Chrissy Klenke, Teresa Auch Schultz, Rayla E. Tokarz, Elena S. Azadbakht
{"title":"课程数据深潜:识别学科中的数据素养","authors":"Chrissy Klenke, Teresa Auch Schultz, Rayla E. Tokarz, Elena S. Azadbakht","doi":"10.7191/jeslib.2020.1169","DOIUrl":null,"url":null,"abstract":"Objective: Evaluate and examine Data Literacy (DL) in the supported disciplines of four liaison librarians at a large research university. Methods: Using a framework developed by Prado and Marzal (2013), the study analyzed 378 syllabi from a two-year period across six departments—Criminal Justice, Geography, Geology, Journalism, Political Science, and Sociology—to see which classes included DLs. Results: The study was able to determine which classes hit on specific DLs and where those classes might need more support in other DLs. The most common DLs being taught in courses are Reading, Interpreting, and Evaluating Data, and Using Data. The least commonly taught are Understanding Data and Managing Data skills. Conclusions: While all disciplines touched on data in some way, there is clear room for librarians to support DLs in the areas of Understanding Data and Managing Data. Correspondence: Chrissy Klenke: cklenke@unr.edu Received: June 29, 2019 Accepted: October 3, 2019 Published: February 3, 2020 Copyright: © 2020 Klenke, Schultz, Tokarz, and Azadbakht. This is an open access article licensed under the terms of the Creative Commons Attribution License. Data Availability: Data associated with this article is shareable upon request. Disclosures: The authors report no conflict of interest. Full-Length Paper Curriculum Data Dive: Identifying Data Literacies in the Disciplines Christina M. Klenke, Teresa Auch Schultz, Rayla E. Tokarz, and Elena Azadbakht University of Nevada, Reno, Reno, NV, USA","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Curriculum Data Deep Dive: Identifying Data Literacies in the Disciplines\",\"authors\":\"Chrissy Klenke, Teresa Auch Schultz, Rayla E. Tokarz, Elena S. Azadbakht\",\"doi\":\"10.7191/jeslib.2020.1169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: Evaluate and examine Data Literacy (DL) in the supported disciplines of four liaison librarians at a large research university. Methods: Using a framework developed by Prado and Marzal (2013), the study analyzed 378 syllabi from a two-year period across six departments—Criminal Justice, Geography, Geology, Journalism, Political Science, and Sociology—to see which classes included DLs. Results: The study was able to determine which classes hit on specific DLs and where those classes might need more support in other DLs. The most common DLs being taught in courses are Reading, Interpreting, and Evaluating Data, and Using Data. The least commonly taught are Understanding Data and Managing Data skills. Conclusions: While all disciplines touched on data in some way, there is clear room for librarians to support DLs in the areas of Understanding Data and Managing Data. Correspondence: Chrissy Klenke: cklenke@unr.edu Received: June 29, 2019 Accepted: October 3, 2019 Published: February 3, 2020 Copyright: © 2020 Klenke, Schultz, Tokarz, and Azadbakht. This is an open access article licensed under the terms of the Creative Commons Attribution License. Data Availability: Data associated with this article is shareable upon request. Disclosures: The authors report no conflict of interest. Full-Length Paper Curriculum Data Dive: Identifying Data Literacies in the Disciplines Christina M. Klenke, Teresa Auch Schultz, Rayla E. Tokarz, and Elena Azadbakht University of Nevada, Reno, Reno, NV, USA\",\"PeriodicalId\":90214,\"journal\":{\"name\":\"Journal of escience librarianship\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of escience librarianship\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7191/jeslib.2020.1169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of escience librarianship","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7191/jeslib.2020.1169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Curriculum Data Deep Dive: Identifying Data Literacies in the Disciplines
Objective: Evaluate and examine Data Literacy (DL) in the supported disciplines of four liaison librarians at a large research university. Methods: Using a framework developed by Prado and Marzal (2013), the study analyzed 378 syllabi from a two-year period across six departments—Criminal Justice, Geography, Geology, Journalism, Political Science, and Sociology—to see which classes included DLs. Results: The study was able to determine which classes hit on specific DLs and where those classes might need more support in other DLs. The most common DLs being taught in courses are Reading, Interpreting, and Evaluating Data, and Using Data. The least commonly taught are Understanding Data and Managing Data skills. Conclusions: While all disciplines touched on data in some way, there is clear room for librarians to support DLs in the areas of Understanding Data and Managing Data. Correspondence: Chrissy Klenke: cklenke@unr.edu Received: June 29, 2019 Accepted: October 3, 2019 Published: February 3, 2020 Copyright: © 2020 Klenke, Schultz, Tokarz, and Azadbakht. This is an open access article licensed under the terms of the Creative Commons Attribution License. Data Availability: Data associated with this article is shareable upon request. Disclosures: The authors report no conflict of interest. Full-Length Paper Curriculum Data Dive: Identifying Data Literacies in the Disciplines Christina M. Klenke, Teresa Auch Schultz, Rayla E. Tokarz, and Elena Azadbakht University of Nevada, Reno, Reno, NV, USA