moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization
In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as we...
Gespeichert in:
| Veröffentlicht in: | Technology, knowledge and learning knowledge and learning, 2016-04, Vol.21 (1), p.75-98 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 98 |
|---|---|
| container_issue | 1 |
| container_start_page | 75 |
| container_title | Technology, knowledge and learning |
| container_volume | 21 |
| creator | Pardos, Zachary A. Whyte, Anthony Kao, Kevin |
| description | In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload format to enable reuse and replication of analytics results among instructors and researchers. We survey the evolving landscape of competing established and emerging data models, all of which are accommodated in the platform. Data model descriptions are provided to analytics authors who choose, much like with smartphone app stores, to write for any number of data models depending on their needs and the proliferation of the particular data model. Two case study examples of analytics and responsive visualizations based on different data models are described in the paper. The result is a simple but effective approach to learning analytics immediately applicable to X consortium MOOCs and beyond. |
| doi_str_mv | 10.1007/s10758-015-9268-2 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1773180792</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ericid>EJ1093410</ericid><sourcerecordid>3984476161</sourcerecordid><originalsourceid>FETCH-LOGICAL-c451t-3d00973779e0a64f226d1abc1377dd85f7de622eb968ff414cd2edca2ee6ed0a3</originalsourceid><addsrcrecordid>eNp1kF1LwzAUhosoOOZ-gBdCwNtVc9KPtN6NbX4x2PDrNqRJOjO6diYpOn-9KZXhjblITvK878nhDYJzwFeAMb22gGmShRiSMCdpFpKjYEAIQAgpxceHOiWnwcjaDfYrwSSLk0HwtW0a8bS6QfOaF5Wu12i5UzVaKG7q7japebV3Wlj0qd074nXPn5vWCIVWFXdlY7bIb2jGHUczbZ3RRet0U497t9V27I0SvWnb8kp_8w6eBSclr6wa_Z7D4PV2_jK9DxfLu4fpZBGKOAEXRhLjnEaU5grzNC4JSSXwQoB_kjJLSipVSogq8jQryxhiIYmSghOlUiUxj4bBZd93Z5qPVlnHNn52P5dlQGkEGaY58SroVcI01hpVsp3RW272DDDrMmZ9xsxnzLqMWee56D3KaHHQzx8B51EM2HPSc-tZvVbmz8__Nv0Bn9OI9Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1773180792</pqid></control><display><type>article</type><title>moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization</title><source>SpringerLink (Online service)</source><creator>Pardos, Zachary A. ; Whyte, Anthony ; Kao, Kevin</creator><creatorcontrib>Pardos, Zachary A. ; Whyte, Anthony ; Kao, Kevin</creatorcontrib><description>In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload format to enable reuse and replication of analytics results among instructors and researchers. We survey the evolving landscape of competing established and emerging data models, all of which are accommodated in the platform. Data model descriptions are provided to analytics authors who choose, much like with smartphone app stores, to write for any number of data models depending on their needs and the proliferation of the particular data model. Two case study examples of analytics and responsive visualizations based on different data models are described in the paper. The result is a simple but effective approach to learning analytics immediately applicable to X consortium MOOCs and beyond.</description><identifier>ISSN: 2211-1662</identifier><identifier>EISSN: 2211-1670</identifier><identifier>DOI: 10.1007/s10758-015-9268-2</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Case Studies ; Colleges & universities ; Creativity and Arts Education ; Data Analysis ; Data Collection ; Data models ; Education ; Educational Technology ; Higher education ; Large Group Instruction ; Learning analytics ; Learning and Instruction ; Mathematics Education ; Modularity ; MOOCs ; Online Courses ; Open learning ; Open Source Technology ; Privacy ; Science Education ; Technology Uses in Education ; Visualization</subject><ispartof>Technology, knowledge and learning, 2016-04, Vol.21 (1), p.75-98</ispartof><rights>Springer Science+Business Media Dordrecht 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c451t-3d00973779e0a64f226d1abc1377dd85f7de622eb968ff414cd2edca2ee6ed0a3</citedby><cites>FETCH-LOGICAL-c451t-3d00973779e0a64f226d1abc1377dd85f7de622eb968ff414cd2edca2ee6ed0a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10758-015-9268-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10758-015-9268-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1093410$$DView record in ERIC$$Hfree_for_read</backlink></links><search><creatorcontrib>Pardos, Zachary A.</creatorcontrib><creatorcontrib>Whyte, Anthony</creatorcontrib><creatorcontrib>Kao, Kevin</creatorcontrib><title>moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization</title><title>Technology, knowledge and learning</title><addtitle>Tech Know Learn</addtitle><description>In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload format to enable reuse and replication of analytics results among instructors and researchers. We survey the evolving landscape of competing established and emerging data models, all of which are accommodated in the platform. Data model descriptions are provided to analytics authors who choose, much like with smartphone app stores, to write for any number of data models depending on their needs and the proliferation of the particular data model. Two case study examples of analytics and responsive visualizations based on different data models are described in the paper. The result is a simple but effective approach to learning analytics immediately applicable to X consortium MOOCs and beyond.</description><subject>Case Studies</subject><subject>Colleges & universities</subject><subject>Creativity and Arts Education</subject><subject>Data Analysis</subject><subject>Data Collection</subject><subject>Data models</subject><subject>Education</subject><subject>Educational Technology</subject><subject>Higher education</subject><subject>Large Group Instruction</subject><subject>Learning analytics</subject><subject>Learning and Instruction</subject><subject>Mathematics Education</subject><subject>Modularity</subject><subject>MOOCs</subject><subject>Online Courses</subject><subject>Open learning</subject><subject>Open Source Technology</subject><subject>Privacy</subject><subject>Science Education</subject><subject>Technology Uses in Education</subject><subject>Visualization</subject><issn>2211-1662</issn><issn>2211-1670</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kF1LwzAUhosoOOZ-gBdCwNtVc9KPtN6NbX4x2PDrNqRJOjO6diYpOn-9KZXhjblITvK878nhDYJzwFeAMb22gGmShRiSMCdpFpKjYEAIQAgpxceHOiWnwcjaDfYrwSSLk0HwtW0a8bS6QfOaF5Wu12i5UzVaKG7q7japebV3Wlj0qd074nXPn5vWCIVWFXdlY7bIb2jGHUczbZ3RRet0U497t9V27I0SvWnb8kp_8w6eBSclr6wa_Z7D4PV2_jK9DxfLu4fpZBGKOAEXRhLjnEaU5grzNC4JSSXwQoB_kjJLSipVSogq8jQryxhiIYmSghOlUiUxj4bBZd93Z5qPVlnHNn52P5dlQGkEGaY58SroVcI01hpVsp3RW272DDDrMmZ9xsxnzLqMWee56D3KaHHQzx8B51EM2HPSc-tZvVbmz8__Nv0Bn9OI9Q</recordid><startdate>20160401</startdate><enddate>20160401</enddate><creator>Pardos, Zachary A.</creator><creator>Whyte, Anthony</creator><creator>Kao, Kevin</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7XB</scope><scope>88B</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CJNVE</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>M0N</scope><scope>M0P</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEDU</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20160401</creationdate><title>moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization</title><author>Pardos, Zachary A. ; Whyte, Anthony ; Kao, Kevin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-3d00973779e0a64f226d1abc1377dd85f7de622eb968ff414cd2edca2ee6ed0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Case Studies</topic><topic>Colleges & universities</topic><topic>Creativity and Arts Education</topic><topic>Data Analysis</topic><topic>Data Collection</topic><topic>Data models</topic><topic>Education</topic><topic>Educational Technology</topic><topic>Higher education</topic><topic>Large Group Instruction</topic><topic>Learning analytics</topic><topic>Learning and Instruction</topic><topic>Mathematics Education</topic><topic>Modularity</topic><topic>MOOCs</topic><topic>Online Courses</topic><topic>Open learning</topic><topic>Open Source Technology</topic><topic>Privacy</topic><topic>Science Education</topic><topic>Technology Uses in Education</topic><topic>Visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pardos, Zachary A.</creatorcontrib><creatorcontrib>Whyte, Anthony</creatorcontrib><creatorcontrib>Kao, Kevin</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection【Remote access available】</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Education Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Education Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer science database</collection><collection>Computing Database</collection><collection>Education Database</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Technology, knowledge and learning</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pardos, Zachary A.</au><au>Whyte, Anthony</au><au>Kao, Kevin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1093410</ericid><atitle>moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization</atitle><jtitle>Technology, knowledge and learning</jtitle><stitle>Tech Know Learn</stitle><date>2016-04-01</date><risdate>2016</risdate><volume>21</volume><issue>1</issue><spage>75</spage><epage>98</epage><pages>75-98</pages><issn>2211-1662</issn><eissn>2211-1670</eissn><abstract>In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload format to enable reuse and replication of analytics results among instructors and researchers. We survey the evolving landscape of competing established and emerging data models, all of which are accommodated in the platform. Data model descriptions are provided to analytics authors who choose, much like with smartphone app stores, to write for any number of data models depending on their needs and the proliferation of the particular data model. Two case study examples of analytics and responsive visualizations based on different data models are described in the paper. The result is a simple but effective approach to learning analytics immediately applicable to X consortium MOOCs and beyond.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10758-015-9268-2</doi><tpages>24</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2211-1662 |
| ispartof | Technology, knowledge and learning, 2016-04, Vol.21 (1), p.75-98 |
| issn | 2211-1662 2211-1670 |
| language | eng |
| recordid | cdi_proquest_journals_1773180792 |
| source | SpringerLink (Online service) |
| subjects | Case Studies Colleges & universities Creativity and Arts Education Data Analysis Data Collection Data models Education Educational Technology Higher education Large Group Instruction Learning analytics Learning and Instruction Mathematics Education Modularity MOOCs Online Courses Open learning Open Source Technology Privacy Science Education Technology Uses in Education Visualization |
| title | moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T07%3A30%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=moocRP:%20Enabling%20Open%20Learning%20Analytics%20with%20an%20Open%20Source%20Platform%20for%20Data%20Distribution,%20Analysis,%20and%20Visualization&rft.jtitle=Technology,%20knowledge%20and%20learning&rft.au=Pardos,%20Zachary%20A.&rft.date=2016-04-01&rft.volume=21&rft.issue=1&rft.spage=75&rft.epage=98&rft.pages=75-98&rft.issn=2211-1662&rft.eissn=2211-1670&rft_id=info:doi/10.1007/s10758-015-9268-2&rft_dat=%3Cproquest_cross%3E3984476161%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1773180792&rft_id=info:pmid/&rft_ericid=EJ1093410&rfr_iscdi=true |