The field of education has undergone a significant transformation due to the rapid advancements in Artificial Intelligence (AI). Among the various AI technologies, Knowledge Graphs (KGs) using Natural Language Processing (NLP) have emerged as powerful visualization tools for integrating multifaceted information. In the context of university education, the availability of numerous specialized courses and complicated learning resources often leads to inferior learning outcomes for students. In this paper, we propose an automated framework for knowledge extraction, visual KG construction, and graph fusion, tailored for the major of Electronic Information. Furthermore, we perform data analysis to investigate the correlation degree and relationship between courses, rank hot knowledge concepts, and explore the intersection of courses. Our objective is to enhance the learning efficiency of students and to explore new educational paradigms enabled by AI. The proposed framework is expected to enable students to better understand and appreciate the intricacies of their field of study by providing them with a comprehensive understanding of the relationships between the various concepts and courses.
Advancing Quantum Information Science Pre-College Education: The Case for Learning Sciences Collaboration
School of Computing（计算学院）；University of Pittsburgh（匹兹堡大学）；Graduate School of Education（教育研究生院）；Stanford University（斯坦福大学）；Department of Psychology（心理学系）
"Everyone's using it, but no one is allowed to talk about it": College Students' Experiences Navigating the Higher Education Environment in a Generative AI World
Information School, University of Washington（华盛顿大学信息学院）
Use of AI Tools: Guidelines to Maintain Academic Integrity in Computing Colleges
Faculty of computer and information System, Islamic University of Madina, Saudi Arabia（伊斯兰麦地那大学计算机与信息系统学院）；Faculty of Artificial Intelligence Multimedia University, Malaysia（马来西亚多媒体大学人工智能学院）
Readying Medical Students for Medical AI: The Need to Embed AI Ethics Education
Applied Artificial Intelligence Institute, Deakin University（迪肯大学应用人工智能研究所）；Centre for AI and Digital Ethics, School of Computing and Information Systems, The University of Melbourne（墨尔本大学计算与信息系统学院人工智能与数字伦理中心）
Equity in the Use of ChatGPT for the Classroom: A Comparison of the Accuracy and Precision of ChatGPT 3.5 vs. ChatGPT4 with Respect to Statistics and Data Science Exams
