Midlands State University Library
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Learners' approaches to solving mathematical tasks: does specialisation matter? / created by France Machaba

By: Contributor(s): Material type: TextTextSeries: Africa Education Review ; Volume 13 , number 3 and 4 ,Pretoria UNISA and Routlege 2016Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 18146627
Subject(s): LOC classification:
  • L81.A33 AFR
Online resources: Summary: This article emerged from an analysis of learners’ responses to a task presented to learners studying Mathematics and Mathematical Literacy (ML) in Gauteng, South Africa. Officially, Mathematics and ML are two separate learning areas. Learners from Grade 10 onwards are supposed to take either one or the other, but not both. This means that by Grade 11, learners would have acquired different kinds of knowledge and problem solving skills depending on which of these they take. The article demonstrates that this possibility may not necessarily happen. Grade 11 learners from both learning areas appeared to have acquired sufficient knowledge and skills and were able to solve similar Mathematics tasks in similar ways, with similar adequacy. We argue that, contrary to common perceptions in the field of Mathematics education (particularly in South Africa), engaging in ML does not and should not make one less mathematically advanced than engagement in pure Mathematics
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This article emerged from an analysis of learners’ responses to a task presented to learners studying Mathematics and Mathematical Literacy (ML) in Gauteng, South Africa. Officially, Mathematics and ML are two separate learning areas. Learners from Grade 10 onwards are supposed to take either one or the other, but not both. This means that by Grade 11, learners would have acquired different kinds of knowledge and problem solving skills depending on which of these they take. The article demonstrates that this possibility may not necessarily happen. Grade 11 learners from both learning areas appeared to have acquired sufficient knowledge and skills and were able to solve similar Mathematics tasks in similar ways, with similar adequacy. We argue that, contrary to common perceptions in the field of Mathematics education (particularly in South Africa), engaging in ML does not and should not make one less mathematically advanced than engagement in pure Mathematics

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