An exploration of how teachers perceive and respond to language demands associated with the learning of mathematical literacy

Abstract

With the introduction of Mathematical Literacy (ML) in schools in 2006, a renewed emphasis has been placed on the teaching of Mathematical knowledge and concepts with the use of real-life context-based education. The intention of ML is to provide learners with the opportunity to learn mathematics that is embedded in real-life context-based settings. Learners are expected to gain competencies such as to reason, make decisions, solve problems, manage resources and interpret information within a mathematical contextual setting. These competencies indicate that language skills have become an integral part of ML. It was found that teachers believe that an understanding of the language of learning and teaching plays a pivotal role in learners’ optimal performance in ML. The teachers implemented several strategies aimed at supporting learners with language demands associated with learning ML. The strategies included identifying key words in ML questions, reading the ML questions aloud, selecting resources carefully, providing support in interpreting the contextual setting before attempting to find the mathematical demand of the question, and using code switching in the classroom. Teachers also suggested ways in which they could be supported in the ML classroom. The purpose of this study was to understand how teachers perceive and respond to the language demands associated with the learning of ML. To investigate how teachers perceive this phenomenon, a qualitative approach was adopted, and the analysis of data was conducted in three stages. First, questionnaires were distributed to 42 ML teachers to elicit their views about the role played by language in teaching and learning. Thirty-three teachers completed the questionnaires. The responses were analysed, and this analysis guided the second stage of the research which was the implementation of more meaningful classroom observations. Of these observed participants, all six agreed to participate further in the study by formulating thought provoking questions to gainmore insights into how teachers perceive and respond to the language demands associated with the learning of ML. The results of the study are limited in relation to generalisability because the sample was small. The findings indicate that teachers do consider the language proficiency of learners when they are teaching ML. The study found that a review of the existing channels of communication between stakeholders of the Department of Basic Education (DBE), and the ML teachers needs to be conducted, along with a review of the quality of the ML examination papers released by the DBE. Also, a research review needs to be conducted on how the DBE views the language demands associated with the learning of ML as reflected in the DBE policy documents on ML and, last, a review on the effect the DBE resources have on teaching and learning in ML classrooms needs to be conducted.