{"@id":"https://credentialengineregistry.org/resources/ce-76a7652e-422c-4ea8-a2b2-8893b964ff6f","@type":"ceterms:MicroCredential","@context":"https://credreg.net/ctdl/schema/context/json","ceterms:ctid":"ce-76a7652e-422c-4ea8-a2b2-8893b964ff6f","ceterms:name":{"en-US":"Data Disaggregation for Data-Driven Decisions"},"ceterms:image":"https://d2umcf2gmasgod.cloudfront.net/671291c413923d950566d942.png","ceterms:keyword":{"en-US":["data literacy"]},"ceterms:ownedBy":["https://credentialengineregistry.org/resources/ce-34e96e45-7ba7-4870-b3cf-055d9621d354"],"ceterms:requires":[{"@type":"ceterms:ConditionProfile","ceterms:name":{"en-US":"Open Badges Criteria"},"ceterms:description":{"en-US":"Key  Method\n\nThe educator disaggregates, or separates, data in meaningful and actionable forms to make effective data-driven decisions.\n\nMethod  Components\n\nEducators often have questions or hunches about why data are the way they are. They analyze the data to explore those hunches. This work often demands cutting, or disaggregating, data in particular ways. For example, educators may disaggregate data to help answer the following sorts of questions:\n\nThe class average was 76% on a particular assessment. But did students, on average, perform equally well across all learning standards on that assessment \nThe class average for word problems is 82%. I wonder if my students who are classified as English Language Learners systematically perform differently on these problems than do students without that classification.\nIt seems like my students who identify as girls don't give up as quickly on math problems. Do they have higher interest scores than my students who identify as boys? How did students who are non-binary perform in this assessment? (Educators should use these as examples of questions to ask when looking at the variation of performance by different gender identities represented in their classroom.)\n\nIn each case, educators start with a question or hunch and disaggregate the data, or cut it in intentional ways, to better understand whether there are systematic trends that are not immediately obvious when looking at the data as a whole set.\n\nWhen disaggregating data, data-literate teachers keep two key points in mind: (1) small differences may not, in fact, be true differences from a statistical point of view (i.e., the differences are not statistically significant), and (2) any possible relationships are often associative and not causal-and usually require additional investigation and unpacking. Disaggregating data is a critical step in determining what data-driven action might be appropriate and where further inquiry may be productive."},"ceterms:subjectWebpage":"https://digitalpromise.box.com/s/5eqwm45tb24xoq6swvwbnlubvj4x9239"}],"ceterms:inCatalog":"https://microcredentials.digitalpromise.org/explore/data-disaggregation-for-data-driven-decisions","ceterms:offeredBy":["https://credentialengineregistry.org/resources/ce-34e96e45-7ba7-4870-b3cf-055d9621d354"],"ceterms:inLanguage":["en"],"ceterms:description":{"en-US":"Educator combines and analyzes many forms of data to help make inferences about student understanding and behaviors."},"ceterms:credentialId":"https://microcredentials.digitalpromise.org/explore/data-disaggregation-for-data-driven-decisions","ceterms:subjectWebpage":"https://microcredentials.digitalpromise.org/explore/data-disaggregation-for-data-driven-decisions","ceterms:copyrightHolder":["https://credentialengineregistry.org/resources/ce-34e96e45-7ba7-4870-b3cf-055d9621d354"],"ceterms:availableOnlineAt":["https://microcredentials.digitalpromise.org/explore/data-disaggregation-for-data-driven-decisions"],"ceterms:availabilityListing":["https://microcredentials.digitalpromise.org/explore/data-disaggregation-for-data-driven-decisions"],"ceterms:credentialStatusType":{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://credreg.net/ctdl/terms/CredentialStatus","ceterms:targetNode":"credentialStat:Active","ceterms:frameworkName":{"en-US":"Credential Status"},"ceterms:targetNodeName":{"en-US":"Active"},"ceterms:targetNodeDescription":{"en-US":"Awards of the credential are ongoing."}},"ceterms:usesVerificationService":["https://credentialengineregistry.org/resources/ce-1472586c-b08c-4f22-9013-5b4d9a58d277"]}