Abstract
The two-tier item is a relatively new item format and is gradually gaining popularity in some areas of educational research. In science education, a typical two-tier item is made up of two portions. The purpose of the first portion is to assess whether students could identify the correct concept with respect to the information stated in the item stem, while the second examines the reason they supplied to justify the option they chose in the first portion. Since the data thus collected are related in a certain way, they pose challenges regarding how analysis should be done to capture the relationship that exists between the two tiers. This chapter attempts to analyze such data by using a user-defined fit statistic within the Rasch approach. The kind of information that can be gathered will be illustrated by way of analyzing a data set in mathematics.
Keywords
- Word Problem
- Subject Matter Expert
- Partial Credit
- Data Analyst
- Item Pair
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Buying options
References
Adams, R. J., & Wu, M. L. (2011). The construction and implementation of user-defined fit tests for use with marginal maximum likelihood estimation and generalized item response models. In N. J. S. Brown, B. Duckor, K. Draney, & M. Wilson (Eds.), Advances in Rasch measurement (Vol. 2). Maple Grove: JAM Press.
Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah: Lawrence Erlbaum Associates.
Tam, H. P., & Li, L. A. (2007). Sampling and data collection procedures for the National Science Concept Learning Study. International Journal of Science Education, 29(4), 405–420.
Tam, H. P., & Wu, M. (2009). Analyzing two-tier items with user-defined fit statistics. Paper presented at the annual meeting of the American Educational Research Association, San Diego, USA.
Tan, K. D., & Treagust, D. (1999). Evaluating students’ understanding of chemical bonding. School Science Review, 81(294), 75–83.
Treagust, D. (1988). Development and use of diagnostic test to evaluate students’ misconceptions in science. International Journal of Science Education, 10(2), 159–169.
Treagust, D. F., & Smith, C. L. (1989). Secondary students’ understanding of gravity and the motion of planets. School Science and Mathematics, 89(5), 380–391.
Wainer, H., Bradlow, E. T., & Wang, X. (2007). Testlet response theory and its applications. New York: Cambridge University Press.
Wu, M. L., Adams, R. J., & Wilson, M. R. (1998). ConQuest – Generalised item response modeling software. Melbourne: Australian Council for Educational Research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Tam, H.P., Wu, M., Lau, D.C.H., Mok, M.M.C. (2012). Using User-Defined Fit Statistic to Analyze Two-Tier Items in Mathematics. In: Mok, M. (eds) Self-directed Learning Oriented Assessments in the Asia-Pacific. Education in the Asia-Pacific Region: Issues, Concerns and Prospects, vol 18. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4507-0_12
Download citation
DOI: https://doi.org/10.1007/978-94-007-4507-0_12
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4506-3
Online ISBN: 978-94-007-4507-0
eBook Packages: Humanities, Social Sciences and LawEducation (R0)