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
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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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
Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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.
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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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
Introduction and overview SAPA methodology Results References
SAPA: what the subject sees
A
ab B
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Introduction and overview SAPA methodology Results References
SAPA: what the subject sees
A
ac C
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Introduction and overview SAPA methodology Results References
SAPA: what the subject sees
A
ad D
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Introduction and overview SAPA methodology Results References
SAPA: what the subject sees
B
bc C
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Introduction and overview SAPA methodology Results References
SAPA: what the subject sees
B
bd D
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Introduction and overview SAPA methodology Results References
SAPA: what the subject sees
C
cd D
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Introduction and overview SAPA methodology Results References
SAPA: what the experimenter sees: A Synthetic matrix
A
ab B
ac bc C
ad bd cd D
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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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
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Introduction and overview SAPA methodology Results References
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
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Introduction and overview SAPA methodology Results References
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
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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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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Introduction and overview SAPA methodology Results References
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