Application of Exploratory Structural Equation Modeling to Evaluate the Academic Motivation Scale

In this research, the authors examined the construct validity of scores of the Academic Motivation Scale using exploratory structural equation modeling. Study 1 and Study 2 involved 1,416 college students and 4,498 high school students, respectively. First, results of both studies indicated that the factor structure tested with exploratory structural equation modeling provides better fit to the data than the one tested with confirmatory factor analysis. Second, the factor structure was gender invariant in the exploratory structural equation modeling framework. Third, the pattern of convergent and divergent correlations among Academic Motivation Scale factors was more in line with theoretical expectations when computed with exploratory structural equation modeling rather than confirmatory factor analysis. Fourth, the configuration of convergent and divergent correlations connecting each Academic Motivation Scale factors to a validity criterion was more in line with theoretical expectations with exploratory structural equation modeling than with confirmatory factor analysis.

[1]  Markus Appel,et al.  A Short Measure of the Need for Affect , 2012, Journal of personality assessment.

[2]  Kit-Tai Hau,et al.  Goodness of fit in structural equation models , 2005 .

[3]  Vassilis Barkoukis,et al.  The assessment of intrinsic and extrinsic motivation and amotivation: Validity and reliability of the Greek version of the Academic Motivation Scale , 2008 .

[4]  K. Cokley,et al.  A Psychometric Investigation of the Academic Motivation Scale Using a United States Sample , 2001 .

[5]  L. Angeles Evaluating Cutoff Criteria of Model Fit Indices for Latent Variable Models with Binary and Continuous Outcomes , 2002 .

[6]  Roger E. Millsap,et al.  Assessing Factorial Invariance in Ordered-Categorical Measures , 2004 .

[7]  B. Muthén,et al.  Applying Multigroup Confirmatory Factor Models for Continuous Outcomes to Likert Scale Data Complicates Meaningful Group Comparisons , 2004 .

[8]  Gordon W. Cheung,et al.  Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance , 2002 .

[9]  S. Jeanne Horst,et al.  Evaluating existing and new validity evidence for the Academic Motivation Scale , 2005 .

[10]  F. Guay,et al.  Predicting Career Indecision: A Self-Determination Theory Perspective , 2003 .

[11]  R. C. Durfee,et al.  MULTIPLE FACTOR ANALYSIS. , 1967 .

[12]  Louis W. Glorfeld An Improvement on Horn's Parallel Analysis Methodology for Selecting the Correct Number of Factors to Retain , 1995 .

[13]  R. Schumacker,et al.  A beginner's guide to structural equation modeling, 3rd ed. , 2010 .

[14]  F. Guay Motivations Underlying Career Decision-Making Activities: The Career Decision-Making Autonomy Scale (CDMAS) , 2005 .

[15]  S. Anderson,et al.  Therapist Use-of-Self Orientations Questionnaire: A Reliability and Validity Study , 2011 .

[16]  Andreas Ritter,et al.  Structural Equations With Latent Variables , 2016 .

[17]  André Beauducel,et al.  On the Performance of Maximum Likelihood Versus Means and Variance Adjusted Weighted Least Squares Estimation in CFA , 2006 .

[18]  R. Ryan,et al.  Perceived locus of causality and internalization: examining reasons for acting in two domains. , 1989, Journal of personality and social psychology.

[19]  Gregory R. Hancock,et al.  Structural equation modeling: A second course, 2nd ed. , 2013 .

[20]  K. Yuan,et al.  On the Likelihood Ratio Test for the Number of Factors in Exploratory Factor Analysis , 2007 .

[21]  R. Vallerand,et al.  Self-determination and persistence in a real-life setting: toward a motivational model of high school dropout. , 1997, Journal of personality and social psychology.

[22]  P. Pintrich A Motivational Science Perspective on the Role of Student Motivation in Learning and Teaching Contexts. , 2003 .

[23]  S. Finney Nonnormal and categorical data in structural equation modeling , 2013 .

[24]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[25]  L. Pelletier,et al.  Longitudinal Cross-Gender Factorial Invariance of the Academic Motivation Scale , 2006 .

[26]  A. Morin,et al.  The Eating Attitudes Test-26 Revisited using Exploratory Structural Equation Modeling , 2013, Journal of Abnormal Child Psychology.

[27]  J. Horn A rationale and test for the number of factors in factor analysis , 1965, Psychometrika.

[28]  Gregory R. Hancock,et al.  Structural equation modeling : a second course , 2006 .

[29]  W. Velicer,et al.  Comparison of five rules for determining the number of components to retain. , 1986 .

[30]  B. Avolio,et al.  . , 2005, The Leadership Quarterly.

[31]  Evelyne F. Vallières,et al.  The Academic Motivation Scale: A Measure of Intrinsic, Extrinsic, and Amotivation in Education , 1992 .

[32]  R. J. Vallerand,et al.  Vers une méthodologie de validation trans-culturelle de questionnaires psychologiques: Implications pour la recherche en langue française. , 1989 .

[33]  Edward L. Deci,et al.  Intrinsic Motivation and Self-Determination in Human Behavior , 1975, Perspectives in Social Psychology.

[34]  R. Vallerand,et al.  Autonomous, Controlled, and Amotivated Types of Academic Motivation: A Person-Oriented Analysis , 2007 .

[35]  Nicholas D. Myers,et al.  Coaching efficacy and exploratory structural equation modeling: a substantive-methodological synergy. , 2011, Journal of sport & exercise psychology.

[36]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[37]  E. Deci,et al.  Handbook of Self-Determination Research , 2002 .

[38]  Sean D. Kristjansson,et al.  Smoking outcome expectancies in young adult female smokers: individual differences and associations with nicotine dependence in a genetically informative sample. , 2011, Drug and alcohol dependence.

[39]  Dianne M. Finkelstein,et al.  A Beginner's Guide to Structural Equation Modeling , 2005, Technometrics.

[40]  J. Kahn Factor Analysis in Counseling Psychology Research, Training, and Practice , 2006 .

[41]  R. J. Vallerand,et al.  Construction et validation de I'echelle de motivation en educa- tion (EME) , 1989 .

[42]  E. Deci,et al.  The "What" and "Why" of Goal Pursuits: Human Needs and the Self-Determination of Behavior , 2000 .

[43]  James C. Hayton,et al.  Factor Retention Decisions in Exploratory Factor Analysis: a Tutorial on Parallel Analysis , 2004 .

[44]  H. Marsh,et al.  Construct Validity of the Multidimensional Structure of Bullying and Victimization: An Application of Exploratory Structural Equation Modeling. , 2011 .

[45]  R. J. Vallerand,et al.  Construction et validation de l'Échelle des Perceptions de Compétence dans les Domaines de Vie (EPCDV). , 1993 .

[46]  R. P. McDonald,et al.  Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size , 1988 .

[47]  Duane T. Wegener,et al.  Evaluating the use of exploratory factor analysis in psychological research. , 1999 .

[48]  Evelyne F. Vallières,et al.  On the Assessment of Intrinsic, Extrinsic, and Amotivation in Education: Evidence on the Concurrent and Construct Validity of the Academic Motivation Scale , 1993 .

[49]  B. Muthén,et al.  Exploratory Structural Equation Modeling , 2009 .

[50]  H. Marsh,et al.  In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler's (1999) Findings , 2004 .

[51]  Goodness of Fit Indices , 2014 .

[52]  F. Chen Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance , 2007 .

[53]  A. Morin,et al.  Psychometric properties of the Center for Epidemiologic Studies Depression Scale (CES-D) in French clinical and nonclinical adults. , 2011, Revue d'epidemiologie et de sante publique.

[54]  R. Vallerand,et al.  Intrinsic, extrinsic, and amotivational styles as predictors of behavior: A prospective study. , 1992 .

[55]  Ulrich Trautwein,et al.  Please Scroll down for Article Structural Equation Modeling: a Multidisciplinary Journal Exploratory Structural Equation Modeling, Integrating Cfa and Efa: Application to Students' Evaluations of University Teaching , 2022 .

[56]  R. Henson,et al.  Use of Exploratory Factor Analysis in Published Research , 2006 .

[57]  W F Velicer,et al.  Factors Influencing Four Rules For Determining The Number Of Components To Retain. , 1982, Multivariate behavioral research.

[58]  Jeanne A. Teresi,et al.  An Essay on Measurement and Factorial Invariance , 2006, Medical care.

[59]  Andrew J. Martin,et al.  Methodological Measurement Fruitfulness of Exploratory Structural Equation Modeling (ESEM): New Approaches to Key Substantive Issues in Motivation and Engagement , 2011 .

[60]  L. Guttman Some necessary conditions for common-factor analysis , 1954 .

[61]  G. Bennett,et al.  The assessment. , 1989, Health visitor.

[62]  J. Osborne,et al.  Sample size and subject to item ratio in principal components analysis. , 2004 .

[63]  D. Fadda,et al.  Validation of an Italian Version of the Oxford Happiness Inventory in Adolescence , 2012, Journal of personality assessment.

[64]  Herbert W Marsh,et al.  Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis. , 2014, Annual review of clinical psychology.

[65]  R. Vallerand,et al.  Toward a tripartite model of intrinsic motivation. , 2012, Journal of personality.

[66]  C. Lonigan,et al.  Psychometric evaluation of the Children's Behavior Questionnaire-Very Short Form in preschool children using parent and teacher report , 2013 .

[67]  F. Guay,et al.  Validation d'un modèle motivationnel des aspirations professionnelles , 2016 .

[68]  A. Morin,et al.  Cross-validation of the short form of the physical self-inventory (PSI-S) using exploratory structural equation modeling (ESEM) , 2011 .

[69]  W. Meredith Measurement invariance, factor analysis and factorial invariance , 1993 .