at Times 1 and 2. Structural equation modelling (SEM) is conducted separately for Time 1 data and Time 2 data. The empirical evaluation of the hypothesised Arts model, as well as an examination of the model’s stability for each cross- sectional data set (i.e., Time 1 and Time 2), is conducted using suitable methodological designs and statistical procedures, focusing on latent variable modelling. In line with this, two
hypotheses are proposed for both Times 1 and 2.
In terms of academic outcomes:
1a. School, home, and community Arts participation will positively predict adaptive motivation, PB goals, academic intentions, academic buoyancy, school enjoyment, class participation, and homework completion - and negatively predict impeding motivation
and maladaptive motivation, after controlling for socio-demographic factors and prior achievement.
In terms of non-academic outcomes:
1b. School, home, and community Arts participation will positively predict peer relations, self-esteem, life meaning, and life satisfaction - and negatively predict poor mental health, after controlling for socio-demographic factors and prior achievement.
Longitudinal testing of the hypothesised Arts model
The aim of the next empirical component of this study involves the important
longitudinal examination of the hypothesised Arts model. The assessment of this longitudinal SEM Arts model is to identify key paths between Arts participation and outcome factors, controlling for prior variance in outcome factors. In line with this, two hypotheses are proposed for the longitudinal Arts model.
In terms of academic outcomes:
2a. School, home, and community Arts participation will predict gains in adaptive motivation, PB goals, academic intentions, academic buoyancy, school enjoyment, class participation, and homework completion - and predict declines in impeding motivation and maladaptive motivation, after controlling for socio-demographic factors, prior achievement, and prior variance in outcome measures (i.e., Time 1 academic outcomes).
In terms of non-academic outcomes:
2b. School, home, and community Arts participation will predict gains in peer relations, self-esteem, life meaning, and life satisfaction - and predict declines in poor mental health, after controlling for socio-demographic factors, prior achievement, and prior variance in outcome measures (i.e., Time 1 non-academic outcomes).
For both academic and non-academic outcomes:
2c. Auto-regressive paths (i.e., between parallel Time 1 and Time 2 outcomes - such as Time 1 academic buoyancy to Time 2 academic buoyancy) will be positive and of moderate to strong valence.
Cross-sectional and longitudinal construct validation of the instrumentation
Although not central to the substantive concerns of this study, the cross-sectional and longitudinal Arts models will inevitably rely on the sound measurement underpinning them. Accordingly, prior to estimating these models, the analysis will seek to establish the
psychometric properties to these measures. In line with this, no hypotheses are advanced in relation to psychometric properties; instead, they take the form of open research questions, including:
3a. What are the distributional and reliability properties of central scales?
3b. What is the nature of the factor structure underpinning the set of instrumentation relevant to the hypothesised Arts model?
3c. Do multigroup confirmatory factor analysis (CFA) tests of invariance demonstrate the invariance of key measurement parameters (i.e., factor loadings, factor
correlations, and uniquenesses) as a function of gender, school level, language background, and testing phase (Time 1 and Time 2)?
Chapter Summary
In summary, this chapter has detailed the hypotheses central to the present study,
exploring the role of school, home, and community Arts participation in students’ academic and non-academic outcomes. The Arts model will be tested through cross-sectional and longitudinal data, appropriate methodological designs, and multivariate statistical procedures. Broadly, the model holds that Arts participation will positively predict adaptive academic and non-academic outcomes and negatively predict maladaptive academic and non-academic outcomes. This model and its component hypotheses are the centrepiece of the current project.
CHAPTER 3: METHODOLOGY: SAMPLE, MEASURES, PROCEDURE, AND