Temperament, ability, and interests predict …...Introduction and overview SAPA methodology...

Introduction and overview SAPA methodology Results References

Temperament, ability, and interests predictimportant real world choices

William Revelle and David CondonPart of a Symposium:

Motivation as a basic personality process.Organized by Luke Smillie and Joshua Wilt

Annual meeting of the Society for the Study of Motivation

Personality, Motivation and Cognition LaboratoryDepartment of PsychologyNorthwestern UniversityEvanston, Illinois USA

Chicago, May 24, 2012

1 / 41


Outline

1 Introduction and overviewPersonality and MotivationBeyond Affect, Behavior, Cognition and Desire:Temperament, Ability and InterestsA need for integrative studies

2 SAPA methodologyConceptual overviewTechnical Overview

3 ResultsAnalytical TechniqueTAI and motivational choice

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The study of personality includes the study of motivation

1 Personality is the coherent patterning over time and space ofAffect, Behavior, Cognition and Desire.

Items in most personality tests may be organized in terms oftheir relative emphasis on the ABCDs.We have examined the coherency of ABCDs over short periodsof time (e.g., the patterning of energetic and affective changesduring the day over several weeks using text messaging).We have also examined it cross sectionally to examine longtime choice behavior with meaningful outcomes.

2 Personality and motivationTraditional personality measures emphasize average levels ofABCDs.Personality traits reflect sensitivities to motivationally salientstimuli.

Personality traits are the first derivatives of personality statesin reaction to motivationally salient stimuli.

Short term: Affective reactions and goal directed behaviorLong term: Meaningful life choices: College major andoccupation

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Personality and Temperament

Hogan (1982) distinguishes between personality as identity andpersonality as reputation. To this we would add actions.

1 Identity

How we see ourselvesStudies of the structure of self report

2 Reputation

How others see usStudies of the structure of peer report

3 Actions

What we actually doStudies of the residues of our choices and our actions.One important outcome is choice of college major.Another is the choice of occupation.

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Going beyond the ABCDs: Personality as Temperament, Ability, andInterests

1 Temperament: what we usually do

Identity, Reputation, and ActionsAffective, Cognitive and Behavioral reactions to situations: the“Big 5” (Goldberg, 1990), the “Giant 3” (Eysenck, 1990)

2 Ability: What we can do

Measures of intellectual ability – life as an intelligence test(Deary, Penke & Johnson, 2010; Gottfredson, 1997; Horn &Cattell, 1966; Johnson & Bouchard, 2005)

3 Interests: What we like to do

6 dimensions: Realistic, Investigative, Artistic, Social,Enterprising, Conventional (aka RIASEC Holland, 1996)2 dimensions (e.g., people vs. things/facts vs. ideas, Prediger& Vansickle, 1992) of interests

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Traditional model of Temperament, Abilities, and Interests

TemperamentE N

O

CA

Abilities gV P

R

Interests

R

S

I

AE

C

Temperament

2- 5 dimensions reflectingindividual differences in Affect,Behavior, Cognition, Desire

Ability

1 g

2 gf gc

Interests

2 broad dimensions organizing6-8 specific interests

1 People vs. Things

2 Facts vs Ideas6 / 41


Personality as Temperament, Ability, and Interests

1 It has long been known that Temperament, Ability andInterests (TAI) are interrelated predictors of long termoutcomes (Kelly & Fiske, 1950).

Unfortunately, the study of interests has been relegated tovocational counselorsAbility has been studied by educational psychologists andIndustrial Organizational psychologists.Need to integrate these in a general theory of personality andmotivated choice.

2 A few groups do try to integrate temperament and ability

These include Lubinski & Benbow (2000); Lubinski, Webb,Morelock & Benbow (2001); Lubinski & Benbow (2006)Ackerman (1997), Ackerman & Heggestad (1997)Kuncel, Campbell & Ones (1998); Kuncel, Hezlett & Ones(2001); Kuncel, Crede & Thomas (2005)

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Traditional model of Temperament, Abilities, and Interests

TemperamentE N

O

CA

Abilities gV P

R

Interests

R

S

I

AE

C

Outcome

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Motivation involves choice

1 Motivational models emphasize intensity as well as direction

Performance models emphasize efficiency in any one taskHow many resources are available for a particular task

2 Direction of behavior (aka resource allocation) emphasizeschoice

Dynamic models of choice (the Dynamics of Action) fromAtkinson & Birch (1970) or a reparameterization (theCues-Tendency-Action model) by Revelle (1986) emphasizethat behaviors inhibit each other.For computer simulations of choice behavior using theCues-Tendency-Action (CTA) model see Fua, Horswill, Ortony& Revelle (2009); Fua, Revelle & Ortony (2010)

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Motivation involves choice between incompatible outcomes

TemperamentE N

O

CA

Abilities gV P

R

Interests

R

S

I

AE

C

Outcome1

Outcome2

Outcome3

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A need for integrative studies

Prior work has shown that there is a need to integrateTemperament, Abilities and Interests.

But how to do it?

To integrate the areas requires large sample sizes, ease of datacollection, and a diverse subject population.

Some do this through meta analysis, some use broad basednational samples.

Is it possible for single labs to do integrative studies?

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How to do integrative studies?

Problem of small samples sizes based upon collegeundergraduates. Typical subject pools are neither largeenough nor diverse enough.

Expensive to get access to large and diverse populationsExceptions include national and international survey samplesusing preselected items:

National Longitudinal Study of Youth (NLSY)Program for International Student Assessment (PISA)German Socio-Economic Panel

Is it possible to do large based sampling with tailored items?

Yes, use the web.

12 / 41


Synthetic Aperture Personality Assessment (SAPA)

Using the web and open source materials to collect data ontemperament, ability and interests

Synthetically form large covariance matrices from smallersubsets of itemsEach subject given ≈ 50 personality, 10 interest, and 14-16ability items sampled from the larger pool.Total pool of items > 1000

≈ 400 personality items primarily from InternationalPersonality Item Pool Goldberg (1999)92 interest items for Oregon Vocational Interest Scales(Pozzebon, Visser, Ashton, Lee & Goldberg, 2010)80 ability items (home brewed at NU)Demographic items include age, sex, education, race, country,college major, occupation (if appropriate)Resulting sample sizes > 50, 000 − 250, 000

College major, occupational status and interest items added in9/10

Data to be summarized include ≈ 65, 000 participants

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Method

1 Synthetic Aperture Personality Assessment (Revelle, Wilt &Rosenthal, 2010) forms large covariance matrices by samplingitems across people

≈ 120/day particpants are recruited totest.personality-project.org

Each participant is given 60-70 itemsTotal set of items being analyzed > 500

2 Item content being sampled100 “IPIP” Big 5 items≈ 200 other temperamental items56-80 home brewed ability items92 Oregon Vocational Interest items (ORVIS)

3 Although > 200, 000 participants have been run in all, we willreport only those data from the last 65,000

4 Demographic information includedAge, GenderLevel of educationCollege major and broad field (if appropriate)Occupation (if appropriate) 14 / 41

test.personality-project.org


SAPA: what the subject sees

A

ab B

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A

ac C

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A

ad D

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B

bc C

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B

bd D

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C

cd D

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SAPA: what the experimenter sees: A Synthetic matrix

A

ab B

ac bc C

ad bd cd D

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SAPA: Technical overview

1 n x n synthetic covariance matrices are formed by giving pitems to Np subjects

N Total number of subjectsn Total number of items in synthetic matrixp Probability of any item being given

pN Number of subjects taking any one itemp2N Number of subjects for any pair of items

2 Basic statistics

Data are Massively Missing at RandomMeans and Variances are based upon pN subjectsCovariances are based upon p2N subjects

3 Power of large samples and sampling of items

100-150 people per day => 40,000 subjects per year700-1000 subjects/weekBy varying p, one can prototype items rapidly.

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International Personality Item Pool (IPIP) Big 5: sample items

Conscientiousness Do things according to a plan.

Agreeableness Inquire about others’ well-being.

Neuroticism/Stability Have frequent mood swings.

Openness Am full of ideas

Extraversion Make friends easily

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Oregon Vocational Interest Scales: sample items

Adventure Would like to be a professional athlete.

Altruism Like to care for sick people.

Analytic Would like to be a chemist.

Artistic Create works of art.

Erudition Would like to be a translator or interpreter.

Leadership Like to make important things happen.

Organization Would like to be the financial officer for a company.

Practical Would like to care for cattle or horses.

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Cognitive Ability items

1 Self reported values on standardized tests

SAT VerbalSAT QuantitativeACT

2 Open source items developed for the SAPA project

Analytic Alphanumeric sequencesMatrix Analogous to Raven’s matrices

3 D rotation Difficulty created by number of rotationsVerbal Basic vocabularyFull IQ Weighted sum score of the parts

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Analytical approach: All analyses done in R

1 R: An international collaboration http://R-cran.org

2 R: The open source - public domain version of S+

3 R: Written by statistician (and all of us) for statisticians (andthe rest of us)

4 R: Not just a statistics system, also an extensible language.

This means that as new statistics are developed they tend toappear in R far sooner than elsewhere.For example, a recent issue of Pschological Methods had atleast three articles with examples or supplementary work donein RR facilitates asking questions that have not already been asked.

5 Special functions for SAPA have been written in R and areincluded in the psych package.

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http://R-cran.org


Analytical reporting

1 Given the sample sizes, statistical significance is not an issue,but rather the size of the effects.

2 Correlation is an appropriate effect size measureCorrelations between continuous variables are reported asPearson rCorrelations between dichotomous variables are reported astetrachoric correlationsCorrelations between continuous and dichotomous are reportedas biserialThese last two correlations make assumptions of normaldistributions of latent traits

3 Data displays are graphical techniques for showing thecomplex, multivariate structure of the data

Correlation strength reported as a “heat map” with positivecorrelations shaded as progressively darker shades of blue,negative correlations as darker shades of red.Some multidimensional plots

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Analysis of Temperament, Ability, Interests

1 Big 5 scale scores used an Item Response Theory (IRT)algorithm

With complete data, IRT and simple sum scores are almostidentical.SAPA data are Massively Missing at Random and are betterestimated using IRT techniques.

Two parameter model: item difficulty, item locationOne parameter model: item difficulty

2 Ability measures

SATV, SATQ, SATW and ACT were self reportediq measure was based upon IRT analysis and scoring

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Temperament, Ability and Interests

Temperament, Ability and Interests

AltruismLeadershipAdventure

OrganizationArtistic

ProductionAnalysisEruditionVEdiqR3DiqMXiqANiqFullIQACT

SATWSATQSATV

IntellectExtraversion

StabilityConscientious

Agreeable

Agreeable

Conscientious

Stability

Extraversion

Intellect

SATV

SATQ

SATW ACT

FullIQ

ANiq

MXiq

R3Diq

VEdiq

Erudition

Analysis

Production

Artistic

Organization

Adventure

Leadership

Altruism -1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

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Choice of college major reflects temperament, abilities and interests

1 Undergraduate majors/concentration provide feedback tostudents based upon performance.

2 Performance reflects both ability and time spent on the task

Students choose majors which reinforce their talentsInterests grow in response to feedback

3 Although many students can do well in many majors, they endup choosing those majors that maximally meet their needs.

4 Multiple ways of displaying these data

Majors sorted by abilityMajors sorted by a particular temperament (e.g.,conscientiousness)Majors in a multi-dimensional space of abilities x temperament

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Choosing majors as selection, optimization, and compensation

1 Traits and abilities are independent at individual level

This is seen in the plot of all the TAI variables based uponindividual

2 Majors draw for certain constellations of traits

Selection, Optimization, and Compensation (Baltes & Baltes,1990)Sorting of majors by TAI dimensions

3 Choice of major selects for constellations

This is seen in the plot of the personality dimensions at theaggregate level of majors

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College major sorted by Intelligence (top and bottom 10 majors)

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1gender

Agreeable

Conscientious

Extraversion

Stability

Intellect

FullIQ

Adventure

Analysis

Organization

Leadership

Altruism

Erudition

Artistic

TEIQ

PhysicsMathematics

Chem.Bio.EngNeuroscienceElectrical.Eng

Computer.ProgrammingMechanical.Eng

EconomicsChemistry

MusicCriminology

Other.Community.Social.SvssSocial.WorkK.preK.Edu

NursingCriminal.Justice.CorrectionsHuman.Development.Family

Major.NAHealth.Svcs.AdminMedical.Assisting

-30-21-23-3-43-43-47-25-10-16-120264937-519-82834

-19-17-12-12-14-23-14-14-9-1114191115212-151512

-9-92-53-101-24-9957416148-222116

-14-17-8-11-8-19-6-3-7-6437-7754-557

1034-410710630331-5-120-900

27149181010121412160-3-9-16-9-5-15-14-5-10

43323129282727262424-13-13-16-16-18-18-18-19-21-33

8-1825-115-24412-11314-5-20-15-103335-7-12

6137322534394220462-10-4-14-20-6-116-6-14-5

-53-1-710920265-13-6132-11-4311-201018

-4-15-313-1014256416-4-27-2215-6-3-10

-11-32-197-18-28-13-13-4-6-162130-119-229-161318

27-12313-14261118-5-4-6-11-19-715-12-6-8

114-28-1-4-5-7146-8-12-91-12-246-2-13-9

-10-1-103-3-21-5-4-1-13113120-111-1778

Majors by IQ

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College major sorted by Conscientiousness (top and bottom 10 )

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1gender

Agreeable

Conscientious

Extraversion

Stability

Intellect

FullIQ

Adventure

Analysis

Organization

Leadership

Altruism

Erudition

Artistic

TEIQ

Health.Svcs.AdminBiz.Admin.Mgmt

NursingMedical.AssistingEdu.Administration

Criminal.Justice.CorrectionsAccounting

Health.Sciences.GeneralOther.Medicine.Allied.Health

Elementary.EduMathematics

PhysicsComputer.Programming

Other.Language.LitStudiesOther.PerfVisual.Art

Graphic.ArtsFine.Studio

Fiction.WritingPhilosophyMajor.NA

28-1137345-5

-4141635-21-30-436-31116-17-8

153151292-3111117-17-19-23-4-4-5-5-7-15-15

2118161615141312109-9-9-10-10-11-12-16-16-17-22

51077125-5334-17-14-19-11-5-8-8-11-8-5

09-101223-13-33107-1-6-3-8-125-9

-50-9-106-5-10-7-6-10142710171211172327-14

-21-8-18-330-182-10-6-43243272175101124-19

-7-6-10-12933-4-21-16-188-2444-6-7-35

-14-7-6-50-11-113-31376139-2-11-11-12-1120-6

1030-418173401-6-153-59-4-100-152-10-20

-317-22-10714-13-9-16-15-405-7-16-1628-6

13-619189-2-21121920-32-11-28-2-10-23-21-28-9-16

-6-14-19-811-7-1-11-16-1-127434416161919-12

-13-10-12-918-24-12-3-14-1311-4631334035-2-2

712-18191-6-2610-1-10-21-7-29-89-6-20-17

Majors by Conscientiousness

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College major sorted by Extraversion (top and bottom 10 majors)

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1gender

Agreeable

Conscientious

Extraversion

Stability

Intellect

FullIQ

Adventure

Analysis

Organization

Leadership

Altruism

Erudition

Artistic

TEIQ

PR.AdvertisingMarketing

Physical.EduEdu.Administration

Communications.MediaStudiesBiz.Admin.MgmtDrama.Theater

Other.CommunicationsSecondary.Edu

NursingComputer.Eng

Other.Language.LitStudiesNeuroscienceFiction.Writing

Other.CISEnglish

CIS.GeneralPhysics

MathematicsComputer.Programming

15-8-1356-1168037-396-36-239-37-30-21-43

8159-1366915-13-4-12-7-8-7-15-19-17-23

13315-318-82616-1-10-5-16-5-8-1-9-9-10

18131212111010987-9-11-11-11-12-13-13-14-17-19

-251112-19-4-15-110-1-4-123-961037

-1-2-1364019-26-9101718236245271410

-92-120-4-863-2-1824212911171717433227

-101219-15-6-677-10144-1-7-4-1738-18-2

-14-14-180-17-7-22-150-634-225-1122-826613739

-414-1417-630-20-121-417-4-727-1114-539

1822-17101714515-2211513211-118-4-150

-12-13-79-18-6-2-42419-12-27-28-140-14-11-32-28

73-271116-1410117-1911341319-439127-14

136-251815-103794-12116-2835-215-311-4

1214211921210-1-1-1-1-73-6-9-4-12-10-1-21

Majors by Extraversion

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College major sorted by Stabilty–Neuroticsm (top and bottom 10 )

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1gender

Agreeable

Conscientious

Extraversion

Stability

Intellect

FullIQ

Adventure

Analysis

Organization

Leadership

Altruism

Erudition

Artistic

TEIQ

MgmtInfoSystems

Edu.Administration

Other.Eng.Tech.Major

Physical.Edu

Electrical.Eng

Mechanical.Eng

Computer.Eng

Physics

Industrial.Eng

Biz.Admin.Mgmt

Neuroscience

K.preK.Edu

Art.History

Other.PerfVisual.Art

Journalism

Fine.Studio

Major.NA

English

Art.Theory

Fiction.Writing

-29

5

-33

-13

-43

-47

-39

-30

-31

-11

-3

49

15

-3

4

11

-8

9

8

6

-6

9

-9

5

-14

-14

-13

-19

-11

3

-12

11

-6

-4

1

-5

-15

-7

-2

-7

7

15

3

3

3

1

-1

-9

2

18

-5

4

-4

-11

-9

-16

-22

-8

-8

-16

-1

12

-1

12

-8

-6

-9

-14

-2

10

-11

-7

-2

-5

2

-8

-5

-13

-5

-11

16

12

11

11

10

10

10

10

10

9

-4

-5

-5

-6

-6

-8

-9

-9

-9

-12

14

6

9

-13

10

12

10

27

4

0

18

-16

11

12

11

17

-14

24

13

23

14

0

16

-12

28

27

24

43

8

-8

29

-16

5

7

6

10

-19

17

6

11

18

9

31

21

15

44

14

8

13

-6

-1

-15

-13

4

9

-6

5

-17

-6

-7

8

0

20

-18

34

42

34

61

-1

-7

25

-20

-21

-11

8

-12

-6

-8

2

-11

4

17

14

-14

10

20

17

-5

19

30

-7

-11

-2

-10

-9

-15

-20

-11

-5

2

17

7

13

-1

-1

14

11

-4

-10

17

13

-27

-6

-7

13

-16

-6

-11

-8

2

7

9

-9

-7

-18

-13

-12

-11

2

-6

7

-1

0

-10

-17

-21

-16

0

-17

-28

-19

11

1

-27

-1

2

11

27

-11

-14

13

-11

36

4

23

16

-12

39

6

19

10

18

6

-25

-1

-5

11

1

-4

-10

-28

1

19

31

0

40

-2

15

42

35

18

19

-9

21

-3

-5

-1

-10

-3

12

3

0

12

-29

-5

9

-17

-4

-23

-6

Majors by Stability

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The relationship of personality and ability at the aggregate level

Agreeable

-0.1 0.1

0.55 0.68

-0.10 0.00 0.10

-0.27 -0.63

-0.2 0.2

-0.2

0.0

0.2

-0.81

-0.1

0.1 Conscientious

0.59 0.32 -0.74 -0.62

Extraversion

0.08 -0.54

-0.2

0.00.1

-0.72

-0.100.00

0.10 Stability

-0.04 0.25Intellect

-0.1

0.10.76

-0.2 0.0 0.2

-0.2

0.2

-0.2 0.0 0.1 -0.1 0.1

FullIQ

36 / 41


Major groups by Ability and Stability

-0.2 -0.1 0.0 0.1 0.2 0.3

-0.05

0.00

0.05

0.10

Major groups by Ability and Stability

Ability

Stability

Scl.ScMd.A.H

Busnss

EductnNtrl.S

Arts

Engnrn

Cm.S.S

Tchnlg

Lngg.L

Cmmnct

Math

Cl.R.S

Grp.NA

37 / 41


Major groups by Ability and Agreeableness

-0.2 -0.1 0.0 0.1 0.2 0.3

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

Major groups by Ability and Agreeableness

Ability

Agreeableness

Scl.Sc

Md.A.H

Busnss

Eductn

Ntrl.S

Arts

Engnrn

Cm.S.S

Tchnlg

Lngg.L

Cmmnct

Math

Cl.R.S

Grp.NA

38 / 41


Major groups by Ability and Conscientiousness

-0.2 -0.1 0.0 0.1 0.2 0.3

-0.2

-0.1

0.0

0.1

Major groups by Ability and Conscientiousness

Ability

Extraversion

Scl.Sc

Md.A.HBusnss

Eductn

Ntrl.S

Arts

Engnrn

Cm.S.S

Tchnlg

Lngg.L

CmmnctMath

Cl.R.S

Grp.NA

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Why are Ability and Temperament measures negatively correlated atthe group level?

1 Compensatory selection will lead to a negative correlation

Are Physicists selected to be disagreeable but smartAre educators selected be low on ability but highly agreeable?

2 Selection does not need to be compensatory, but merelyextreme.

If group A is selected for high ability, the mean score on othertraits should be averageIf group B is selected for on Agreeableness, the mean scores onability should be averageThis leads to a negative correlation between Ability andAgreeableness at the group level.

3 Feeback mechanisms are likely: people select into fields basedupon differences in characteristics of the fields.

What motivational interventions can we do to make STEMmajors seem more agreeable?

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Conclusion

1 Motivational choice can be seen in real world choices ofcollege major

Other examples include occupational choice

2 Using web based data techniques (e.g., SAPA), it is possible todo integrative studies of Temperament, Ability and Interests

3 Motivational choice reflects selection and compensation oftemperament ability, and interests

Majors that require high ability do not necessarily draw forsocially adaptive traitsMajors that require social skills do not necessarily draw forhigh ability

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Temperament, ability, and interests predict …...Introduction and overview SAPA methodology...

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