A+Sample+Grow+Beast+Project+-+High+School

Grow Beasts in Wikispace!
1. Students develop their understanding of the concept of a mathematical model. (concept) 2. Students are able to use mathematics (i.e. slope and x-y scatter plots) to make predictions about physical phenomena. (skill)
 * Abstract** -- Students use spreadsheets and a wikispace to facilitate the construction of their understanding of how mathematical measurement and modeling can be used to make predictions of a physical phenomenon, the growth of a Grow Beast.
 * Learning Targets**
 * Context** -- middle school math or math and science class


 * The Learning Episode [[image:KimballRex_After_4_Days.jpg width="146" height="122" align="right"]]**

"**Grow Beasts**" are small toys made from a super-absorbent polyacrylamide polymer. When placed in a liquid they absorb it and gradually expand over the course of several days. When they are removed from the liquid evaporation begins. The Grow Beast shrinks. This can also take several days but the Grow Beast will eventually return to more or less its original shape and size and can be grown again. A **wikispace** is a Web page or collection of Web pages that can be edited by anyone who accesses it (and who has been given permission to do so). Thus a wikispace can serve as a collaborative tool allowing people to share information asynchronously and from disparate locations.
 * Terms:**
 * Spreadsheets** facilitate the manipulation and representation of numerical data. Data can be entered into arrays of cells in a spreadsheet and operations can be performed on rows, columns, and on individual cells.

Each team will be given five Grow Beasts with which to experiment. The goal will be to develop models of growth that enable teams to predict how big a Grow Beast will be at any given time as it grows over the course of 96 hours (four days). To make things more interesting, consider this: Grow Beasts grow differently depending on the medium in which they grow. That is, a Grow Beast grown in ketchup will not grow at the same rate as one grown in lemonade. Teams will need to develop models that enable them to predict the effects of //acidity// (acid/base) and //salinity// (saltiness) on Grow Beast growth. Lemon juice can be used to increase the acidity of test liquids and iodized table salt to increase the salinity of test liquids. As the project's culminating activity a Grow Beast will be grown for 96 hours in conditions that will be announced as part of the contest. That is the teacher will specify whether salt or lemon juice (not both), and how much, will be added to 500 ml of distilled water. The teacher will also specify the initial length of the Grow Beast as this can vary from beast to beast. Students use only their models derived from their experiences with the Grow Beasts and from the shared data to make predictions. May the best model win!
 * The Project** -- Students will work in teams of three with the Grow Beasts using experimentation, measurement, and mathematics to develop their understanding of how Grow Beasts grow in various conditions. They will use the spreadsheets to record, analyze and represent data. They will use the wikispace to share data. While an individual team may only be able to perform a few experiments, the whole group, sharing data, hypotheses, and analyses through the wikispace will be able to assemble a larger pool of knowledge. Ideally more than one class in more than one school will participate simultaneously in the project, using the wikispace to share data.
 * Connections to Our Learning Model** -- Students will have direct kinesthetic experiences with the Grow Beasts. They will be able to design these experiences and implement their own decisions. This should increase their commitment to the process. It may also increase the quality of their reflections on the experiences. The wikispace will facilitate communication between remote groups and this communication will be purposeful, aimed at the development of a mathematical model that enables accurate predictions of growth. Teams will use the data they develop and the data developed by other teams to revise and refine their understanding of the growth models they develop.

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