A student's grade evaluation model for network teaching system based on BP algorithm
The development of network technology is promoting the rapid transformation of human education mode. How to properly and effectively evaluate a student's grade in the new education environment is a difficult problem. In the paper, firstly, the characteristics of student learning in the network...
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creator | Xia Jun Zhang Yinshuo Wang Peng |
description | The development of network technology is promoting the rapid transformation of human education mode. How to properly and effectively evaluate a student's grade in the new education environment is a difficult problem. In the paper, firstly, the characteristics of student learning in the network teaching are introduced. Then, a student's grade evaluation model based on the characteristics of network teaching is designed, and the BP network with three-layer structure is used to evaluate the student's grade after trained with some representative samples. Lastly, the result shows that the training process is changing to the convergence, and the convergence effect is good. The model is helpful to give some suggestions for a student changing his learning strategies and learning contents in the next step, reminding him timely to adjust his learning schedule and learning methods. |
doi_str_mv | 10.1109/MIC.2013.6758022 |
format | Conference Proceeding |
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How to properly and effectively evaluate a student's grade in the new education environment is a difficult problem. In the paper, firstly, the characteristics of student learning in the network teaching are introduced. Then, a student's grade evaluation model based on the characteristics of network teaching is designed, and the BP network with three-layer structure is used to evaluate the student's grade after trained with some representative samples. Lastly, the result shows that the training process is changing to the convergence, and the convergence effect is good. The model is helpful to give some suggestions for a student changing his learning strategies and learning contents in the next step, reminding him timely to adjust his learning schedule and learning methods.</description><identifier>EISBN: 9781479913909</identifier><identifier>EISBN: 1479913901</identifier><identifier>EISBN: 9781479913923</identifier><identifier>EISBN: 1479913928</identifier><identifier>DOI: 10.1109/MIC.2013.6758022</identifier><language>eng</language><publisher>IEEE</publisher><subject>BP algorithm ; grade evaluation model ; MATLAB ; network teaching system ; Neurons</subject><ispartof>Proceedings of 2013 2nd International Conference on Measurement, Information and Control, 2013, Vol.1, p.542-545</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6758022$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27923,54918</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6758022$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Xia Jun</creatorcontrib><creatorcontrib>Zhang Yinshuo</creatorcontrib><creatorcontrib>Wang Peng</creatorcontrib><title>A student's grade evaluation model for network teaching system based on BP algorithm</title><title>Proceedings of 2013 2nd International Conference on Measurement, Information and Control</title><addtitle>MIC</addtitle><description>The development of network technology is promoting the rapid transformation of human education mode. How to properly and effectively evaluate a student's grade in the new education environment is a difficult problem. In the paper, firstly, the characteristics of student learning in the network teaching are introduced. Then, a student's grade evaluation model based on the characteristics of network teaching is designed, and the BP network with three-layer structure is used to evaluate the student's grade after trained with some representative samples. Lastly, the result shows that the training process is changing to the convergence, and the convergence effect is good. The model is helpful to give some suggestions for a student changing his learning strategies and learning contents in the next step, reminding him timely to adjust his learning schedule and learning methods.</description><subject>BP algorithm</subject><subject>grade evaluation model</subject><subject>MATLAB</subject><subject>network teaching system</subject><subject>Neurons</subject><isbn>9781479913909</isbn><isbn>1479913901</isbn><isbn>9781479913923</isbn><isbn>1479913928</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjztPwzAURs2ABCrZkVi8MSVc24kfY4l4VCqCIXvlxNdpIA9ku6D-eyrR6Syfjr5DyC2DgjEwD2-buuDARCFVpYHzC5IZpVmpjGHCgLkiWYyfAMCUqioG16RZ05gODud0H2kfrEOKP3Y82DQsM50WhyP1S6Azpt8lfNGEttsPc0_jMSacaGsjOnqaPn5QO_ZLGNJ-uiGX3o4RszNXpHl-aurXfPv-sqnX23wwkHJpQLS6VIJ7qbzyWioQCMZI1znk0Frgp4zu9LTSVmMpoJNli67kSnvvxIrc_WsHRNx9h2Gy4bg7p4s_i6NOdw</recordid><startdate>201308</startdate><enddate>201308</enddate><creator>Xia Jun</creator><creator>Zhang Yinshuo</creator><creator>Wang Peng</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201308</creationdate><title>A student's grade evaluation model for network teaching system based on BP algorithm</title><author>Xia Jun ; Zhang Yinshuo ; Wang Peng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-6903b84732f67f7f86703e0996dcde20ba02758c75558a8e430c64bed4278ffd3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>BP algorithm</topic><topic>grade evaluation model</topic><topic>MATLAB</topic><topic>network teaching system</topic><topic>Neurons</topic><toplevel>online_resources</toplevel><creatorcontrib>Xia Jun</creatorcontrib><creatorcontrib>Zhang Yinshuo</creatorcontrib><creatorcontrib>Wang Peng</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xia Jun</au><au>Zhang Yinshuo</au><au>Wang Peng</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A student's grade evaluation model for network teaching system based on BP algorithm</atitle><btitle>Proceedings of 2013 2nd International Conference on Measurement, Information and Control</btitle><stitle>MIC</stitle><date>2013-08</date><risdate>2013</risdate><volume>1</volume><spage>542</spage><epage>545</epage><pages>542-545</pages><eisbn>9781479913909</eisbn><eisbn>1479913901</eisbn><eisbn>9781479913923</eisbn><eisbn>1479913928</eisbn><abstract>The development of network technology is promoting the rapid transformation of human education mode. How to properly and effectively evaluate a student's grade in the new education environment is a difficult problem. In the paper, firstly, the characteristics of student learning in the network teaching are introduced. Then, a student's grade evaluation model based on the characteristics of network teaching is designed, and the BP network with three-layer structure is used to evaluate the student's grade after trained with some representative samples. Lastly, the result shows that the training process is changing to the convergence, and the convergence effect is good. The model is helpful to give some suggestions for a student changing his learning strategies and learning contents in the next step, reminding him timely to adjust his learning schedule and learning methods.</abstract><pub>IEEE</pub><doi>10.1109/MIC.2013.6758022</doi><tpages>4</tpages></addata></record> |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | BP algorithm grade evaluation model MATLAB network teaching system Neurons |
title | A student's grade evaluation model for network teaching system based on BP algorithm |
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