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Sheng Bi; Zeyi Miao; Qizhi Min – IEEE Transactions on Learning Technologies, 2025
The objective of question generation from knowledge graphs (KGQG) is to create coherent and answerable questions from a given subgraph and a specified answer entity. KGQG has garnered significant attention due to its pivotal role in enhancing online education. Encoder-decoder architectures have advanced traditional KGQG approaches. However, these…
Descriptors: Grammar, Models, Questioning Techniques, Graphs
Yuchen Wang; Juxiang Zhou; Zijie Li; Shu Zhang; Xiaoyu Han – IEEE Transactions on Learning Technologies, 2024
Graded reading is one of the important ways of English learning. How to automatically judge and grade the difficulty of the English reading corpus is of great significance for precision teaching and personalized learning. However, the current rule-based readability assessment methods have some limitations, such as low efficiency and poor accuracy.…
Descriptors: Computational Linguistics, Reading Materials, Readability, Semantics
Elizabeth Koh; Lishan Zhang; Alwyn Vwen Yen Lee; Hongye Wang – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence (AI) has the potential to revolutionize teaching and learning applications. This article examines the word cloud, a toolkit often used to scaffold teaching and learning for reflection, critical thinking, and content learning. Addressing the issues in traditional word clouds, semantic word clouds have been…
Descriptors: Vocabulary, Visual Aids, Electronic Publishing, Word Frequency