UMass Lowell Dept. of Computer Science  Graduate School of Education

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UMass Lowell Dept. of Computer Science  Graduate School of Education Machine Science Inc. Tsongas Industrial History Center U.S. National Park Service

What is iSENSE? iSENSE is a set of free tools for collecting, sharing, and visualizing scientific data. We are developing mobile apps, data-logging hardware, and a data-sharing web site. iSENSE is intended for use in middle school and high school classrooms. The technology can be used to teach math, engineering, physics, chemistry, earth science, and other subjects.

Agenda Key Concepts Introductory Survey Data-Collection Activities Car Ramp Physics – accelerometer data – project 570 Data Walk – GPS data – project 569 Use contribution key “MIT” Discussion How to integrate iSENSE into teaching

Key Concepts PROJECT Data Set Project Repository for data Field Type and source of anticipated data Data Set Table of values Visualization Graphical view of one or more data sets Field 1 Field 2 Field 3 Value a Value d Value g Value b Value e Value h Value c Value f Value i Data Set 1 Value j Value l Value n Value k Value m Value o Data Set 2 Visualization 1 Visualization 2 Visualization 3

Introductory Survey Goals Create an iSENSE account Log in to the web site Get familiar with the web site Contribute data using the Manual Entry method Explore the visualization tools Link http://isenseproject.org/projects/568

Accelerometer App Goals Collect acceleration data using a mobile app Contribute the data to iSENSE Use iSENSE to examine multiple data sets Explore the different visualizations Save one or more visualizations Link http://isenseproject.org/projects/570

GPS Tracking App Goals Collect acceleration data using a mobile app Contribute the data to iSENSE Use iSENSE to examine multiple data sets Explore the different visualizations Save one or more visualizations Link http://isenseproject.org/projects/569

Why Use iSENSE? Sharing projects and data online takes good classroom activities, which are often private, static, and ephemeral, and makes them public, evolving, and lasting. We are in the age of “big data,” and science is becoming a data-driven enterprise. It’s important for students to begin developing data science skills. Many of the eight cross-cutting Next Generation Science Standards science and engineering “practices” can be integrated into iSENSE activities. NGSS Practices 1. Asking questions (for science) and defining problems (for engineering) 2. Developing and using models 3. Planning and carrying out investigations4. Analyzing and interpreting data 5. Using mathematics and computational thinking 6. Constructing explanations (for science) and designing solutions (for engineering) 7. Engaging in argument from evidence 8. Obtaining, evaluating, and communicating information

Going Forward Questions or comments? Ideas for using iSENSE as a teaching tool? Suggestions for additional features? We have resources and funding available to work with you to integrate iSENSE with your teaching. This material is based upon work supported by the National Science Foundation under grants DRL-0735597, DRL-0735592, REC-0546513, IIS-1123972, and IIS-1123998. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.