• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedFor visually-impairedUser profile (HSE staff only)Search
Advanced search
Menu
HSE University
User profile (HSE staff only)Search
Advanced search

Course Syllabus

Master 2022/2023

Psychometric Theories and Analysis of Test Items

Category 'Best Course for New Knowledge and Skills'
Type: Compulsory course (Science of Learning and Assessment)
Area of studies: Psychology
Delivered by: Institute of Education
Where: Institute of Education
When: 1 year, 3, 4 module
Mode of studies: offline
Open to: students of all HSE University campuses
Instructors: Alina Ivanova, Elena Kardanova
Master’s programme: Science of Learning and Assessment
Language: English
ECTS credits: 6
Contact hours: 60

Course Syllabus

Full Syllabus

Abstract

Prerequisite: basic knowledge in statistics. This course introduces the fundamental concept of modern measurement theory, including Rasch measurement approach and item response theory (IRT) approach. The course starts with a short review of classical test theory, its connection to item response theory and basic assumptions of the latter. Smooth transition to Rasch measurement includes such topics as basic principles and basic assumptions of Rasch measurement. While presented Rasch models for dichotomous and polytomous data the students will learn how Rasch analysis constructs linear measures from scored observations. Theoretical and practical aspects of data analysis, output interpretation and reporting will be introduced. In addition to presenting the Rasch model, the course covers some basic methods for parameter estimation and for assessing fit and dimensionality, as well as differential item functioning (DIF). Introduction to linking and equating problems will be done. Further, the course addresses a variety of other dichotomous and polytomous item response theory (IRT) models, such as 1PL, 2PL, and 3PL models, GRM and GPCM models, and extensions, including topics of multidimensional and multifaced modelling. The course is accessible for students without a sophisticated background in psychometrics or statistics, as well as for those who want to gain a deeper understanding on measurement principles. The use of Winsteps and R software demonstrate how to apply the basic psychometric analysis methods to real-world examples in education and psychology.
Learning Objectives

Learning Objectives

  • The objectives of mastering the discipline "Psychometric Theories and Analysis of Test Items" is to master the basic theoretical principles and practical skills of analyzing test items, building and analyzing tools and scales within the framework of IRT and modern measurement approaches.
Expected Learning Outcomes

Expected Learning Outcomes

  • Possess practical skills in using standard IRT methods and models for building and analyzing specific assessment tools in education, building and analyzing scales and methods in psychology, sociology and other social sciences;
  • Navigate the flow of scientific information to search for the necessary mathematical models and methods of analysis to solve psychometric problems.
  • Be able to choose and apply IRT models that correspond to the goals of the analysis (dichotomous and polytomic, one-dimensional and multidimensional, multifaceted, etc).
  • Analyze test items and tests in the framework of IRT using appropriate software products, interpret and present the results of the analysis
Course Contents

Course Contents

  • Disadvantages and limitations of classical testing theory (CTT)
  • Principles for measuring latent variables within the framework of IRT.
  • Rasch models
  • Dichotomous Rasch Model
  • Polytomous Rasch models
  • Rating Scale Analysis
  • IRT modeling for the development of psychological scales
  • Linking
  • Dichotomous IRT models
  • Polytomous models of IRT
  • Estimating the parameters of IRT models
  • Analysis of measurement properties of items in IRT
  • DIF analysis
  • Test taker analysis
  • Standard Setting
  • Multifaceted models
  • Multidimensional IRT models
Assessment Elements

Assessment Elements

  • non-blocking IWW - individual and group written work
  • non-blocking Group Presentations on Written Assignment (GP WPI)
  • non-blocking Group Article Presentations (GPA)
  • non-blocking Exam. Theory
  • non-blocking Exam. Practice
Interim Assessment

Interim Assessment

  • 2022/2023 4th module
    0.2 * Exam. Theory + 0.2 * Exam. Practice + 0.15 * Group Presentations on Written Assignment (GP WPI) + 0.15 * Group Article Presentations (GPA) + 0.3 * IWW - individual and group written work
Bibliography

Bibliography

Recommended Core Bibliography

  • Applications of item response theory to practical testing problems, Lord, F. M., 2008
  • Applying the rasch model : fundamental measurement in the human sciences, Bond, T. G., 2007
  • Fundamentals of item response theory, Hambleton, R. K., 1991
  • Introduction to classical and modern test theory, Crocker, L., 2008
  • Item response theory for psychologists, Embretson, S. E., 2009
  • James, A., Algina, J., & Swaminathan, H. (2015). Psychometrics: Classical Test Theory. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.7E3F0482
  • Rasch models for measurement, Andrich, D., 1988

Recommended Additional Bibliography

  • Ronald K. Hambleton, & Russell W. Jones. (n.d.). ========================= = ITEMS. Instructional Topics in Educational Measurement ========================= An NCME Instructional Module on Comparison of Classical Test Theory and Item Response Theory and Their Applications to Test Development. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.46F2C9F0