Modeling the phenomenon versus modeling the data set

Journal article

Stillman, Gloria Ann and Brown, Jill. (2021). Modeling the phenomenon versus modeling the data set. Mathematical Thinking and Learning. 25(3), pp. 270-295. https://doi.org/10.1080/10986065.2021.2013144
AuthorsStillman, Gloria Ann and Brown, Jill
Abstract

This paper investigates students’ mathematical modeling activity in data-rich modeling tasks. It aims at gaining insight into how students develop meaning when modeling data-rich situations and the mathematical models produced. A tendency to model a particular dataset, rather than the phenomenon that the dataset is a particular instance of, has been observed previously. Students concentrate on fitting mathematical objects such as functions to data, rather than using domain knowledge about the situation being modeled, mapping this to the data so as to capture the phenomenon as a whole. In other instances, students find functions that simply linearly interpolate the data and do not consider key features of the phenomenon, particularly when they have access to technological tools. The extent to which students’ reasoning indicated awareness of their taking either approach was investigated in a qualitative study with Year 10/11 students. How the approach taken affected the processes students engage in whilst modeling was also investigated. The paper contributes to our currently limited literature on research into this issue and how it affects the outcome of students learning to model in classrooms at this level of schooling.

Keywordsdata-rich situations; modeling the dataset; modeling the phenomenon; technology use; modeling purpose of use; modeling processes
Year2021
JournalMathematical Thinking and Learning
Journal citation25 (3), pp. 270-295
PublisherRoutledge
ISSN1532-7833
Digital Object Identifier (DOI)https://doi.org/10.1080/10986065.2021.2013144
Scopus EID2-s2.0-85122028105
Web address (URL)https://www.tandfonline.com/doi/full/10.1080/10986065.2021.2013144
Open accessOpen access
Research or scholarlyResearch
Page range270-295
FunderAustralian Research Council (ARC)
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Output statusPublished
Publication dates
Online28 Dec 2021
Publication process dates
Accepted29 Nov 2021
Deposited28 Jun 2023
Grant IDDP17010555
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