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LIVE STREAM – 4-day Statistics Short Course

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Seminar Overview: Item Response Theory Course

This interactive training course will introduce the concepts of unidimensional and multidimensional IRT models and provide instruction, demonstration, and hands-on opportunities of using the free R software to estimate commonly used IRT models.

Seminar Topics:

  • The Rasch, 1PL, 2PL, and 3PL IRT models will be discussed for unidimensional dichotomous data.
  • The GR and GPC models will be presented for polytomous data.
  • The 2PL model will be explained for multidimensional dichotomous data.
  • The analysis of these models and types of data will be implemented using the eRm, ltm, and mirt packages in R.

Seminar Description:

This item response theory course is perfect for anyone seeking to enhance their researcher skills of using R to do IRT analysis and advance their knowledge of IRT. These may be students, faculty, and researchers from a variety of fields that utilize IRT (e.g., education, psychometrics, psychology, and testing). The audience is expected to have a basic to intermediate knowledge level of general statistics. No prior knowledge of experience of using R to do IRT is necessary. The instructions and training on IRT and the use of R will be taught at an introductory to intermediate level.

Instructor: Ki Cole, Ph.D.

item response theory course

Ki Cole, Ph.D. is an Associate Professor for Research, Evaluation, Measurement and Statistics (REMS) in the College of Education and Human Sciences (CEHS). She is an Oklahoma native and attended the land-grant University of Arkansas (BS, MS, and PhD). She joined the REMS faculty at OSU in August 2014 and has served as the Course Coordinator for the REMS service courses since 2019. Dr. Cole is an active participant in all areas of teaching, research, and service. Her primary areas of study are in the design, evaluation, and use of tests and surveys. She is the recipient of the 2020 Marguerite Scrubbs Award for Meritorious Early Career Research and 2018 Distinguished Faculty Research Award in CEHS. She teaches graduate courses (e.g., Statistical Methods, ANOVA, Factor Analysis, and Item Response Theory) and serves on graduate student committees across colleges at OSU. She has co-authored one textbook and publishes in Educational and Psychological Measurement, International Journal of Testing, and Journal of Quantitative Research in Education. She serves as External Evaluator for various grants and has served as a reviewer of grant proposals for the National Science Foundation (NSF). Ki has served as the CEHS representative to Faculty Council since 2019.

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APA Continuing Education Credits:

item response theory training course

This course offers ? hours of Continuing Education Credits. Yhat Enterprises, LLC is approved by the American Psychological Association to sponsor continuing education for psychologists. Yhat Enterprises, LLC maintains responsibility for this program and its content.

Seminar Includes:

Materials, downloads, recorded course video viewable for up to one year.

Learning Objectives:

The first objective of this item response theory course is to introduce participants to commonly used IRT models. Evidence of meeting this objective will be the following:

  • Participants will be able to distinguish between the Rasch, one-parameter (1PL), two-parameter (2PL), three-parameter (3PL), graded response (GR) and generalized partial credit (GPC) models.
  • Participants will be able to determine which unidimensional model to use when data are of a particular structure: dichotomous or polytomous.
  • Participants will be able to apply a multidimensional model to simple and complex data.
  • Participants will have an understanding of item parameters (e.g. difficulty, discrimination, threshold, etc.), and how they relate to the item (or category) characteristic curves for each IRT model.
  • Participants will have a general understanding of item calibration and latent ability estimation processes.
  • Participants will know the desired conditions for proper calibrations of each IRT model.

The second objective of this item response theory course is to provide detailed instructions on how to use the IRT-related packages (i.e., eRm, ltm, and mirt) in R for IRT analysis. Evidence of meeting this objective will be the following:

  • Participants will be able to determine which package to use based on the model choice and the data structure.
  • Participants will be able to upload a dataset into R.
  • Participants will be able to call a needed function and supply the appropriate parameters to analyze a dataset and produce test and item characteristic and information plots.
  • Participants will be able to interpret the output of a called function, including the item parameters and ability estimates, and its added components.

Seminar Prerequisites:

Prior knowledge of R software is not required. A basic understanding of unidimensional IRT models is highly recommended. Familiarity with writing syntax may also be helpful for using R but is not essential. The course will be taught under the assumptions that participants have an elementary-level of knowledge about IRT and have little to no experience using R.

If this course is not a good fit for you please view our complete statistics training course list.

Software and Computer Support:

Participants need a laptop computer with Wi-Fi and webcam capabilities.

The R software will be used for all analyses, and is freely available for download.

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

Day 1

C.S.T.

Time

Topic

9:00-9:30

11:00 – 11:30

30 min

Welcome and introduction

Check R Installations on Computers

9:30-10:45

1hr 15 min

Unidimensional Rasch and 1PL models

10:45-11:00

12:45 – 1:00

15 min

Snack and Refreshment Break

11:00-12:30

1hr 30 min

Applications of Rasch and 1PL models in R

12:30-1:30

2:30 – 3:30

1 hr

Lunch Break

1:30-3:00

1hr 30 min

Unidimensional 2PL and 3PL models

3:00-3:15

5:00 – 5:15

15 min

Snack and Refreshment Break

3:15-4:45

1hr 30 min

Applications of 2PL and 3PL models in R

4:45-5:00

15 min

De-brief

Day 2

9:00-9:15

11:00 – 11:15

15 min

Review

9:15-10:45

1hr 30 min

Unidimensional GR model

10:45-11:00

12:45 – 1:00

15 min

Snack and Refreshment Break

11:00-12:30

1hr 30 min

Applications of GR model in R

12:30-1:30

2:30 – 3:30

1 hr

Lunch Break

1:30-3:00

1hr 30 min

Unidimensional GPC model and Application in R

3:00-3:15

5:00 – 5:15

15 min

Snack and Refreshment Break

3:15-4:45

1hr 30 min

Open Discussion and Consulting

4:45-5:00

15 min

De-brief

Day 3

9:00-9:15

11:00 – 11:30

15 min

Review

9:15-10:45

1hr 30 min

Multidimensional 2PL model for Simple Structure Data

10:45-11:00

12:45 – 1:00

15 min

Snack and Refreshment Break

11:00-12:30

1hr 30 min

Application of MIRT 2PL for Simple Structure Data

12:30-1:30

2:30 – 3:30

1 hr

Lunch Break

1:30-3:00

1hr 30 min

MIRT for Complex Structure and Bifactor Models

3:00-3:15

5:00 – 5:15

15 min

Snack and Refreshment Break

3:15-4:45

1hr 30 min

Open Discussion and Consulting

4:45-5:00

15 min

De-brief

Day 4

9:00-9:15

11:00 – 11:30

15 min

Review

9:15-10:45

1hr 30 min

Open Discussion and Consulting

10:45-11:00

12:45 – 1:00

15 min

Review

11:00-12:30

1hr 30 min

Open Discussion and Consulting

12:30-1:30

2:30 – 3:30

1 hr

De-brief

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