Data mining in education is steadily gaining momentum to explore the learning analytics because of its easy to use with any programming knowledge. This emerging method primarily focus on developing methods for handling and exploring voluminous information represented in distinct types of data. Deployment of data mining in education helps to better understand the synergy between the learning and educational settings established by the institutions to foster their learning activity. This work presents a data mining based virtual simulation experimental teaching system which provisions personalized interactive learning, real-world scene experimental training and comprehensive assessment of the learning effect. The proposed system employs interactive programming, automatic evaluation of experimental results, assessing the impact of teaching effectiveness with other modules. The work also provides a series of comprehensive cases and programming experiments apart from presenting the execution pages. The results indicate that this system can intuitively help students to improve their learning process, student participation and foster independent learning ability. The application of data mining alleviates the dependency on complex programming paradigms to make learning analytics, which is beneficial to both the teaching and learning communities.

教育中的数据挖掘由于其易于与任何编程知识一起使用而正在稳步获得探索学习分析的动力。这种新兴方法主要侧重于开发处理和探索不同类型数据所表示的大量信息的方法。在教育中部署数据挖掘有助于更好地了解机构为促进学习活动而建立的学习和教育环境之间的协同作用。提出了一种基于数据挖掘的虚拟仿真实验教学系统，提供个性化互动学习、真实场景实验训练和学习效果综合评估。该系统采用交互式编程，自动评估实验结果，与其他模块一起评估对教学效果的影响。作品除了展示执行页面之外，还提供了一系列全面的案例和编程实验。结果表明，该系统能够直观地帮助学生改善学习过程、学生参与度和培养自主学习能力。数据挖掘的应用减轻了对复杂编程范式的依赖来进行学习分析，这对教学和学习社区都有好处。