The effectiveness of DataMed Analytics Tutor and the repeatability dataset of AI tools

DataQ1_3 Dataset: The DataQ1_3 dataset comprises three parts: Learning Effectiveness Evaluation (Q1), Learning Experience and Satisfaction Evaluation (Q2), and Open-ended Interviews (Q3). Q1 and Q2 consist of objective questions rated on a 1 to 5 Likert scale, where 1 indicates "strongly disagree" and 5 indicates "strongly agree." Q1 includes 7 items assessing students' performance and learning outcomes in data analysis tasks after using the AI-assisted tool. Q2, with 9 items, evaluates students' learning experience and their satisfaction with the AI teaching model. Q3 contains 4 open-ended questions to gather students' subjective feedback on preferences between AI-assisted tools and traditional teaching methods, changes in interest and confidence, and the strengths and weaknesses of the AI teaching model.Reliability and Consistency Tests Dataset: The Reliability and Consistency Tests dataset evaluates the reproducibility and reliability of the AI tool. The table records the standard answers for different questions alongside multiple AI-generated responses. Consistency metrics were calculated based on the accuracy ratings from evaluators. The results demonstrate high accuracy and consistency across multiple responses, with scores approaching 1, confirming the tool's reliability and stability in educational scenarios.DataQ1_3 数据集：该数据集由三部分构成，分别为学习效果评估（Q1）、学习体验与满意度评估（Q2）以及开放式访谈（Q3）。Q1与Q2均为采用1至5级李克特（Likert）量表评分的客观题，其中1代表“非常不同意”，5代表“非常同意”。Q1包含7个条目，用于评估学生使用人工智能辅助工具（AI-assisted tool）后，在数据分析任务中的表现与学习成果。Q2设有9个条目，用于评估学生的学习体验以及对人工智能教学模式的满意度。Q3包含4个开放式问题，用于收集学生针对人工智能辅助工具与传统教学方式的偏好、学习兴趣与信心的变化，以及人工智能教学模式的优缺点等内容的主观反馈。 信度与一致性测试数据集：该数据集用于评估该人工智能工具的可重复性与可靠性。该表格记录了不同问题的标准答案与多组人工智能生成的回复。基于评估人员给出的准确性评分计算一致性指标，结果显示多次回复的准确性与一致性均较高，得分接近1，证实了该工具在教育场景中的可靠性与稳定性。