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Jie Yang; Ehsan Latif; Yuze He; Xiaoming Zhai – Journal of Science Education and Technology, 2025
The development of explanations for scientific phenomena is crucial in science assessment. However, the scoring of students' written explanations is a challenging and resource-intensive process. Large language models (LLMs) have demonstrated the potential to address these challenges, particularly when the explanations are written in English, an…
Descriptors: Artificial Intelligence, Technology Uses in Education, Automation, Scoring
Quan Yang; Huajian Xin; Xuehua Ji; Fae Mai – International Journal of Web-Based Learning and Teaching Technologies, 2024
This article analyses the significance of ideological and political education for college students in Tibet and proposes a natural language model for an ideological education curriculum to improve the accuracy of students' document search. The segmentation results are optimized to enhance literature search accuracy, promoting the development of…
Descriptors: Universities, Geographic Regions, Educational Change, Educational Innovation
Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Question generation is an emerging research area of artificial intelligence in education. Question authoring tools are important in educational technologies, e.g., intelligent tutoring systems, as well as in dialogue systems. Approaches to generate factual questions, i.e., questions that have concrete answers, mainly make use of the syntactical…
Descriptors: Chinese, Questioning Techniques, Automation, Natural Language Processing