论文标题
流程挖掘和基于规则的AI的合并方法，用于高等教育的研究计划和监测
A Combined Approach of Process Mining and Rule-based AI for Study Planning and Monitoring in Higher Education
论文作者
论文摘要
本文提出了一种使用过程挖掘方法和基于规则的人工智能方法来分析和理解基于校园管理系统数据和研究计划模型的学生的研究路径的方法。过程挖掘技术用于表征成功的研究路径，并检测和可视化与预期计划的偏差。这些见解与从检查法规中提取的相应研究计划的建议和要求相结合。在这里，事件计算和答案集编程用于提供研究计划的模型，以支持计划和一致性检查，同时就可能的研究计划提供反馈。结合使用，过程采矿和基于规则的人工智能用于通过得出规则和建议来指导学生以更高成功率的更合适的学习路径来支持研究计划和监测。将实施两种申请，一个用于学生，另一项用于研究计划设计师。
This paper presents an approach of using methods of process mining and rule-based artificial intelligence to analyze and understand study paths of students based on campus management system data and study program models. Process mining techniques are used to characterize successful study paths, as well as to detect and visualize deviations from expected plans. These insights are combined with recommendations and requirements of the corresponding study programs extracted from examination regulations. Here, event calculus and answer set programming are used to provide models of the study programs which support planning and conformance checking while providing feedback on possible study plan violations. In its combination, process mining and rule-based artificial intelligence are used to support study planning and monitoring by deriving rules and recommendations for guiding students to more suitable study paths with higher success rates. Two applications will be implemented, one for students and one for study program designers.
