Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer

Based on the positioning of training application-oriented and innovative talents in the field of big data, this article aims to address the current situation where the theoretical system of big data course is not complete, the experimental system is unreasonable, and the assessment indicators are no...

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Main Authors: Ning Liu, Yeyangyi Xiang, Fei Wang, Shuyu Cao
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2024-01-01
Series:Cognitive Robotics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S266724132400017X
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author Ning Liu
Yeyangyi Xiang
Fei Wang
Shuyu Cao
author_facet Ning Liu
Yeyangyi Xiang
Fei Wang
Shuyu Cao
author_sort Ning Liu
collection DOAJ
description Based on the positioning of training application-oriented and innovative talents in the field of big data, this article aims to address the current situation where the theoretical system of big data course is not complete, the experimental system is unreasonable, and the assessment indicators are not perfect. A Transformer based “1 + 1 + N” big data course unified system and multidimensional evaluation model is constructed, reforms and practices are carried out in terms of improving the course theoretical system, increasing unit experiments and comprehensive experiment cases, and improving process assessment. The Transformer based multi-dimensional evaluation model of the big data course is proposed to solve the current problems of heavy theory and light practice, heavy standardization assessment and light innovation ability training in the course. The proposed course unified system and multidimensional evaluation model had achieved remarkable results, effectively increasing students’ construction of the big data professional knowledge system, enhancing students’ subjective initiative in learning the course, and significantly improving students’ innovative ability and ability to comprehensively solve practical problems.
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id doaj-art-2c3cb1c8dde645ce99c5ac1193b9599b
institution OA Journals
issn 2667-2413
language English
publishDate 2024-01-01
publisher KeAi Communications Co. Ltd.
record_format Article
series Cognitive Robotics
spelling doaj-art-2c3cb1c8dde645ce99c5ac1193b9599b2025-08-20T02:35:43ZengKeAi Communications Co. Ltd.Cognitive Robotics2667-24132024-01-01423724410.1016/j.cogr.2024.11.003Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced TransformerNing Liu0Yeyangyi Xiang1Fei Wang2Shuyu Cao3Corresponding author.; School of Information Science and Technology, Beijing Forestry University, No.35 Qinghua East Road, Haidian District, Beijing, 100091, ChinaSchool of Information Science and Technology, Beijing Forestry University, No.35 Qinghua East Road, Haidian District, Beijing, 100091, ChinaSchool of Information Science and Technology, Beijing Forestry University, No.35 Qinghua East Road, Haidian District, Beijing, 100091, ChinaSchool of Information Science and Technology, Beijing Forestry University, No.35 Qinghua East Road, Haidian District, Beijing, 100091, ChinaBased on the positioning of training application-oriented and innovative talents in the field of big data, this article aims to address the current situation where the theoretical system of big data course is not complete, the experimental system is unreasonable, and the assessment indicators are not perfect. A Transformer based “1 + 1 + N” big data course unified system and multidimensional evaluation model is constructed, reforms and practices are carried out in terms of improving the course theoretical system, increasing unit experiments and comprehensive experiment cases, and improving process assessment. The Transformer based multi-dimensional evaluation model of the big data course is proposed to solve the current problems of heavy theory and light practice, heavy standardization assessment and light innovation ability training in the course. The proposed course unified system and multidimensional evaluation model had achieved remarkable results, effectively increasing students’ construction of the big data professional knowledge system, enhancing students’ subjective initiative in learning the course, and significantly improving students’ innovative ability and ability to comprehensively solve practical problems.http://www.sciencedirect.com/science/article/pii/S266724132400017XBig dataTransformerMultidimensional evaluation modelKnowledge GraphProcess Assessment
spellingShingle Ning Liu
Yeyangyi Xiang
Fei Wang
Shuyu Cao
Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer
Cognitive Robotics
Big data
Transformer
Multidimensional evaluation model
Knowledge Graph
Process Assessment
title Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer
title_full Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer
title_fullStr Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer
title_full_unstemmed Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer
title_short Big Data Course Multidimensional Evaluation Model based on Knowledge Graph enhanced Transformer
title_sort big data course multidimensional evaluation model based on knowledge graph enhanced transformer
topic Big data
Transformer
Multidimensional evaluation model
Knowledge Graph
Process Assessment
url http://www.sciencedirect.com/science/article/pii/S266724132400017X
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AT yeyangyixiang bigdatacoursemultidimensionalevaluationmodelbasedonknowledgegraphenhancedtransformer
AT feiwang bigdatacoursemultidimensionalevaluationmodelbasedonknowledgegraphenhancedtransformer
AT shuyucao bigdatacoursemultidimensionalevaluationmodelbasedonknowledgegraphenhancedtransformer