Abstract
Mathematical Literacy (ML) is a relatively new school subject that learners study in the final 3 years of high school and is examined as a matric subject. An investigation of a 2009 provincial examination written by matric pupils was conducted on both the curriculum elements of the test and learner performance. In this study we supplement the prior qualitative investigation with an application of Rasch measurement theory to review and revise the scoring procedures so as to better reflect scoring intentions. In an application of the Rasch model, checks are made on the test as a whole, the items and the learner responses, to ensure coherence of the instrument for the particular reference group, in this case Mathematical Literacy learners in one high school. In this article, we focus on the scoring of polytomous items, that is, items that are scored 0, 1, 2 … m. We found in some instances indiscriminate mark allocations, which contravened assessment and measurement principles. Through the investigation of each item, the associated scoring logic and the output of the Rasch analysis, rescoring was explored. We report here on the analysis of the test prior to rescoring, the analysis and rescoring of individual items and the post rescore analysis. The purpose of the article is to address the question: How may detailed attention to the scoring of the items in a Mathematical Literacy test, through theoretical investigation and the application of the Rasch model, contribute to a more informative and coherent outcome?
Highlights
Background to the studyThe subject Mathematical Literacy (ML), introduced in 2006 in South Africa, is a compulsory subject for those Grade 10–12 learners who do not study Mathematics
The purpose in ML is not that learners learn more and higher mathematics: the emphasis in ML is on the use of mathematics to explore the meaning and implications of quantitative information presented in many real-life situations
The output provides statistics on the test as a whole as well as the individual item statistics, in particular the fit residual statistic and the chi square probability statistic, which provide information on the fit of the items. In addition to these statistics we investigated the item characteristic curves (ICCs) to identify which items were misfitting in the ways to be discussed
Summary
Background to the studyThe subject Mathematical Literacy (ML), introduced in 2006 in South Africa, is a compulsory subject for those Grade 10–12 learners who do not study Mathematics. The purpose in ML is not that learners learn more and higher mathematics: the emphasis in ML is on the use of mathematics to explore the meaning and implications of quantitative information presented in many real-life situations. Mathematical literacy is a subject driven by life-related applications of mathematics. ML differs from Mathematics in purpose and in content. In Mathematics, emphasis is placed on engaging with increasingly more complex and abstract mathematical concepts, the relations between them and some applications to problems. In ML the emphasis is on the application of basic mathematics to understand situations in real life. The debate about the subject content of Mathematics and Mathematical Literacy, though regarded as critical, is not the focus of this article
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
