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Graduate Course Proposal Form Submission Detail - EDF7486

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Current Status: Approved, Permanent Archive - 2005-05-04
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  1. Department and Contact Information

    Tracking Number Date & Time Submitted
    1880 2005-01-26
     
    Department College Budget Account Number
    EDQ ED 171100000
     
    Contact Person Phone Email
    John Ferron 9745361 ferron@tempest.coedu.usf.edu

  2. Course Information

    Prefix Number Full Title
    EDF 7486 Application of Structural Equation Modeling in Education

    Is the course title variable? N
    Is a permit required for registration? N
    Are the credit hours variable? N
    Is this course repeatable?
    If repeatable, how many times? 0

    Credit Hours Section Type Grading Option
    3 C - Class Lecture (Primarily) R - Regular
     
    Abbreviated Title (30 characters maximum)
    Structural Equations in Ed
     
    Course Online? Percentage Online
    -

    Prerequisites

    EDF 7408 or equivalent

    Corequisites

    none

    Course Description

    Application of structural equation modeling in educational research, including path models, confirmatory factor analysis, structural modeling with latent variables, and latent growth curve models.


  3. Justification

    A. Please briefly explain why it is necessary and/or desirable to add this course.

    A recent study of the research reported in PsycINFO has indicated that structural equation modeling (SEM) has become the “preeminent method of data analysis” in the social sciences (Hershberger, 2003, p. 41). Research articles using structural equation m

    B. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service?

    This course will be an elective for students in Educational Measurement and Evaluation. Given the widespread application of multilevel modeling in education and related fields, it is anticipated that the majority of students in the program will choose this elective. In offerings as a Selected Topics Course, it has drawn students from educations, psychology, public health, nursing, business, etc. It is anticipated that this will continue.

    C. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?

    Yes, 5 times.

    D. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)

    Doctoral Degree meeting departmental requirement of at least 50% of doctoral coursework in the areas of Educational Statistics, Measurement and Evaluation.

    Documented training in SEM.

    Documented experience using SEM in educational research.


  4. Other Course Information

    A. Objectives

    The primary purpose of this course is to help students gain an understanding of the logic, concepts, methods, applications, and limitations of structural equation modeling. We will address basic educational applications of structural equation modeling include path models, confirmatory factor analysis, and structural models with latent variables. We will also consider more advanced educational applications, such as latent growth curve models, multi-group models, higher order factor analysis, multitrait-multimethod models, and models with interactions among latent variables. The course emphasis is on the application of these procedures in the context of research in education. Computer applications of the procedures will be integrated into the course.

    B. Learning Outcomes

    The successful completion of the course requirements is expected to result in increased ability to (a) intelligently read and evaluate research literature, (b) recognize the strengths and limitations of statistical analysis in the conduct of disciplined inquiry, (c) design research studies requiring the use of structural equation modeling and (d) communicate with peers and other professionals on research issues. More specifically, students will be able to...

    1. Recognize research scenarios that are amenable to SEM

    2. Translate research questions into path models

    3. Specify a mathematical model based on a path diagram

    a) in matrix form (LISREL notation)

    b) in equation form (EQS, CALIS notation)

    4. Screen data for the purpose of assessing the tenability of assumptions

    5. Make decisions regarding estimation based on the form of the data

    6. Prepare data for the structural equation modeling analysis

    7. Write the computer code necessary to run a structural equation modeling analysis

    8. Recognize and make decisions regarding identification problems

    9. Recognize and make decisions regarding improper solutions

    10. Evaluate the overall fit of the model

    11. Evaluate fit in the components of the model

    12. If appropriate, compare the fit of competing models

    13. If appropriate, modify the model to improve fit

    14. Summarize and communicate the results of the analysis

    Grades will be based on 4 projects. A brief description of the projects and the rubrics used for grading are provided below.

    Project 1 (20%)

    Students will complete path analyses based on data provided by the instructor. The student will specify the model(s), estimate the model(s) using appropriate software, evaluate fit, prepare path diagrams containing the unstandardized and standardized solutions, will estimate specified total, direct, and indirect effects, and will interpret and discuss the findings.

    ____ Correct specification of model(s)

    ____ Accurate program syntax

    ____ Acceptable evaluation of fit

    ____ Accurate path diagram – unstandardized

    ____ Accurate path diagram – standardized

    ____ Accurate estimate of total, direct, and indirect effects

    Project 2 (20%)

    Students will complete confirmatory factor analyses based on data provided by the instructor. The student will specify the model(s), estimate the model(s) using appropriate software, evaluate fit, prepare path diagrams containing the unstandardized and standardized solutions, and interpret and discuss the findings.

    ____ Correct specification of model(s)

    ____ Accurate program syntax

    ____ Acceptable evaluation of fit

    ____ Accurate path diagram – unstandardized

    ____ Accurate path diagram – standardized

    Project 3 (20%)

    Students will complete analyses of a structural equation model with latent variables based on data provided by the instructor. The student will specify the model(s), estimate the model(s) using appropriate software, evaluate fit, prepare path diagrams containing the unstandardized and standardized solutions, and interpret and discuss the findings.

    ____ Correct specification of model(s)

    ____ Accurate program syntax

    ____ Acceptable evaluation of fit

    ____ Accurate path diagram – unstandardized

    ____ Accurate path diagram – standardized

    Project 4 (40%)

    Students will complete analyses of a structural equation model based on data and models of their own choosing. The student will identify and/or gather the data, develop the model(s), specify the model(s), estimate the model(s) using appropriate software, evaluate fit, prepare path diagrams, and write a report on the study in APA format, where the results section should be of a quality suitable for publication.

    ____ Rationale for questions/model included

    ____ Appropriate level of detail regarding sample

    ____ Appropriate level of detail regarding variables

    ____ Analyses clearly described, including any modifications

    ____ Model(s) specified consistently with theory/rationale

    ____ Program syntax is accurate

    ____ Data screening conducted and reported

    ____ Appropriate choice of fit indices

    ____ Accurate interpretation of fit indices

    ____ Parameter estimates included

    ____ Accurate description/discussion of parameter estimates

    ____ Limitations noted

    ____ Conclusions consistent with results

    ____ Publishable writing of results section

    C. Major Topics

    Orientation to Course, Introduction to SEM, Path Models

    Model Specification, Equation notation

    Model Specification, LISREL notation

    Implied Covariance Matrices, Identification, and Equivalent Models

    Model Estimation and Power

    Model Fit and Interpretation Issues Non-Normality and Interpretation Issues

    Latent Growth Models

    D. Textbooks

    Orientation to Course, Introduction to SEM, Path Models

    Hershberger, S. L. (2003). The growth of structural equation modeling: 1994-2001. Structural Equation Modeling, 10, 35-46

    McDonald, R. P. & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses, Psychological Methods, 7, 64-82.

    Boomsma, Anne. (2000). Reporting analyses of covariance structures. Structural Equation Modeling, 7, 461-483.

    Model Specification, Equation notation

    Wolfle, L. M. (2003). The introduction of path analysis to the social sciences, and some emergent t

    E. Course Readings, Online Resources, and Other Purchases

    F. Student Expectations/Requirements and Grading Policy

    G. Assignments, Exams and Tests

    H. Attendance Policy

    I. Policy on Make-up Work

    J. Program This Course Supports


  5. Course Concurrence Information



- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.