Coding additive word problem-solving to see shifts around an intervention
Tshesane, HermanORCID: 0000-0002-4492-7241 and Venkat, HamsaORCID: 0000-0002-6453-1623
(2023)
Coding additive word problem-solving to see shifts around an intervention.
African Journal of Research in Mathematics, Science and Technology Education, 27
(3).
pp. 324-334.
ISSN 1028-8457
Evidence in South Africa of poor performance on word problems points to particular challenges among learners relating to difficulties with, on the one hand, making sense of mathematical word problems and, on the other, moving beyond inefficient counting based calculation methods. While many studies in mathematics education in South Africa have tended to focus on one or the other issue, in this paper our focus is on a coding model that brings both interpretation of word problems and calculation into view simultaneously. This coding model was devised to capture and summarise learner work on solving additive relations word problems across pre-, post- and delayed post-tests around an intervention focused on improving additive word problem-solving. The coding model allowed for initial quantitative summarising of learner responses in ways that facilitated the tracking of shifts in learners’ interpretations of the problem, their calculations and answers, while also pointing to salient avenues for more in-depth qualitative analysis. We argue through the analysis that the coding scheme afforded a holistic view of the profiles of learners’ engagement across the three tests, thus opening a path away from the tendency towards the single-focus of analyses of word problems seen in many prior studies.
National Institute for the Humanities and Social Sciences, in collaboration with the South African Humanities Deans Association, Wits Maths Connect Primary Project
ID Code:
29737
Deposited On:
22 Mar 2024 10:58 by
Melissa Lynch
. Last Modified 22 Mar 2024 11:28
Documents
Full text available as:
Preview
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0 595kB