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Pallavi Singh; Phat K. Huynh; Dang Nguyen; Trung Q. Le; Wilfrido Moreno – IEEE Transactions on Learning Technologies, 2025
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria integer programming (MCIP), which simultaneously accommodates multiple criteria, thereby innovatively addressing the complex task of…
Descriptors: Teamwork, Group Dynamics, Research Design, Models
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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
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Xueqiao Zhang; Chao Zhang; Jianwen Sun; Jun Xiao; Yi Yang; Yawei Luo – IEEE Transactions on Learning Technologies, 2025
Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…
Descriptors: Artificial Intelligence, Instructional Design, Technology Uses in Education, Cognitive Ability
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence