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We propose and implement a novel intelligent tutoring system, called RadarMath, to support intelligent and personalized learning for math education. The system provides the services including automatic grading and personalized learning guidance. Specifically, two automatic grading models are designed to accomplish the tasks for scoring the text-answer and formula-answer questions respectively. An education-oriented knowledge graph with the individual learner’s knowledge state is used as the key tool for guiding the personalized learning process. The system demonstrates how the relevant AI techniques could be applied in today's intelligent tutoring systems.

Moral education refers to the cultivation of ideals, moral quality, culture, and discipline. One of its main tasks is to analyze students’ problem behaviors and identify their underlying need deficiencies. Previous psychological research has focused on studying how distinct factors affect psychological needs and problem behaviors. However, these findings have provided only scattered guidelines for identifying students’ need deficiencies, which are difficult for inexperienced teachers and parents to apply systematically. To address these issues, we attempt to answer two key research questions in this work. First, how do we define a theoretical framework so that the psychological research findings can be systematically applied to identify students’ need deficiencies? Second, can the latest AI technologies be employed to identify such need deficiencies automatically? To answer these research questions, we first build a theoretical framework to summarize all the factors relevant to the students’ problem behaviors and need deficiencies. After that, we propose and develop a task-oriented dialogue system that can properly inquire about different aspects of students’ information and automatically infer their need deficiencies. We conduct comprehensive experiments to evaluate the system’s performance with real-life cases. The results show that the built dialogue system could effectively serve as a diagnostic tool to identify the students’ need deficiencies.

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