Psychological processes of Psychological processes of graphical perception: graphical perception:

Past findings and our research Past findings and our research proposalproposal

MariyaMariya ShiykoShiykoMasanao YajimaMasanao Yajima

Columbia University, G4160 March 10Columbia University, G4160 March 10thth, 2006, 2006

OutlineOutlineA model of graphical informationA model of graphical information--processingprocessing1.1. Input: quantitative/qualitative informationInput: quantitative/qualitative information2.2. Retinal imageRetinal image3.3. Visual cortexVisual cortex4.4. ShortShort--term and longterm and long--term memoryterm memory

ImplicationsImplications

Research proposalResearch proposal1.1. Variables in the studyVariables in the study2.2. HypothesesHypotheses3.3. SampleSample4.4. MaterialsMaterials5.5. Procedure Procedure

ReferencesReferences

A model of A model of graphical informationgraphical information--processing processing

(Kosslyn, Wilkinson)(Kosslyn, Wilkinson)

Input Retina Visual Input Retina Visual ShortShort--term term (quantity Cortex (quantity Cortex LongLong--termterm

& & memorymemoryquality) quality)

FormatFormatLine graphs Line graphs •• emphasize emphasize x x -- yy trendstrends((CarswellCarswell et al., 1987; Shan et al., 1999; et al., 1987; Shan et al., 1999; ZacksZacks & &

TverskyTversky, 1999), 1999)

Bar graphs Bar graphs •• stimulate discrete comparisons stimulate discrete comparisons

(Shah & (Shah & ShellhammerShellhammer, 1999), 1999) and and •• reduce bias towards reporting reduce bias towards reporting

only one variableonly one variable

Pie charts Pie charts •• preferable for comparing preferable for comparing

relative proportions relative proportions (Kosslyn, 1994; Wilkinson, 1999)(Kosslyn, 1994; Wilkinson, 1999)

DimensionalityDimensionality3D graphs enhance 3D graphs enhance comparison of 3 variablescomparison of 3 variables((WickensWickens et al., 1994)et al., 1994)

3D displays interfere with 3D displays interfere with reading individual data reading individual data pointspoints (Shah et al.)(Shah et al.)

3D objects require prior 3D objects require prior knowledge of reading knowledge of reading similar graphssimilar graphs (Shah et al.)(Shah et al.)

For twoFor two--variable variable relationship depicted in relationship depicted in 3D, accuracy and speed 3D, accuracy and speed of data reading of data reading decreases/does not decreases/does not changechange (Fischer, 2000; Spence, 1990)(Fischer, 2000; Spence, 1990)

Colors Colors Colors may be misleading when used Colors may be misleading when used for continuous data for continuous data (Cleveland & McGill, 1985)(Cleveland & McGill, 1985)

The use of colors may falsely suggest The use of colors may falsely suggest presence of categorical data presence of categorical data (Cleveland & McGill, 1985)(Cleveland & McGill, 1985)

Colors help to group data in scatter Colors help to group data in scatter plots plots ((LewandowskyLewandowsky & Spence, 1989) & Spence, 1989)

Colors reduce the load of shortColors reduce the load of short--term term memory when used as referents and memory when used as referents and are preferred to legends are preferred to legends (Kosslyn, 1994)(Kosslyn, 1994)

Rank ordering Rank ordering (most accurate to least accurate) (most accurate to least accurate)

of visual dimensions used to of visual dimensions used to represent quantitative informationrepresent quantitative information

(adopted from Cleveland & McGill, 1984)(adopted from Cleveland & McGill, 1984)

1.1. Position along a common scalePosition along a common scale2.2. Position along nonaligned scalesPosition along nonaligned scales3.3. Length, direction, angleLength, direction, angle4.4. AreaArea5.5. Volume, curvatureVolume, curvature6.6. Shading, color saturationShading, color saturation

•• Depends on lightningDepends on lightning

• Depends on viewing Depends on viewing positionposition

•• Depends on color Depends on color contrastscontrasts

•• Black & white colors Black & white colors are best suited for are best suited for visual perceptionvisual perception

The retinal imageThe retinal image

Follows the principles of Follows the principles of absolute & relative absolute & relative discriminabilitydiscriminability(Kosslyn, 1989)(Kosslyn, 1989)

Most Most discriminablediscriminablesymbols are verticals, symbols are verticals, horizontals, & diagonals horizontals, & diagonals (Cleveland, 1993; Wilkinson, 1993)(Cleveland, 1993; Wilkinson, 1993): :

‘‘oo’’, , ‘‘--’’, , ‘‘!!’’, , ‘‘xx’’

The visual cortexThe visual cortexextracts spatial frequency, orientation, and other extracts spatial frequency, orientation, and other

features needed to construct complex visual scenesfeatures needed to construct complex visual scenes

Principles of perceptual organizationPrinciples of perceptual organizationGestalt laws:Gestalt laws:

a) a) good continuity: good continuity: ‘‘--------------------’’b) proximity: b) proximity: ‘‘xx xxx xxxx xxx xx’’c) similarity: c) similarity: ‘‘!!!OOO!!!OOO’’d) good form: d) good form: ‘‘{ }{ }’’ vs. vs. ‘‘{ { ¥¥’’

Integral vs. separable dimensionsIntegral vs. separable dimensions (Kosslyn, 1989)(Kosslyn, 1989)

Processing prioritiesProcessing priorities (Kosslyn, 1989)(Kosslyn, 1989)

Processing limitationsProcessing limitations (Kosslyn, 1989)(Kosslyn, 1989)

a) finite capacity (4a) finite capacity (4--7 perceptual groups)7 perceptual groups)

b) purposeful unit binding b) purposeful unit binding

Informative mapping Informative mapping (e.g. labels match the axes)(e.g. labels match the axes)

MemoryMemory

Short-termmemory

Long-termmemory

ReorganizationCapacity

limitsKnowledge

Discriminability Encoding DistortionOrganizationPriorities …

Knowledge is stored in forms of Knowledge is stored in forms of schemasschemas -- mental structures that represent mental structures that represent some aspect of the world. People use some aspect of the world. People use schemas to organize current knowledge and schemas to organize current knowledge and provide a framework for future provide a framework for future understanding understanding ((WikipediaWikipedia))

KnowledgeKnowledge

About graphs About content

Knowledge/schemas about graphs Knowledge/schemas about graphs that interfere with graph readings:that interfere with graph readings:

1. Viewers tends to favor 45 degree lines rather than 1. Viewers tends to favor 45 degree lines rather than steeper or flatter linessteeper or flatter lines when required to remember when required to remember graphical representations of data graphical representations of data ((SchianoSchiano & & TverskyTversky, 1992; , 1992; TverskyTversky & & SchianoSchiano, 1989), 1989)

2. Viewers tend to expect independent variable plotted on 2. Viewers tend to expect independent variable plotted on X axis & dependent variable X axis & dependent variable -- on Yon Y axis axis

3. Viewers confuse slope & height/value magnitude 3. Viewers confuse slope & height/value magnitude ((GattisGattis & & HolyoakHolyoak, 1995 , 1995 Bell and Bell and JanvierJanvier, 1981, 1981))

4. Novice viewers rely on their prior knowledge about the 4. Novice viewers rely on their prior knowledge about the content rather than the information depicted in the content rather than the information depicted in the graphgraph (Shah 1995)(Shah 1995)

Content knowledgeContent knowledge-- Influences on interpretation of graphsInfluences on interpretation of graphs-- Influences on memoryInfluences on memory-- Is especially important for novice graph Is especially important for novice graph

viewersviewers

EasyEasy HardHard* Distance * Acceleration* Distance * Acceleration* Position * Velocity * Position * Velocity * Time* Time

Content knowledge/schemas that Content knowledge/schemas that interfere with graph readingsinterfere with graph readings

Viewers tend to overestimate the correlation Viewers tend to overestimate the correlation between variables when they believe that between variables when they believe that these variables are relatedthese variables are related(Freedman and Smith, 1996; Jennings et al., 1982)(Freedman and Smith, 1996; Jennings et al., 1982)

Viewers more likely to make inferences about Viewers more likely to make inferences about general trends (main effects) when viewing general trends (main effects) when viewing graphs with familiar relationships graphs with familiar relationships (Shah & (Shah & ShellhammerShellhammer, 1999 ), 1999 )

Younger students tend to interpret abstract Younger students tend to interpret abstract representation of data as an iconic representation of data as an iconic representation of real event, e.g. height representation of real event, e.g. height instead of growth, location instead of speedinstead of growth, location instead of speed((JanvierJanvier 1981; 1981; LeinhardtLeinhardt et al., 1990)et al., 1990)

ImplicationsImplications•• Choose the format depending on the Choose the format depending on the

communication goalcommunication goal•• Use multiple formats to communicate the Use multiple formats to communicate the

same datasame data•• Use 3D with cautionUse 3D with caution•• Choose colors thoughtfullyChoose colors thoughtfully•• Reduce working memory demandsReduce working memory demands•• Follow the principles of perceptionFollow the principles of perception•• Be aware of your audienceBe aware of your audience

IndependentIndependentVariablesVariables

Prior knowledge Prior knowledge about graphsabout graphsPrior statistical Prior statistical knowledgeknowledge

description of description of relationships relationships b/w 3 variablesb/w 3 variablesNumber of Number of responses responses •• CorrectCorrect•• Incorrect Incorrect

Identification of Identification of misleading misleading graphsgraphs

OutcomesOutcomes

H1: people with prior knowledge of graphs H1: people with prior knowledge of graphs will describe relationship b/w 3 variableswill describe relationship b/w 3 variables

H2: people with prior knowledge of graphs H2: people with prior knowledge of graphs will notice discrepancies in graphical will notice discrepancies in graphical representationsrepresentations

H3: people with prior knowledge of graphs H3: people with prior knowledge of graphs will report more information than people will report more information than people with no such knowledge with no such knowledge

H4: people with prior knowledge of graphs H4: people with prior knowledge of graphs will have more correct responses will have more correct responses compared to people with no such compared to people with no such knowledgeknowledge

HypothesesHypotheses

Students from the statistical Students from the statistical graphing classgraphing classStudents from other classes (?)Students from other classes (?)

We will differentiate students by: We will differentiate students by: -- prior knowledge of graphsprior knowledge of graphs-- prior statistical knowledgeprior statistical knowledge-- gendergender-- ageage-- educationeducation

SampleSample

MaterialsMaterials

4 graphs adopted from other studies 4 graphs adopted from other studies (and modified) (and modified)

All graphs represent relationship All graphs represent relationship between 3 variablesbetween 3 variables

Some graphs contain misleading Some graphs contain misleading information about the relationshipinformation about the relationship

ProcedureProcedure

Students will be given testing Students will be given testing instructionsinstructionsStudents will fill out personal Students will fill out personal informationinformationTesting will take 16 minutes (4 Testing will take 16 minutes (4 minutes per graph)minutes per graph)Testing materials will be collected Testing materials will be collected and processedand processed

Your feedbackYour feedback

-About hypotheses

-About procedure

-About materials

-???

Selected referencesSelected references•• Cleveland, W. S. (1993). A model for studying display methods ofCleveland, W. S. (1993). A model for studying display methods of statistical statistical

graphics. graphics. Journal of Computational and Graphical StatisticsJournal of Computational and Graphical Statistics, , 22(4), 323(4), 323--343.343.•• Cleveland, W. S., & McGill, R. (1984). Graphical perception: TheCleveland, W. S., & McGill, R. (1984). Graphical perception: Theory, ory,

experimentation, and application to the development of graphicalexperimentation, and application to the development of graphical methods. methods. Journal of American Statistical Association, 79Journal of American Statistical Association, 79(387), 531(387), 531--554.554.

•• Holmes, S. (1993). Comment on Holmes, S. (1993). Comment on ““A model for studying display methods of A model for studying display methods of statistical graphics.statistical graphics.”” Journal of Computational and Graphical Statistics, 2Journal of Computational and Graphical Statistics, 2(4), (4), 349349--353. 353.

•• LohseLohse, G. L. (1997). The role of working memory on graphical informat, G. L. (1997). The role of working memory on graphical information ion processing. processing. Behavior and Information TechnologyBehavior and Information Technology, , 1616(6), 279(6), 279--308.308.

•• SchnotzSchnotz, W. (2002). Towards and integrated view of learning from text a, W. (2002). Towards and integrated view of learning from text and nd visual displays. Educational Psychology Review, 14(1), 101visual displays. Educational Psychology Review, 14(1), 101--120120

•• Shah, P., & Carpenter, P. (1995). Conceptual limitations in compShah, P., & Carpenter, P. (1995). Conceptual limitations in comprehending line rehending line graphs. graphs. Journal of Experimental Psychology, 124Journal of Experimental Psychology, 124(1), 43(1), 43--61.61.

•• Shah, P., & Shah, P., & HoeffnerHoeffner, J. (2002). Review of graph comprehension research: , J. (2002). Review of graph comprehension research: Implications for instruction. Implications for instruction. Educational Psychology Review,Educational Psychology Review, 1414(1), 47(1), 47--69.69.

•• TufteTufte, E. R. (1983). , E. R. (1983). The visual display of quantitative information and The visual display of quantitative information and envisioning informationenvisioning information. . CreshireCreshire, Connecticut: Graphics Press. , Connecticut: Graphics Press.

•• WainerWainer, H. (1997). , H. (1997). Visual RevelationsVisual Revelations. New York: Copernicus. . New York: Copernicus. •• Wilkinson, L. (1993). Comment on Wilkinson, L. (1993). Comment on W.S.ClevelandW.S.Cleveland, a model for studying display , a model for studying display

methods of statistical graphics. methods of statistical graphics. Journal of Computational and Graphical Journal of Computational and Graphical Statistics, 2(4)Statistics, 2(4), 355, 355--360. 360.