3.8.1. Quantitative Data Analysis
Quantitative data analysis employed statistical methods appropriate for examining changes in measured variables and determining the significance of observed differences between the experimental and control groups. The analysis process included:
1. Descriptive Statistical Analysis:
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o Calculation of means, standard deviations, and ranges for all measured variables
o Examination of distribution characteristics and identification of potential outliers
o Generation of descriptive profiles for both experimental and control groups
2. Inferential Statistical Analysis:
o Paired t-tests to assess within-group changes from pre- to post-intervention
o Independent samples t-tests to compare between-group differences
o Analysis of Variance (ANOVA) to examine interactions between variables
o Analysis of Covariance (ANCOVA) to control for potential confounding variables
o Calculation of effect sizes (Cohen’s d) to determine practical significance
3. Reliability and Validity Analysis:
o Internal consistency assessment (Cronbach’s alpha) for survey instruments
o Inter-rater reliability testing for speech assessment rubrics
o Factor analysis to confirm construct validity of measurement tools
All quantitative analyses were conducted using SPSS software (Version 27), with a significance level of p < 0.05 established for hypothesis testing.
3.8.2. Qualitative Data Analysis
Qualitative data analysis followed a systematic approach to identify patterns, themes, and insights within participants’ subjective experiences. The analysis process included:
1. Thematic Analysis of Interview Data:
o Verbatim transcription of all recorded interviews
o Open coding to identify initial concepts and categories
o Axial coding to establish relationships between categories
o Selective coding to integrate categories around core themes
o Comparative analysis between experimental and control group narratives
o Identification of illustrative quotes representing key themes
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2. Content Analysis of Reflective Journals:
o Systematic coding of journal entries using both predetermined and emergent codes
o Tracking of development patterns over time
o Identification of critical incidents and transformative learning moments
o Analysis of metacognitive awareness and self-assessment accuracy
o Comparison of self-reported experiences with observational data
3. Observational Data Analysis:
o Structured coding of field notes using a predetermined observational framework
o Identification of patterns in participation, engagement, and skill application
o Documentation of pedagogical strategies and student responses
o Integration of observational insights with other data sources
Qualitative data analysis was facilitated using NVivo software (Version 12), which enabled systematic organization, coding, and retrieval of textual data.