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UCLA MobilizingCS

UCLA MobilizingCS is a data collection tool

UCLA MobilizingCS is a data collection tool

UCLA MobilizingCS

by University of California, Los Angeles
UCLA MobilizingCS
UCLA MobilizingCS
UCLA MobilizingCS

What is it about?

UCLA MobilizingCS is a data collection tool. It provides mobile-based data capture through inquiry-based surveys and temporally triggered reminders. All captured data are automatically timestamped, geocoded and uploaded to a centralized Mobilize server for analysis and visualization. MobilizingCS is fully functional without network connectivity and can run on multiple mobile phone platforms.

UCLA MobilizingCS

App Details

Version
3.12.9
Rating
(3)
Size
10Mb
Genre
Education
Last updated
May 30, 2018
Release date
February 16, 2013
More info

App Screenshots

UCLA MobilizingCS screenshot-0
UCLA MobilizingCS screenshot-1
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App Store Description

UCLA MobilizingCS is a data collection tool. It provides mobile-based data capture through inquiry-based surveys and temporally triggered reminders. All captured data are automatically timestamped, geocoded and uploaded to a centralized Mobilize server for analysis and visualization. MobilizingCS is fully functional without network connectivity and can run on multiple mobile phone platforms.

Through MobilizingCS students use mobile phones and web services to systematically collect and interpret data about issues important to them and their communities. The goal of Mobilize is to strengthen STEM instruction throughout our educational system and to develop innovative methods for educating and engaging students in computational thinking and data analysis.

The core lessons in the MobilizingCS units will be framed around principles of Computational Thinking. Specifically, through Participatory Sensing campaigns, students will identify phenomena to study, consider "designs" for how data are to be collected, and rally the computational resources to execute their plans. Along the way they will grapple with questions related to the nature of data (its representation, formats and protocols for sharing) and of algorithms (rules governing data collection, strategies for analysis). Students will learn about classical themes in Computer Science, from databases to networking, as well as lessons in Statistics, from visualization to basic inference.

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