### Abstract

In this information age, the capacity to perceive structure in data, model that structure, and make decisions regarding its implications is rapidly becoming the most important of the quantitative literacy skills. We build on Kaput's belief in a Science of Need to motivate and direct the development of tasks and tools for engaging students in reasoning about data. A Science of Need embodies the utility value of mathematics, and engages students in seeing the importance of mathematics in both their current and their future lives. An extended example of the design of tasks that require students to generate, test, and revise models of complex data is used to illustrate the ways in which attention to the contributions of students can aid in the development of both useful and theoretically coherent models of mathematical understanding by researchers. Tools such as Fathom are shown as democratizing agents in making data modeling more expressive and intimate, aiding in the development of deeper and more applicable mathematical understanding.

Original language | English (US) |
---|---|

Pages (from-to) | 113-130 |

Number of pages | 18 |

Journal | Educational Studies in Mathematics |

Volume | 68 |

Issue number | 2 |

DOIs | |

State | Published - Jun 2008 |

### Fingerprint

### Keywords

- Data modeling
- Mathematical applications
- Model eliciting activities
- Modeling
- Models
- Technology
- Visualization

### ASJC Scopus subject areas

- Mathematics(all)
- Social Sciences(all)

### Cite this

*Educational Studies in Mathematics*,

*68*(2), 113-130. https://doi.org/10.1007/s10649-008-9118-4

**A science need : Designing tasks to engage students in modeling complex data.** / Lesh, Richard; Middleton, James; Caylor, Elizabeth; Gupta, Shweta.

Research output: Contribution to journal › Article

*Educational Studies in Mathematics*, vol. 68, no. 2, pp. 113-130. https://doi.org/10.1007/s10649-008-9118-4

}

TY - JOUR

T1 - A science need

T2 - Designing tasks to engage students in modeling complex data

AU - Lesh, Richard

AU - Middleton, James

AU - Caylor, Elizabeth

AU - Gupta, Shweta

PY - 2008/6

Y1 - 2008/6

N2 - In this information age, the capacity to perceive structure in data, model that structure, and make decisions regarding its implications is rapidly becoming the most important of the quantitative literacy skills. We build on Kaput's belief in a Science of Need to motivate and direct the development of tasks and tools for engaging students in reasoning about data. A Science of Need embodies the utility value of mathematics, and engages students in seeing the importance of mathematics in both their current and their future lives. An extended example of the design of tasks that require students to generate, test, and revise models of complex data is used to illustrate the ways in which attention to the contributions of students can aid in the development of both useful and theoretically coherent models of mathematical understanding by researchers. Tools such as Fathom are shown as democratizing agents in making data modeling more expressive and intimate, aiding in the development of deeper and more applicable mathematical understanding.

AB - In this information age, the capacity to perceive structure in data, model that structure, and make decisions regarding its implications is rapidly becoming the most important of the quantitative literacy skills. We build on Kaput's belief in a Science of Need to motivate and direct the development of tasks and tools for engaging students in reasoning about data. A Science of Need embodies the utility value of mathematics, and engages students in seeing the importance of mathematics in both their current and their future lives. An extended example of the design of tasks that require students to generate, test, and revise models of complex data is used to illustrate the ways in which attention to the contributions of students can aid in the development of both useful and theoretically coherent models of mathematical understanding by researchers. Tools such as Fathom are shown as democratizing agents in making data modeling more expressive and intimate, aiding in the development of deeper and more applicable mathematical understanding.

KW - Data modeling

KW - Mathematical applications

KW - Model eliciting activities

KW - Modeling

KW - Models

KW - Technology

KW - Visualization

UR - http://www.scopus.com/inward/record.url?scp=43849103201&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=43849103201&partnerID=8YFLogxK

U2 - 10.1007/s10649-008-9118-4

DO - 10.1007/s10649-008-9118-4

M3 - Article

VL - 68

SP - 113

EP - 130

JO - Educational Studies in Mathematics

JF - Educational Studies in Mathematics

SN - 0013-1954

IS - 2

ER -