Domain Question Mapping (DQM)

This project develops an innovative approach to constructing Domain Question Maps (DQMs) to address challenges in automatically creating concept maps from unstructured educational materials. By leveraging publicly available question-answering datasets, the study fine-tunes pre-trained language models for question generation and uses a textbook's hierarchical outline to train a specificity classification model. This method formulates specific questions aligned with learning objectives, enhancing knowledge representation and learner engagement. DQMs effectively generate educational questions and identify hierarchical relationships, facilitating personalized and adaptive learning.

This project develops an innovative approach to constructing Domain Question Maps (DQMs) to address challenges in automatically creating concept maps from unstructured educational materials.

By leveraging publicly available question-answering datasets, the study fine-tunes pre-trained language models for question generation and uses a textbook’s hierarchical outline to train a specificity classification model. This method formulates specific questions aligned with learning objectives, enhancing knowledge representation and learner engagement.

DQMs effectively generate educational questions and identify hierarchical relationships, facilitating personalized and adaptive learning — marking a significant advancement over traditional concept maps.

Code: github.com/YesNLP/Automated-Domain-Question-Map-Construction

Paper: arXiv:2601.07062