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            <h2>Data for Decisions Curriculum</h2>
            <h4>About</h4>
            <p>The overarching goal of the Data for Decisions Curriculum is to build the capabilities of research organizations, government ministries, and civil society organizations to more effectively collect, use, and share data in their organizations and apply data in their decision making processes. Through basic organizational data environment assessment, understanding each stage of the data lifecycle, and tools to develop a data project plan, the curriculum aims to increase the awareness and use of quality data for evidence-based decision making and in tackling social challenges.</p> 
            <h4>The Gap</h4>
            <p>The curriculum was developed in response to the results  of a needs assessment conducted by Myanmar’s Enlightened Myanmar Research Foundation. The assessment, which spanned multiple government ministries and civil society organizations, indicated an overwhelming desire for tools to support the changing organizational data environments across sectors in Myanmar.</p>
            <p>Although there are many data literacy resources available, there was not anything that fit the precise needs of organizations in Myanmar. Specifically:
                <ul>
                    <li>a structure designed for environments with nascent/emerging data cultures</li>
                    <li>a comprehensive approach that begins with the foundations of assessing organizational data environments and data problems, upon which skills can be built</li>
                    <li>not focused solely on statistical skill building</li>
                    <li>open and customizable</li>
            </ul></p>
            <p>We see these as needs not unique to Myanmar and have structured the curriculum to be adapted and expanded for other organizations.</p>
        
            <h4>Objectives</h4>
            <p>The key objectives of this course include:
                <ul>
                    <li>Learn basic questions to ask of your data and how to define data problems or needs within a community or organization</li>
                    <li>Understand how to identify the key data players surrounding a difficult problem or social challenge</li>
                    <li>Learn the data life cycle, and understand the importance of data collection, analysis, and sharing</li>
                    <li>Understand how to be a more savvy data consumer, and learn new ways to manage and store data so that it can be easily shared among organizations</li>
                    <li>Think critically about the vision and mission of your organization, and how to apply innovative solutions that follow that mission using data</li>
                    <li>Know what methods to implement and what data collection tools need to be designed to address data gaps</li>
                    <li>Understand how to share data resources and solutions amongst different communities and organizations</li>
                    <li>Think critically about how to learn from these sharing opportunities</li>
                    <li>Build a culture of self-reflection around data, and share this culture with other communities and organizations</li>
            </ul></p>
    
            <h4>Curriculum Structure</h4>
            <p>The course is structured into three days spanning six separate modules. Each module has a specific goal and covers a topic designed to bolster ability in using data for decision making. Modules are structured over a three-hour period including one ten-minute break. Each module contains new information while simultaneously building on previous knowledge from past modules. While following these modules in order can provide the user with a solid foundation in data for decision making, the modules are meant to stand alone and can be applied in whichever order the user chooses.</p>
            <p>The organization of each module is as follows
                <ul>
                    <li>Day 1</li>
                    <ul>
                        <li>Module 1: Introduction to Data for Decision Making</li>
                        <li>Module 2: Assessing Your Organization’s Data Culture</li>
                    </ul>
                    <li>Day 2</li>
                    <ul>
                        <li>Module 3: Introduction to the Data Lifecycle – Collecting Data</li>
                        <li>Module 4: Introduction to the Data Lifecycle – Analyzing and Sharing Data</li>
                    </ul>
                    <li>Day 3</li>
                    <ul>
                        <li>Module 5: Applying Data for Decision Making to Your Organization, Part 1</li>
                        <li>Module 6: Applying Data for Decision Making to Your Organization, Part 2</li>
                    </ul>
    </ul></p>
<p>Each module contains the following:
    <ul>
        <li>A downloadable Powerpoint (.ppt) slide deck for the module</li>
        <li>Instructor's guide</li>
        <li>Student handbook</li>
        <li>Guide for each activity contained in the module</li>
</ul></p>
<h4>Content Choices</h4>
<p>Content priorities were developed through findings from the needs assessment and consultation with local organizations. Pilot testing was conducted to obtain feedback on the relative amount of time allocated to different topic areas. Examples and case studies are largely relevant for the Myanmar context and can be replaced with locally relevant materials as needed. Examples of additional modules that could be created include:</p>
<ul>
    <li>Gender sensitive data approaches</li>
    <li>Ethics and privacy in the data lifecycle</li>
    <li>A module specific for managers</li>
    <li>Program-specific skills (e.g. Excel, R, SPSS, Tableau)</li>
    <li>Proxy indicators</li>
    <li>Basic data and computer literacy</li>
    <li>Basic statistical literacy</li>
    <li>Big data</li>
</ul>
<p>As noted above, the curriculum was designed to be adaptable for new content to be added and topic emphasis shifted based upon new target audiences.</p>

<h4>Key Organizations</h4>
<p>The curriculum was developed by the Technology & Social Change Group at the University of Washington Information School, in partnership with the Myanmar Book Aid and Preservation Foundation. The project was made possible by the generous support of the Tableau Foundation. An initiative led by the employees of Tableau Software, the Tableau Foundation encourages the use of facts and analytical reasoning to solve the world’s problems though fellowships that help non-profits build data capabilities from the grassroots up.</p>

<h4>Resources Consulted</h4>
<p>The following resources were consulted to develop the curriculum:</p>
<p><a href="https://www.databasic.io/en/wtfcsv/wtfcsv-activity-guide.pdf">https://www.databasic.io/en/wtfcsv/wtfcsv-activity-guide.pdf</a></p>
<p><a href="Datatherapy.org">Datatherapy.org</a></p>
<p>Innovations for Poverty Action (2016). Goldilocks Case Study: Digital Green. Retrieved 1 July 2018, from <a href="https://www.poverty-action.org/publication/goldilocks-case-study-digital-green">https://www.poverty-action.org/publication/goldilocks-case-study-digital-green</a></p>
<p>Knowledge Sharing. (n.d.). In <i>Wikipedia</i>. Retrieved July 1, 2018, from <a href="https://en.wikipedia.org/wiki/Knowledge_sharing">https://en.wikipedia.org/wiki/Knowledge_sharing</a></p>
<p>Patton, M. (2012). <i>Essentials of Utilization-focused Evaluation</i>. Los Angeles, Calif.: SAGE.</p>
<p>Serrat, Olivier (May 2010). The Critical Incident Technique. <i>Knowledge Solutions</i>, 86.</p>
<p>UNDP, UN Global Pulse, ‘A Guide to Data Innovation for Development: From Idea to Proof of Concept,’ 2016</p>
            
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