Using Rasch Theory to Guide the Practice of Survey Development and Survey Data Analysis in Science Education and to Inform Science Reform Efforts: An Exemplar Utilizing STEBI Self-Sufficiency Data

March 1st, 2011 | RESEARCH

Over many decades, science education researchers have developed, validated, and used a wide range of attitudinal instruments. Data from such instruments have been analyzed, results have been published, and public policies have been influenced. Unfortunately, most science education instruments are not developed using a guiding theoretical measurement framework. Moreover, ordinal-level attitudinal data are routinely analyzed as if these data are equal interval, thereby violating requirements of parametric tests. This paper outlines how researchers can use Rasch analysis to develop higher quality science education instruments and why researchers must use Rasch analysis to prepare appropriate ordinal-level data for parametric analyses. Detailed recommendations are set forth to help science education researchers increase the rigor of attitudinal instrument development and analysis. Suggestions are also set forth regarding how philosophical and analytical Rasch techniques align with broad goals of the science education research community.


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Team Members

William Boone, Author, Miami University
J. Scott Townsend, Author, Eastern Kentucky University
John Staver, Author, Purdue University


Identifier Type: doi
Identifier: 10.1002/sce.20413
Identifier Type: issn
Identifier: 0036-8326

Publication: Science Education
Volume: 95
Number: 2
Page(s): 258

Related URLs

EBSCO Full Text


Audience: Educators | Teachers | Scientists
Discipline: Education and learning science | General STEM
Resource Type: Peer-reviewed article | Research Products
Environment Type: Exhibitions | Informal | Formal Connections | Media and Technology | Professional Development | Conferences | Networks | Public Programs