1. Introduction to the Test:
Purpose and Context of the Analysis:
A Kruskal-Wallis H test was conducted to determine if there were significant differences in [outcome] across three [groups], including [group names].
中文释义：
Kruskal-Wallis H 检验用于检验在 [依赖变量] 上是否存在 [组数] 个组之间的显著差异，测量工具为 [测量工具或方法]。
2. Results Reporting:
The Kruskal-Wallis H test revealed [a significant/no significant] difference in [dependent variable] between the [group(s)] on [dependent variable], χ²(df) = [value], p = [value].
中文释义：
Kruskal-Wallis H 检验揭示了在 [依赖变量] 上，[组别] 之间存在 [显著/不显著] 差异，χ²(df) = [值]，p = [值]。
If applicable, describe post-hoc analysis（事后检验）:
Post-hoc comparisons using [method] indicated that [Group A] had [significantly higher/lower] [dependent variable] than [Group B], [p-value]. [If no significant difference, indicate p-value.]
中文释义：
使用 [方法] 进行的事后比较表明，[组 A] 在 [依赖变量] 上显著高于/低于 [组 B]，p = [值]。
Effect Size (if applicable)效应量:
The effect size for the Kruskal-Wallis test was [effect size], indicating a [small/medium/large] effect.
中文释义：
Kruskal-Wallis 检验的效应量为 [效应量]，表明效应为 [小/中/大]。
3. Discussion and Interpretation:
Interpretation of Findings:
These results suggest that [group or method] led to significantly different [dependent variable], indicating [implication of results].
中文释义：
这些结果表明，[组别或方法] 导致了 [依赖变量] 显著的差异，说明 [结果的含义]。
Implications for Future Research or Practice:
These findings suggest that future studies should [recommendations for further investigation or application in the field].
中文释义：
这些发现表明，未来的研究应探讨混合学习方法中哪些具体要素有助于增加参与度，以及如何进一步优化这些方法。
1. Example:
The Kruskal-Wallis H test was conducted to determine if there were significant differences in the level of student engagement across three different teaching methods: traditional lectures, online learning, and blended learning. The dependent variable was student engagement, measured using a self-report scale.
2. Description of the Test:
Explain what the Kruskal-Wallis H test is and why it's used. For example, you can mention it as a non-parametric test used to compare differences between more than two independent groups when the dependent variable is ordinal or continuous but not normally distributed.
3. Results Section:
In the results section, report the test statistic (H), degrees of freedom (df), the p-value, and any post-hoc tests if applicable.
Example:
A Kruskal-Wallis H test was conducted to compare student engagement across three teaching methods. The test revealed a statistically significant difference in engagement levels, χ²(2) = 12.34, p < .01. Post-hoc pairwise comparisons using the Dunn-Bonferroni correction indicated that students in the blended learning group reported significantly higher engagement (M = 4.5) compared to those in the traditional lecture group (M = 2.8), p < .05. However, no significant difference was found between the online learning (M = 3.2) and traditional lecture groups, p = .12.
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