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<p>This toolkit is organized into six modules designed to introduce the concept of data literacy and how you can grow this skill set among students on your campus. The modular design allows you to review each module in order, or skip around to the modules that are most relevant to your interests and needs. Each module includes an overview of the topic, case study examples of the concept in action, a reflection activity to solidify learning, and additional resources to explore further. </p>
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<p>This toolkit is organized into five modules designed to introduce the concept of data literacy and how you can grow this skill set among students on your campus. The modular design allows you to review each module in order, or skip around to the modules that are most relevant to your interests and needs. Each module includes an overview of the topic, case study examples of the concept in action, a reflection activity to solidify learning, and additional resources to explore further. </p>
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<ul>
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<li><ahref="modules/dlmodule1.html">Module 1: The Foundations of Data Literacy</a> – Core concepts of data literacy and their importance for information professionals.</li>
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<li><ahref="modules/dlmodule2.html">Module 2: Building a Data Culture on Your Campus</a> – Strategies to engage stakeholders and promote a data-savvy mindset.</li>
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<li><ahref="modules/dlmodule3.html">Module 3: Incorporating Data Literacy Instruction</a> – Introduction to embedding data literacy in curricula and activities.</li>
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<li><ahref="modules/dlmodule4.html">Module 4: Data and Data Sources</a> – Teaching about data types, sources, and quality evaluation.</li>
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<li><ahref="modules/dlmodule5.html">Module 5: Making Data Insightful and Actionable</a> – Interpretation, analysis, and communication of data.</li>
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<li><ahref="modules/dlmodule6.html">Module 6: Managing Data Responsibly and Ethically</a> – Addressing privacy, bias, and ethical data use.</li>
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<li><ahref="modules/dlmodule4.html">Module 3: Data and Data Sources</a> – Teaching about data types, sources, and quality evaluation.</li>
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<li><ahref="modules/dlmodule5.html">Module 4: Making Data Insightful and Actionable</a> – Instructing others about the interpretation, analysis, and communication of data.</li>
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<li><ahref="modules/dlmodule6.html">Module 5: Managing Data Responsibly and Ethically</a> – Addressing privacy, bias, and ethical data use.</li>
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</ul>
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<p>By using this toolkit, you will be empowered to enhance the data fluency of individuals across your institution and equip your learning community with the skills and tools necessary to make informed and responsible decisions grounded in data! </p>
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</section>
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<section>
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<h2>Reusing and Citing this Toolkit</h2>
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<p>You are welcome to use part or all of this toolkit's content for your own educational programs, so long as proper attribution is given. Please be sure to link to our toolkit's url (https://data-literacy-toolkit.github.io/).
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<p>This work is being shared under a CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International, license. You may use, share, remix this content with proper attribution to the creators of this toolkit.
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<p>This toolkit was developed with support from the Institute of Museum and Library Services RE-256673-OLS-24 (<ahref="https://www.imls.gov/grants/awarded/re-256673-ols-24">https://www.imls.gov/grants/awarded/re-256673-ols-24</a>)</p>
<li><ahref="../modules/dlmodule4.html">Data and Data Sources</a></li>
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<li><ahref="../modules/dlmodule5.html">Making Data Insightful</a></li>
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<li><ahref="../modules/dlmodule6.html">Managing Data Responsibly</a></li>
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<li><ahref="../modules/dlmodule3.html">Data and Data Sources</a></li>
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<li><ahref="../modules/dlmodule4.html">Making Data Insightful</a></li>
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<li><ahref="../modules/dlmodule5.html">Managing Data Responsibly</a></li>
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</ul>
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</nav>
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@@ -69,14 +68,14 @@ <h2>Becoming Data Literate</h2>
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<li><b>Interpreting data visualizations:</b> This <ahref="https://guides.library.yale.edu/datavisualization/types">research guide</a> from Yale University explains the uses and distinctions among various types of data visualizations. This will also be explored further in our Making Data Insightful and Actionable module. </li>
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<li><b>Drawing conclusions from data:</b> This <ahref="https://insight7.io/6-steps-to-developing-actionable-insights/">learning resource</a> from Insight7 describes the process of turning data into actionable insights. This will also be explored further in our Making Data Insightful and Actionable module.</li>
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<li><b>Communicating data-informed findings:</b> This <ahref="https://www.pragmaticinstitute.com/resources/articles/data/communicating-data-to-non-data-teams/">informational article</a> from the Pragmatic Institute discusses the importance and process of communicating data insights to non-data professionals. This will also be explored further in our Making Data Insightful and Actionable module. </li>
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<li><b>Engaging in ethical and critical thinking:</b> This <ahref="https://libguides.library.ncat.edu/c.php?g=778712&p=10368600">research guide</a> from North Carolina A&T University presents data ethics from the perspective of a researchlibrary. This will also be explored further in our Managing Data Responsibly and Ethically module.</li>
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<li><b>Engaging in ethical and critical thinking:</b> This <ahref="https://libguides.library.ncat.edu/c.php?g=778712&p=10368600">research guide</a> from North Carolina A&T University presents data ethics from the perspective of a research library. This will also be explored further in our Managing Data Responsibly and Ethically module.</li>
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</ul>
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<p>In order to enhance data literacy on your campus, it is important to first become data literate yourself. This does not require a formal education or degree. Just informal learning and practice through toolkits like this one can prepare you with the skills you need to be a data literacy instructor and advocate! </p>
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</section>
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<section>
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<h2>Case Example</h2>
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<p>The University of South Florida-St. Petersburg engaged in the creation of a series of <ahref="https://lib.usf.edu/research-and-instruction/workshops/a-z-list-of-info-data-literacy-workshops/">data literacy workshops and initiatives</a> to build on existing, successful information literacy programs. The success of these programs for enhancing data literacy skills is discussed in a 2020 article by Burress et al. <ahref="#ref4">[4]</a>. The success of this program was driven by an interdisciplinary and cross-campus collaboration to expand data literacy skills that could be applied across disciplines. The initiative centered on a framework for data literacy that discussed data in all its forms but particularly emphasized research data skills. The success of this program allowed it to be integrated into the general education curriculum, engaging hundreds of students each year in data instruction.</p>
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<p>The University of South Florida-St. Petersburg engaged in the creation of a series of <ahref="https://lib.usf.edu/research-and-instruction/workshops/a-z-list-of-info-data-literacy-workshops/">data literacy workshops and initiatives</a> to build on existing, successful information literacy programs. The outcomes of these programs for enhancing data literacy skills is discussed in a 2020 article by Burress et al. <ahref="#ref4">[4]</a>. This program was driven by an interdisciplinary and cross-campus collaboration to expand data literacy skills that could be applied across disciplines. The initiative centered on a framework for data literacy that discussed data in all its forms but particularly emphasized research data skills. The success of this program allowed it to be integrated into the general education curriculum, engaging hundreds of students each year in data instruction.</p>
<li><ahref="../modules/dlmodule1.html">Foundations of Data Literacy</a></li>
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<li><ahref="../modules/dlmodule2.html">Building a Data Culture</a></li>
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<li><ahref="../modules/dlmodule3.html">Data and Data Sources</a></li>
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<li><ahref="../modules/dlmodule4.html">Making Data Insightful</a></li>
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<li><ahref="../modules/dlmodule5.html">Managing Data Responsibly</a></li>
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<h2>Data Events and Activities</h2>
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<p>There are many different ways to engage stakeholders on your campus in data literacy activities. As noted in the prior section, the best practice is probably to offer many options for engagement, similar to how we might teach for different learning styles <ahref="#ref3">[3]</a>. The following are just a few examples of events and activities that you might initiate on your campus:</p>
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<li><b>Host a “Data Literacy Week”: </b> Having an entire week of activities can be a great way to increase awareness around campus. You could host panels with data experts, such as faculty around campus, hold hands-on workshops, and have students present posters on data literacy topics.</li>
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<li><b>Hold a Hackathon Event: </b> Encourage students to work in teams to identify solutions to issues related to data literacy. The competitive nature of the hackathon will make it a memorable event.</li>
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<li><b>Lead a Data Storytelling Contest: </b> Invite students to submit short narratives that discuss data visualizations that they have used to answer a question in their academic or professional life. </li>
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<li><b>Host a “Data Literacy Week”: </b> Having an entire week of activities can be a great way to increase awareness around campus. You could host panels with data experts, such as faculty around campus, hold hands-on workshops, and have students present posters on data literacy topics. "Love Data Week" is celebrated during the week of Valentine's Day each year and many universities celebrate with a week of activities, including the <ahref="https://btaa.org/research/love-data-week/love-data-week-events">Big Ten Academic Alliance. </a></li>
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<li><b>Hold a Hackathon Event: </b> Encourage students to work in teams to identify solutions to issues related to data literacy. The competitive nature of the hackathon will make it a memorable event. Several universities have hosted similar events in recent years, such as the <ahref="https://www.uh.edu/nouhadrizk/data-science-showcase-and-hackathon/index.php">University of Houston </a></li>
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<li><b>Lead a Data Storytelling Contest: </b> Invite students to submit short narratives that discuss data visualizations that they have used to answer a question in their academic or professional life. A data storytelling contest at <ahref="https://www.ivybusiness.iastate.edu/event/data-visualization-and-storytelling-case-competition/">Iowa State University</a> provides a useful example of what this type of event might look like.</li>
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