This research focuses on students’ satisfaction and on how students’ satisfaction relates to their performance and involvement in study activities in the e-classroom. Our research is a case study at the course level of a business and economics study programme at a private higher education institution in Slovenia. The study is based on decision-tree induction, a highly used algorithm in a variety of domains for knowledge discovery and pattern recognition using a data mining approach. The results revealed that students are less satisfied with a course when both the requirements for the involvement in the e-classroom and the workload are both high. Further, the average grade might not be of crucial importance when addressing student satisfaction. In our case, students are much more satisfied with a course when the average grades are high and when the workload is not so elevated and when a part of the workload moves to the e-classroom.

中文翻译：

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使用决策树预测学生的满意度

这项研究的重点是学生的满意度以及学生的满意度与他们在电子教室中的学习活动的表现和参与度之间的关系。我们的研究是在斯洛文尼亚私立高等教育机构的商业和经济学学习计划课程级别的案例研究。该研究基于决策树归纳，这是一种在各种领域中使用广泛的算法，用于使用数据挖掘方法进行知识发现和模式识别。结果显示，当参与电子课堂的要求和工作量都很高时，学生对课程的满意度较低。此外，在解决学生满意度问题时，平均成绩可能不是至关重要的。在我们的例子中，