Education Data-Driven Online Course Optimization Mechanism for College Student
During the recent epidemic period of COVID-19, online courses have become an important learning form for college students. However, online learning cannot communicate face to face in class and position students’ abilities accurately, and there are many problems and limitations such as one-way evalua...
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| Veröffentlicht in: | Mobile information systems 2021, Vol.2021, p.1-8 |
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| container_title | Mobile information systems |
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| creator | Wang, Ziqiao Yu, Ningning |
| description | During the recent epidemic period of COVID-19, online courses have become an important learning form for college students. However, online learning cannot communicate face to face in class and position students’ abilities accurately, and there are many problems and limitations such as one-way evaluation, for example, neglecting of process evaluation and simple evaluation form. Therefore, how to construct the evaluation system of online course teaching and make effective use of the evaluation mechanism becomes an urgent problem. Based on the big data mining of online course evaluation data, the online course evaluation optimization architecture based on process evaluation is proposed. The optimization of online course evaluation is analyzed from online course evaluation data and student comments using deep learning and collaborative filtering technology. This includes improving teacher teaching and improving student learning efficiency. Data experiment proves that the proposed algorithm can provide an optimal evaluation strategy, guarantee the students’ learning quality, and improve the efficiency of online course. |
| doi_str_mv | 10.1155/2021/5545621 |
| format | Article |
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However, online learning cannot communicate face to face in class and position students’ abilities accurately, and there are many problems and limitations such as one-way evaluation, for example, neglecting of process evaluation and simple evaluation form. Therefore, how to construct the evaluation system of online course teaching and make effective use of the evaluation mechanism becomes an urgent problem. Based on the big data mining of online course evaluation data, the online course evaluation optimization architecture based on process evaluation is proposed. The optimization of online course evaluation is analyzed from online course evaluation data and student comments using deep learning and collaborative filtering technology. This includes improving teacher teaching and improving student learning efficiency. Data experiment proves that the proposed algorithm can provide an optimal evaluation strategy, guarantee the students’ learning quality, and improve the efficiency of online course.</description><identifier>ISSN: 1574-017X</identifier><identifier>EISSN: 1875-905X</identifier><identifier>DOI: 10.1155/2021/5545621</identifier><language>eng</language><publisher>Amsterdam: Hindawi</publisher><subject>Accuracy ; Algorithms ; Big Data ; CAI ; Collaboration ; Colleges & universities ; Computer assisted instruction ; Coronaviruses ; COVID-19 ; Curricula ; Data mining ; Education ; Feedback ; Knowledge ; Learning ; Machine learning ; Online instruction ; Optimization ; Students ; Teachers ; Tutoring</subject><ispartof>Mobile information systems, 2021, Vol.2021, p.1-8</ispartof><rights>Copyright © 2021 Ziqiao Wang and Ningning Yu.</rights><rights>Copyright © 2021 Ziqiao Wang and Ningning Yu. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-2f796ebcdcb5edd2399c452a34e1b04925d92270675862b33bce1ac2485f467c3</citedby><cites>FETCH-LOGICAL-c337t-2f796ebcdcb5edd2399c452a34e1b04925d92270675862b33bce1ac2485f467c3</cites><orcidid>0000-0002-7570-0648</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,4024,27923,27924,27925</link.rule.ids></links><search><contributor>Lv, Jianhui</contributor><contributor>Jianhui Lv</contributor><creatorcontrib>Wang, Ziqiao</creatorcontrib><creatorcontrib>Yu, Ningning</creatorcontrib><title>Education Data-Driven Online Course Optimization Mechanism for College Student</title><title>Mobile information systems</title><description>During the recent epidemic period of COVID-19, online courses have become an important learning form for college students. 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Data experiment proves that the proposed algorithm can provide an optimal evaluation strategy, guarantee the students’ learning quality, and improve the efficiency of online course.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Big Data</subject><subject>CAI</subject><subject>Collaboration</subject><subject>Colleges & universities</subject><subject>Computer assisted instruction</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Curricula</subject><subject>Data mining</subject><subject>Education</subject><subject>Feedback</subject><subject>Knowledge</subject><subject>Learning</subject><subject>Machine learning</subject><subject>Online instruction</subject><subject>Optimization</subject><subject>Students</subject><subject>Teachers</subject><subject>Tutoring</subject><issn>1574-017X</issn><issn>1875-905X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><recordid>eNp90D1PwzAQBmALgUQpbPyASIwQ6q-LmxG15UMqZACkbpFjO9RV6hTbAcGvJ1U6M90Nj947vQhdEnxLCMCEYkomABwySo7QiEwFpDmG1XG_g-ApJmJ1is5C2GCcYQZihF4WulMy2tYlcxllOvf2y7ikcI11Jpm1nQ8mKXbRbu3vwJ6NWktnwzapW9-LpjEfJnmNnTYunqOTWjbBXBzmGL3fL95mj-myeHia3S1TxZiIKa1FnplKaVWB0ZqyPFccqGTckArznILOKRU4EzDNaMVYpQyRivIp1DwTio3R1ZC78-1nZ0IsN_2rrj9ZUsCMAaGc9OpmUMq3IXhTlztvt9L_lASX-8bKfWPlobGeXw98bZ2W3_Z__QffkGoO</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Wang, Ziqiao</creator><creator>Yu, Ningning</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-7570-0648</orcidid></search><sort><creationdate>2021</creationdate><title>Education Data-Driven Online Course Optimization Mechanism for College Student</title><author>Wang, Ziqiao ; Yu, Ningning</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-2f796ebcdcb5edd2399c452a34e1b04925d92270675862b33bce1ac2485f467c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Big Data</topic><topic>CAI</topic><topic>Collaboration</topic><topic>Colleges & universities</topic><topic>Computer assisted instruction</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Curricula</topic><topic>Data mining</topic><topic>Education</topic><topic>Feedback</topic><topic>Knowledge</topic><topic>Learning</topic><topic>Machine learning</topic><topic>Online instruction</topic><topic>Optimization</topic><topic>Students</topic><topic>Teachers</topic><topic>Tutoring</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Ziqiao</creatorcontrib><creatorcontrib>Yu, Ningning</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mobile information systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Ziqiao</au><au>Yu, Ningning</au><au>Lv, Jianhui</au><au>Jianhui Lv</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Education Data-Driven Online Course Optimization Mechanism for College Student</atitle><jtitle>Mobile information systems</jtitle><date>2021</date><risdate>2021</risdate><volume>2021</volume><spage>1</spage><epage>8</epage><pages>1-8</pages><issn>1574-017X</issn><eissn>1875-905X</eissn><abstract>During the recent epidemic period of COVID-19, online courses have become an important learning form for college students. However, online learning cannot communicate face to face in class and position students’ abilities accurately, and there are many problems and limitations such as one-way evaluation, for example, neglecting of process evaluation and simple evaluation form. Therefore, how to construct the evaluation system of online course teaching and make effective use of the evaluation mechanism becomes an urgent problem. Based on the big data mining of online course evaluation data, the online course evaluation optimization architecture based on process evaluation is proposed. The optimization of online course evaluation is analyzed from online course evaluation data and student comments using deep learning and collaborative filtering technology. This includes improving teacher teaching and improving student learning efficiency. 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| language | eng |
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| source | Wiley Online Library; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Accuracy Algorithms Big Data CAI Collaboration Colleges & universities Computer assisted instruction Coronaviruses COVID-19 Curricula Data mining Education Feedback Knowledge Learning Machine learning Online instruction Optimization Students Teachers Tutoring |
| title | Education Data-Driven Online Course Optimization Mechanism for College Student |
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