Statistical Data Compilation: Research Subject Demographics, Normality Tests, and MANOVA Results for Digital Citizenship Study Among Indonesian Elementary Students
Description
This dataset contains comprehensive statistical data from a research study examining the influence of blended learning models and internet self-efficacy (ISE) on digital citizenship attitudes among elementary school students in Indonesia. The data presents a factorial experimental design (2x2) with 288 total participants. The dataset includes demographic distribution of research subjects categorized by learning model (Blended Learning vs. Direct Instruction) and internet self-efficacy levels (High vs. Low), with further subdivision by gender. Statistical validation tests are provided, including Kolmogorov-Smirnov normality tests and Levene's homogeneity tests for all experimental groups, confirming the appropriateness of parametric statistical analysis. Pretest data t-test results establish baseline equivalence between experimental groups prior to intervention. The main analytical findings are presented through MANOVA results, showing significant main effects for both learning model and internet self-efficacy on digital citizenship attitudes, as well as a significant interaction effect between these variables. The dataset includes detailed hypothesis testing parameters and results for all three research objectives, alongside a visual representation of the relationships between research variables. This supplemental data supports the primary research paper by providing statistical evidence for the efficacy of blended learning approaches in developing digital citizenship attitudes, particularly among students with high internet self-efficacy.
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Steps to reproduce
To reproduce the analysis presented in this dataset, researchers should begin by recruiting 288 elementary school students from Indonesia and assigning them to experimental groups using a 2×2 factorial design. Students should be classified based on learning model (Blended Learning or Direct Instruction) and Internet Self-Efficacy level (High or Low), with demographic data recorded by gender for each group. Prior to experimental treatment, researchers should administer an Internet Self-Efficacy assessment to classify students accordingly, followed by a pretest measurement of Digital Citizenship Attitudes. Statistical validation through t-test analysis should be performed on pretest data to ensure no significant initial differences between groups. The experimental phase involves implementing the Blended Learning model with one group (n=145) and the Direct Instruction model with the control group (n=143), while maintaining consistent instructional content. After the intervention period, researchers should collect posttest data on Digital Citizenship Attitudes. Data validation should be conducted using Kolmogorov-Smirnov tests for normality and Levene's tests for homogeneity of variance across all experimental groups. The primary statistical analysis should utilize Multivariate Analysis of Variance (MANOVA) with Digital Citizenship Attitude as the dependent variable, examining both main effects and interaction effects between learning models and Internet Self-Efficacy levels. Hypothesis testing should evaluate the three research questions using the established significance threshold (p<0.05), followed by visualization and interpretation of the relationships between variables in the context of digital citizenship education among elementary students.
Institutions
- Universitas Negeri Malang Pascasarjana