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Cathie Marsh Institute for Social Research (CMI)

Measuring and Scale construction (with the Rasch Model)

NEW Dates: 29-30 May 2019
Time: 9.30-4pm
Instructor: Dr Maria Pampaka and Prof Julian Williams
Level: Intermediate
Fee: £390 (£280 for those from educational, government and charitable institutions)

CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application.

Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor.

Please contact methods@manchester.ac.uk for a bursary application form. For any general course enquires, please contact cmi-shortcourses@manchester.ac.uk.

Please note: this is not guaranteed and is considered on a case-by-case basis. Please contact us for more information.

Outline

This two-day course aims to introduce participants to measurement theory and the Rasch model for the construction and validation of measures. It covers the basic theory behind measurement, from an Item Response Theory perspective, focusing on the assumptions of the Rasch models, in particular. The Rasch model provides the means to create measures (or score scales) from a combination of items in tests or questionnaires. The principles governing the application of such models are shown through examples from educational measurement but are easily applicable to other areas in social and health sciences. Participants will have the chance to practice with various models of the Rasch family (Dichotomous, Rating Scale and Partial Credit) with specialised software (Winsteps).

Objectives

This two-day course aims to introduce participants to measurement theory and the Rasch model for measures construction and validation (Day 1). Participants will get hands-on experience with analysis and interpretation of the Dichotomous (Day 1), Partial Credit and Rating Scale (Day 2) Rasch models, with specialised software as well as packages freely available in R.

The course will be delivered with a mixture of lectures and practical sessions, around the following themes:

  • Introduction to (Rasch) Measurement 
  • The Dichotomous Rasch Model (with software application)
  • The basics of the validation framework with the Rasch Model 
  • Examples and applications with the Rating Scale Model (which is appropriate for Likert type items) and the Partial Credit Model (which allows for items with a different number of response categories to be analysed together).
  • Differential Item Functioning, optimal functioning of rating scales and dimensionality.

Prerequisites

Participants should have some basic knowledge of introductory statistics. Some familiarity or previous experience with syntax (commands) in statistical packages will also be useful. Examples of data sets from various contexts will be provided; however, participants might also bring their own datasets and problems to analyse, possibly with a view to preparing a validation report or paper for publication. In order to ensure that the datasets are appropriate for such analyses, participants are advised to contact Maria Pampaka (maria.pampaka@manchester.ac.uk) in advance of the course.

Recommended reading

Bond, T.G., and C.M. Fox. 2015. Applying the Rasch model: Fundamental measurement in the human sciences (3rd edition). Routledge.

Pampaka, M., Williams, J.S., Hutchenson, G., Black, L., Davis, P., Hernandez-Martines, P., and Wake, G. 2013. Measuring Alternative Learning Outcomes: Dispositions to Study in Higher Education. Journal of Applied Measurement 14 (2):197-218.

About the instructor

Maria Pampaka is currently holding a joint position, as a Lecturer at the Institute of Education and the Social Statistics group, at the University of Manchester, UK. She is substantially interested in the association between teaching practices and students’ learning outcomes, focused on STEM-related subjects. Methodologically, her expertise and interests lie within evaluation and measurement, and advanced quantitative methods, including complex survey design, longitudinal data analysis, and missing data and imputation techniques.

Julian Williams is Professor of Mathematics Education at The University of Manchester, where he led a series of ESRC-funded Transmaths research projects that investigated mathematics education in the post-compulsory transitions from school to university. He has a long-standing interest in curriculum, pedagogy and assessment in mathematics and across STEM, in mathematical modelling, and in links with vocational and outside-school mathematics. This work has led to interests in social theory and the political economy of education.

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