Emotional%20Intelligence%20and%20Academic%20Achievement%20in%20Higher%20Education

1
Emotional Intelligence and Academic
Achievementin Higher Education

• Presented at
• Higher Education Symposium on Emotional
  Intelligence
• Georgetown University
• October 2-3, 2008
• By
• Dr. Svetlana S. Holt
• Woodbury University

2
Background

• College student body is rapidly emerging as a
  diverse population reflective of the evolving
  needs of the American society (Astin, 1996
  Starks, 1989 London, 1992 Cote Levine, 2000
  Karabel, 2005 Williams, 2004).
• Correlation exists between academic attrition and
  a societys economic well-being (Vela, 2003
  Arendale, 1994 Sexton, 1999 Noel-Levitz, 2005)
  .
• Higher education institutions are facing the
  problem of matriculating, retaining, and
  graduating the best talent and at the same time
  upholding academic standards and integrity
  (Burton Ramist, 2001 US Department of
  Education, 2005 College Board, 2005 Williams,
  2004).

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Problem Statement

• Traditional measurements of intelligence, such as
  SAT scores, are only one way to predict academic
  outcomes for college students. However,
  attrition rates cause universities, as well as
  students, economic hardship, and suggest that
  other factors, in addition to intelligence tests,
  matter. Emotional intelligence is suggested as
  one of the predictors of academic outcomes.

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Purpose of the Study

• The purpose of this research was to determine if
  emotional intelligence (as measured by MSCEIT) in
  undergraduate college students is related to
  academic achievement (as measured by GPA, units
  earned per semester, and intent to graduate)
  and/or traditional intelligence (as measured by
  SATs).

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Review of Relevant Literature and Research

• Criteria and predictors of academic outcomes
• Graduation rates (Camara, 2003 HERI, 2005)
• SAT scores versus GPA (College Board, 2005
  Golberg, 1990 Rothstein, 2004 Fairtest.org,
  2005 Bonfadini, 2005 DeJong, 2005)
• Predictors of degree attainment (Willingham,
  1985 Astin, 1996 Burton Ramist, 2001 Camara,
  2003 Young Corbin, 2001 Camara Echtenacht,
  2004)
• Emotional Intelligence
• Classic research and growing awareness
  (Aristotle, 355 B.C.Thorndike, 1920 Gardner,
  1983 Rotter, 1956 Hilgard, 1980)
• Existing schools of thought and definitions
  (Goleman, 1995 Bar-On, 1997 Mayer Salovey,
  1997)
• Connecting emotions and cognitive processes
• Measurements

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Review of Relevant Literature and Research
(Continued)

• Classic research on learning and emotions (Plato
  Aristotle Piaget Locke Skinner Cage Suppes
  Thoreson Wittrock Bettelheim Tyler
  Havinghurst)
• Acquiring learning through interacting with
  environment
• Behaviorist approach learning in response to
  stimuli
• Psychoanalytic approach body and mind function
  as system
• Emerging research on EI and schools
• Combination/self-report studies (Schilling, 1996
  Wilkins, 2004 La Civita, 2003 Jaeger, 2001
  Tehan, 2001 Boyce, 2001 Edison, 2002 Gumora,
  1999 Barchard, 2003 Vela, 2003 Stottlemyer,
  2002)
• Ability studies (Drago, 2004 Abdullah, 2004
  Lopes, 2004, Lewis, 2004)
• Enhancing EI (Stenberg, 2004 Narodillo-Dias,
  2003 Brackett, 2006 Chang, 2006)
• EI and instructional effectiveness (Rehfeld,
  2002 Yerly, 2000 Peroune, 2004 Lake, 2004
  Haskett, 2003 Bennoua, 2003 Mertz, 2003
  Kamarinos, 2002)

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Description of Characteristics

• Independent characteristics
• Age (variable)
• Gender (attribute)
• Ethnicity (attribute)
• Type of program enrolled (attribute)
• SAT scores (variable)
• EI level measured by MSCEIT (variable)

• Outcome characteristics
• Intent to graduate on a Likert scale of 1-5
  (variable)
• Level of satisfaction with educational experience
  on a Likert scale of 1-5 (variable)
• Cumulative GPA (variable)

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Data Analyses

• Statistical software Excel and SPSS 14.0
• Descriptive data means, SD, min. and max. values
  (Moore McCabe, 1993 )
• Correlation analyses
• Scatter plots
• Positive/negative relationship (Gay Airasian,
  2000 Vogt, 1999 Heiman, 2000)
• Strength of the relationship (r as a correlation
  coefficient)
• Regression Analyses

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Demographics and Descriptive Stats

• 124 usable data sets
• 65 women
• Mean age 26.5
• 64.5 speak English as first language
• Mean work hours 23.3
• Mean GPA 3.3
• Mean SAT 1066
• Mean units per semester 9.6
• High satisfaction
• High intent to graduate
• Low average EI levels

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• EI Scores Min. Max. Mean SD
• Faces Task 41.20 142.90 100.50 27.12
• Facilitations Task 56.50 133.10 99.60 17.80
• Changes Task 59.30 116.90 90.08 11.77
• Em. Mgt. Task 63.30 117.70 93.04 12.45
• Pictures Task 59.70 113.20 94.66 12.15
• Sensations Task 60.30 115.80 91.43 15.09
• Blends Task 53.90 111.10 90.32 12.76
• Social Management Task 61.40 111.80 91.68 12.89
• Perc. Em. Branch 29.10 132.30 94.86 17.25
• Using Emotions Branch 55.50 126.90 93.09 17.70
• Underst. Em. Branch 54.30 113.00 88.90 13.19
• Manag. Em. Branch 58.30 114.00 91.82 12.96
• Emotional Exp. Area 31.90 128.70 92.45 18.88
• Emotional Reas. Area 47.00 115.00 89.98 12.65
• Total EI 36.80 117.90 89.90 16.16

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Relationship between EI and GPA
_______Pearson Correlations for GPA and
EI________________________________________________
_______________ EI Scores GPA Faces
Task -.021 Facilitations Task .015 Changes
Task .093 Emotional Management Task .226
Pictures Task -.015 Sensations Task .01 Blends
Task .083 Social Management Task
.297 Perceiving Brach .005 Using
Branch .014 Understanding Branch .095
Managing Branch .290 Emotional Experiencing
Area .020 Emotional Reasoning Area .222 EI
Total .126 _____________________________________
__________________________________ p .05 p
.01 (2-Tailed)
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Relationship between predictors of academic
achievement, GPA, and Units/semester (Q15)

• Pearson Correlations for Measures of Academic
  Achievement with Emotional Intelligence Scores (N
  124)
• Predictors of Acad. Ach. GPA Units/Semester
• Faces Task -.021 -.003
• Facilitations Task .015 -.082
• Changes Task .093 -.049
• Emotional Management Task .226 -.050
• Pictures Task -.015 -.040
• Sensations Task .010 -.097
• Blends Task .083 -.010
• Social Management Task .297 -.048
• Perceiving Brach .005 -.030
• Using Branch .014 -.095
• Understanding Branch .095 -.030
• Managing Branch .290 -.066
• Emotional Experiencing Area .020 -.065
• Emotional Reasoning Area .222 -.054
• EI Total .126 -.055

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Regression for GPA

• GPA 1.910 .010 Managing Emotions Branch Score
  .115 Satisfaction with Educational Experience
  score
• Rsquared for the model is .144, which means that
  collectively, the variables account for
  approximately 14 of the variation in GPA.

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Regression for Intent to graduate

• Intent to graduate 3.9 .583 Satisfaction with
  Educational Experiences - .02 Understanding
  Emotions Branch score.
• Rsquared for the model is .171, which means that
  collectively, the variables account for
  approximately 17 in the variance in Intent to
  Graduate.

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Regression for Units/Semester

• Units per semester 15.8 - .083 Hours worked per
  week - .161 age.
• Rsquared for the model is .104, which means that
  collectively, the variables account for
  approximately 10 of variance in Units earned per
  semester.

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Regression for GPA including task/branch scores

• GPA (p .021) GPA 1.514 .046 Satisfaction
  with Educational Experiences .025 Emotional
  Management Task score .038 Social Management
  task score- .046 Managing Emotions branch score.
• Rsquared for the model is .107, which means that
  collectively, the variables account for
  approximately 10 of the variance in GPA.

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Relationship between EI, age, and academic
achievement

• Pearson Correlations for Age, Emotional
  Intelligence, and Measures of Academic
  Performance (N124)
• EI and Academic Achievement Age
• Faces Task -.185
• Facilitations Task .010
• Changes Task .005
• Emotional Management Task .005
• Pictures Task -.056
• Sensations Task -.002
• Blends Task -.068
• Social Management Task .103
• Perceiving Brach -.149
• Using Branch -.011
• Understanding Branch -.035
• Managing Branch .067
• Emotional Experiencing Area -.092
• Emotional Reasoning Area .020
• EI Total -.057

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Relationship between gender, EI, and Academic
achievement

• Pearson Correlations for Gender, Emotional
  Intelligence, and Measures of Academic
  Performance (N124)
• EI and Academic Achievement Gender (Female)
• Faces Task .187
• Facilitations Task .100
• Changes Task -.066
• Emotional Management Task .105
• Pictures Task .011
• Sensations Task .034
• Blends Task -.019
• Social Management Task .021
• Perceiving Brach .148
• Using Branch .078
• Understanding Branch -.050
• Managing Branch .061
• Emotional Experiencing Area .163
• Emotional Reasoning Area .005
• EI Total .081

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Significant model to predict GPA for Women

• GPA 2.935 0.01 SAT total score - 0.016 Age
  0.048 Emotional Intelligence total score 0.016
  Emotional Reasoning Area score 0.028 Emotional
  Experiencing Area score.
• Rsquared for the model was .184, which means
  that collectively, the variables account for
  approximately 18 of the variance in GPA for
  women.

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Findings

• Participants had average SAT scores, above
  average GPAs, and low average Emotional
  Intelligence scores
• Significant relationship was found between GPA
  and 4 EI abilities
• Emotional management task
• Social management task
• Managing Emotions branch
• Emotional Reasoning Area
• Age and gender (female) are positively correlated
  with GPA
• Non-native English speakers scored lower on
  Blends task of MSCET
• Hispanics scored higher on Faces tasks than
  Asians and African Americans
• Women scored higher than men on the Faces task

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What findings mean

• There are both academic and non-academic factors
  in student success
• There is a relationship between academic success
  and emotional intelligence
• The better a student is at managing his/her
  emotions, the better he/she is likely do in
  college
• Emotions and cognition are deeply intertwined
• Emotions make us smarter by helping shape
  rational thought and learn practical skills

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Implications

• Other factors, in addition to traditional
  intelligence, should be taken into consideration
  in recruiting and retaining students.
• Emotional Intelligence curriculum for students
• Emotional intelligence training for faculty and
  staff
• Administration process for Higher Education
  Institutions

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Significance of the Study

• Adds to deeper understanding of the role of
  emotions in cognitive processes
• Contributes to research on correlating EI
  interpretations and measurement approaches
• Stimulates reevaluation of the traditional views
  upon the factors predicting and fostering
  academic achievement for college recruiting
  specialists, faculty, and students
• Supports the need to incorporate EI curricula
  into academic programs in colleges and
  universities

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Recommendations for further research

• Larger sample with greater geographical area
• A study on whether EI affects degree/career
  choice
• Relationship between the EI of faculty and staff
  and student success
• Testing the GPA model
• Controlling for the Big Five characteristics
• Further exploration of gender- and
  ethnicity-specific abilities