Wei Wu, Shuangqi Yang, Feng Tian, Xin Wei, Yagang Pan
{"title":"Knowledge graph enhanced recommendation for semantic structure construction and feedback in online learning","authors":"Wei Wu, Shuangqi Yang, Feng Tian, Xin Wei, Yagang Pan","doi":"10.1016/j.phycom.2024.102590","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents a knowledge graph-enhanced recommendation system, inspired by constructivist principles, to address challenges like information overload and fragmented knowledge in online education. The system transforms unstructured information into interconnected knowledge frameworks, facilitating semantic comprehension, personalized recommendations, and cognitive feedback. Aligned with constructivist principles, the platform encourages students to actively construct personalized knowledge structures, enhancing cognitive engagement through adaptive feedback. Experiments with higher education students demonstrate its potential to improve learning interest, knowledge retention, and adaptive feedback, supporting advanced semantic and cognitive learning paradigms.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"69 ","pages":"Article 102590"},"PeriodicalIF":2.0000,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Communication","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1874490724003082","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a knowledge graph-enhanced recommendation system, inspired by constructivist principles, to address challenges like information overload and fragmented knowledge in online education. The system transforms unstructured information into interconnected knowledge frameworks, facilitating semantic comprehension, personalized recommendations, and cognitive feedback. Aligned with constructivist principles, the platform encourages students to actively construct personalized knowledge structures, enhancing cognitive engagement through adaptive feedback. Experiments with higher education students demonstrate its potential to improve learning interest, knowledge retention, and adaptive feedback, supporting advanced semantic and cognitive learning paradigms.
期刊介绍：
PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published.
Topics of interest include but are not limited to:
Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.
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