Concept maps have been widely utilized in education to depict knowledge structures and the interconnections between disciplinary concepts. Nonetheless, devising a computational method for automatically constructing a concept map from unstructured educational materials presents challenges due to the complexity and variability of educational content. We focus primarily on two challenges: (1) the lack of disciplinary concepts that are specifically designed for multi-level pedagogical purposes from low-order to high-order thinking, and (2) the limited availability of labeled data concerning disciplinary concepts and their interrelationships. To tackle these challenges, this research introduces an innovative approach for constructing Domain Question Maps (DQMs), rather than traditional concept maps. By formulating specific questions aligned with learning objectives, DQMs enhance knowledge representation and improve readiness for learner engagement. The findings indicate that the proposed method can effectively generate educational questions and discern hierarchical relationships among them, leading to structured question maps that facilitate personalized and adaptive learning in downstream applications.

翻译：概念图在教育领域已被广泛用于描绘知识结构以及学科概念间的相互联系。然而，由于教育内容的复杂性和多变性，设计一种能够从非结构化教育材料中自动构建概念图的计算方法仍面临挑战。我们主要关注两个挑战：（1）缺乏专门为从低阶到高阶思维的多层次教学目的而设计的学科概念；（2）关于学科概念及其相互关系的标注数据有限。为应对这些挑战，本研究提出了一种构建领域问题图（DQMs）的创新方法，以替代传统的概念图。通过设计与学习目标相一致的具体问题，DQMs增强了知识表征能力，并提升了学习者参与的预备性。研究结果表明，所提出的方法能够有效生成教育问题并识别问题间的层次关系，从而构建出结构化的问题图，有助于在下游应用中实现个性化和自适应学习。