Data Visualization - Nces.ed.gov

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Data VisualizationMichael HopkinsRochester School Department, New Hampshire

Presentation Outline Forum Resources on Data VisualizationData Visualization in Education OrganizationsData Visualization to Advance Data AnalysisData Visualization to Improve CommunicationsImplementing the Data Visualization Process2

Data Visualization is ImportantEffective data visualization can improve communications;make data more user friendly; andincrease stakeholder access to data.3

Forum Guide to Data Visualization:A Resource for Education Agencies4

Document Purpose & AudienceTo recommend data visualization practices thatwill help education agencies communicate datameaning in visual formats that are accessible,accurate, and actionable for a wide range ofeducation stakeholders.The document will be useful for program and data staff;data analysts and researchers;administrators and policymakers; andrelated roles analyzing or presenting data for publicconsumption.5

Table of ContentsChapter 1. Data Visualization in Education Organizations defines the concept of data visualization;describes how data visualization blends both science and art; andexplains how data visualization can improve education data use.Chapter 2. Data Visualization to Advance Data Analysis illustrates how data visualization can be a sound method foranalysts to identify trends, patterns, and cues in data.Chapter 3. Data Visualization to Improve Communications presents four key principles and seven practical recommendationsthat will improve efforts to visualize data for stakeholders whoneed to understand and use education data to make decisions.Chapter 4. Implementing the Data Visualization Process illustrates a six-step process for visualizing data for both analyticaland communications purposes.6

10 and 2 10 minutes of presentation and at least 2 minutesof reflection.Mental processing time is needed.Present information for 10 minutes.Allow students to process information individuallyor collaboratively for 2 minutes.Retention increases with the 2 minutes reflectionand sharing with others.7

Forum Data VisualizationOnline CourseModule 1: Introduction to Data Visualization introduces the concept of data visualization and the ways in whichit can improve how education data are viewed, analyzed,communicated, and understood by a range of common educationstakeholders;introduces the key principles and characteristics of effective datavisualization; andexplains how effective data visualization techniques can contributeto a culture of data quality throughout an education agency.8

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Ch. 1: Data Visualization in Education Organizations10

What is Data Visualization?Data visualization is the transformation of data intoinformation through visual presentation andanalysis. It may culminate in a figure or image, but should not beviewed simply as a graphical product.It is the process of using a wide range ofcommunications methods, presentation technologies,and media formats to visually reveal the meaning ofdata to viewers.11

Ch. 1: Data Visualization in Education Organizations12

Ch. 1: Data Visualization in Education OrganizationsEffective data visualization is valuable as an analytical and communications toolbecause of the insights it provides through visuallyapparent cues, patterns, and trends.customized to meet the information needs of specificintended audiences.intentionally designed to reduce the likelihood ofviewers misunderstanding or misinterpreting data.Effective data visualization is not emphasizing presentation over message in a way thatdistorts or distracts from meaning.more complex or creative than it needs to be toaccurately convey data meaning.13

Ch. 2: Data Visualization to Advance Data AnalysisFind the outlier in this (very small) dataset . Average Value 52. Data Values 51, 60, 52, 48, 51, 57, 44, 46, 48, 50, 52,58, 47, 50, 51, 53, 45, 55, 47, 56, 58, 52,44, 56, 41, 40, 60, 90, 42, 55, 50, 47, 5614

Ch. 2: Data Visualization to Advance Data Analysis15

Ch. 2: Data Visualization to Advance Data AnalysisData visualization to advance data analysis focuses on the needs of data analysts who aretrying to determine what a particular set of data,or multiple datasets, might mean. is not intended to share their analytical methodsas communications tools.16

Ch. 2: Data Visualization to Advance Data Analysis17

Ch. 2: Data Visualization to Advance Data Analysis18

Ch. 2: Data Visualization to Advance Data Analysis19

Ch. 2: Data Visualization to Advance Data AnalysisPreliminary data analysis suggeststhree rational, observation-basedhypotheses that may need more formalstudy:(1)(2)(3)Decreases in student attendance in certainmonths resulted in lower average testscores in the following month.Increases in excused absences forextracurricular activities resulted in loweraverage monthly test scores.Decreases in student attendance andincreases in excused absences forextracurricular activities combined to resultin lower average monthly test scores.20

Ch. 2: Data Visualization to Advance Data Analysis Take Away 1: Attendance and excusedabsence patterns might have had anegative effect on the school’s averagetest scores during specific months. Take Away 2: It is acceptable and evenencouraged to take these factors intoaccount preliminarily when planningtest dates and reflecting on the testscore data. Take Away 3: Although these factorsappear to be correlated, they are notnecessarily connected causally—andcannot be considered causes for lowerscores without additional research.21

Ch. 3: Data Visualization to Improve Communications Data visualization is essential for presentinginformation in a manner that communicatesdata meaning to a range of audiences—especially non-expert viewers.4 key principles ensure that data meaning iscommunicated effectively:1)2)3)4)Show the data.Reduce the clutter.Integrate text and images.Portray data meaning accurately and ethically.22

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 1: Show the Data Data values that underlie a visualization areimportant enough to be labeled becauseshowing the data values improves readercomprehension.A corollary to the key principle of “show thedata” is the need to include relatedinformation, including metadata,that is necessary to fully understand thedata.23

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 1Show the DataWhy mightmetadata behelpful?The two dropoutrates are for thesame school district,population, and year.Dropout Rate (1) is a 12th Grade Annual Dropout Rate, defined as the percentage ofstudents who were enrolled in 12th grade at some time but who did not graduate fromhigh school or complete a state- or district-approved educational program and did nottransfer to another public school district, private school, or state- or district-approvededucational program (including correctional or health facility programs); have atemporary absence due to suspension or school-excused illness; or die.Dropout Rate (2) applies the same definition to a cohort of students entering 9th gradebut dropping out prior to graduation of the cohort (usually 4 or 5 years later). Thus,both bars represent “the dropout rate” in the same school district, population, andschool year, but they count different students over different periods of time.24

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 2: Reduce the Clutter Unnecessary bells and whistles, purely cosmeticfeatures, and other extraneous information distractfrom the primary meaning of the data. Which figure below is most effective?Strike a balance between showing the data and overwhelming the audience.25

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 3: Integrate Images and Text Visualizations should stand on their own asa complete piece of information and beclearly connected to the text.Every aspect of imagery and text shouldpoint viewers toward a better understandingof the take-home message.26

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 3Integrate Images and TextWhich figure title conveysmeaning to a viewer?27

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 4: Portray the Data Accurately and Ethically Even accurately presented data can be presentedunethically, such as limiting which data are seen (overemphasizingsubsets or “patterns” in data by only showing parts ofan axis); suggesting a conclusion that does not reflect the data(referring to a “trend” that does not fully describe thedata); and manipulating how the data are presented visually(suggesting that certain types of data are continuousover time rather than discrete across time to suggestrelationships that are not valid).28

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 4Portray the DataAccurately and Ethically29

Ch. 3: Data Visualization to Improve CommunicationsKey Principle 4Portray the Data Accurately and Ethically30

Ch. 3: Data Visualization to Improve CommunicationsSeven Recommended Practices forData Visualization1)2)3)4)5)6)7)Capitalize on consistency.Data that should not be compared should not bepresented side by side.Don’t limit your design choices to default graphingprograms.Focus on the take-home message for the target audience.Minimize jargon, acronyms, and technical terms.Choose a font that is easy to read and will reproduce well.Recognize the importance of color and the benefits ofSection 508 Compliance.31

Ch. 4: Implementing the Data Visualization ProcessData Visualization: A Six-Step Process1.Question: Someone Needs Information 2.Research: Data Exploration and Analysis 3.What is the question? Is this a one-time informationneed or a routine request that will likely be repeated?What data and analysis are needed? Are high-qualitydata available for relevant exploration and analysis?Findings: Data Meaning/Answer What is the “take-home message” from the data? Thatis, what is the core message in the data that you wishto convey?32

Ch. 4: Implementing the Data Visualization ProcessData Visualization: A Six-Step Process4.Customization: Audience Specific Messaging Who is your audience? To whom is the message beingconveyed? What is the most appropriate way tocommunicate with this audience?5.Visualization: Present Data Meaning Clearly and Accurately How will you present your message? That is, what is themost effective way to visualize the data for your audience?6.User Feedback: Review and Refine Efforts How can you ensure that your visualization is effective?Ask your users for feedback and iterate, iterate, and iteratebased on that feedback.33

Ch. 4: Implementing the Data Visualization ProcessStep 1. Someone NeedsInformationHow does our state’s high schoolgraduation rate compare to otherstates’ high school graduation rates?Step 2. Data Exploration andAnalysisA visit to the NCES website revealsthe availability of the EDFactsConsolidated State PerformanceReport that includes public highschool 4-year adjusted cohortgraduation rate (ACGR) for the US,the 50 states and DC: School years2010-11 to 2012-13 (see figure).Table 4.1. Public high school 4-year adjusted cohortgraduation rate (ACGR) for the United States, the 50states, and the District of Columbia: School years 2010-11to 2012-13Adjusted Cohort Graduation RateState2010-112011-122012-13United cticut838586Delaware78808034

Ch. 4: Implementing the Data Visualization ProcessStep 3. DataMeaning/AnswerWhile the data presented intabular form in table 4.1 areappropriate for some types ofaudiences, even seasonedanalysts are likely to find itdifficult to identify any patterns,trends, or cues in such a table.The default setting in aspreadsheet tool produces agraph with many features thatare likely to lead tomisunderstanding ormisinterpretation of the data(see figure).35

Ch. 4: Implementing the Data Visualization ProcessStep 3. Data Meaning/AnswerOther default graphs are visuallyinteresting but are more likely toobscure rather than clarify meaning. Why 3D for 2D data? What data values dothe tips of the cones indicate? How does a radar chart clarify ACGR? Which bars map to which colors in thelegend?36

Ch. 4: Implementing the Data Visualization ProcessStep 4. Customization:Audience-SpecificMessagingThe question in step 1 originatedfrom the general public. Such abroad audience indicates thatdesigners can’t assume anydata, statistical, policy, oreducation-related expertise onthe part of the viewer.This audience warrants a“no training required” approachto visualization.SOURCE: EDFacts/Consolidated State Performance Report, school years 2010-11, 2011-12, and solidated/index.html.Table prepared January 2015.37

Ch. 4: Implementing the Data Visualization ProcessStep 5. Present DataMeaning Clearly andAccuratelyThe visual power of reordering the states fromhighest to lowest datavalues (recommendation3) inserting a nationalaverage value(recommendation 4), and highlighting that nationalaverage in another colorto simplify comparisons(recommendation 7)will all contribute to betterunderstanding of the takehome message.38

Ch. 4: Implementing the Data Visualization ProcessStep 6. Review and Refine Efforts39

Summary Taking action with data—the right data at the righttime in the right format and in the right context—can be a powerful tool for anyone needing tomake decisions about how our educationalsystem serves students and communities. Data visualization is a critical component of thedata analysis and communications process formany education stakeholders.40

Questions?41

Thank youDownload the Forum Guide to Data Visualization:A Resource for Education Agencies and accessother free Forum resources at:http://nces.ed.gov/forum/publications.asp

Forum Data Visualization Online Course. Module 1: Introduction to Data Visualization introduces the concept of data visualization and the ways in which it can improve how education data are viewed, analyzed, communicated, and understood by a range of common education stakeholders; introduces the key principles and characteristics of effective data

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