IDS Technology Suite

Slide 1

A model IDS classroom makes effective uses of a variety of helpful pieces of technology. The fastest way to get comfortable and learn about it is to try it out, so let’s get started!

Slide 2

Introduction to Data Science

Participatory Sensing

An approach to data collection and interpretation in which individuals, acting alone or in groups, use their personal mobile devices and web services to systematically explore interesting aspects of their worlds, ranging from health to culture.

Slide 3

Introduction to Data Science

Interactive Dashboard

After completing a survey, you can review the data collected by the class with Interactive Dashboard.

Slide 4

Introduction to Data Science

R Programming

Advanced Data Analysis with R in RStudio. Come up with a statistical question, and explore the data science!

Slide 5

Introduction to Data Science

Class Tools, and More!

Create new campaigns, Monitor student activities, Review survey responses.
Want to know more? General Inquiry at info@idsucla.org

A model IDS classroom makes effective uses of a variety of helpful pieces of technology. The fastest way to get comfortable and learn about it is to try it out, so let’s get started! We’re going to begin by introducing you to the Food Habits Campaign, a participatory sensing campaign designed to help students learn about themselves. In this campaign, you’ll be asked to complete a short survey every time you eat snacks.

Demo can be requested at info@idsucla.org

More about Mobilize/IDS Technology

Participatory Sensing

Participatory Sensing: An approach to data collection and interpretation in which individuals, acting alone or in groups, use their personal mobile devices and web services to systematically explore interesting aspects of their worlds, ranging from health to culture. Read More

Download IDS UCLA from iOS Store or Google Play,
Or visit sandbox.idsucla.org/#survey (Navigation Bar -> Survey -> Take)
Login as Teacher/Student with Login Info
There are five surveys you can take after login: Food Habits, Personality Color, Stress and Chill, Timer Perception, Time Use.

Interactive Dashboard

Visit sandbox.mobilizingcs.org/#campaigns/#dashboard or sandbox.mobilizingcs.org/#demo/ (Navigation Bar -> Explore -> Dashboard or Demo Data) with Login Info

R Programming

Visit sandbox.idsucla.org/#rstudio (Navigation Bar -> Explore -> RStudio) with Login Info
You can try the following commands:
load_labs(1)
data(cdc)
…

Classroom Tools and More!

Visit wiki.idsucla.org for detailed steps.
General Inquiry at info@idsucla.org

Introduction to Data Science – Course Overview
Unit	Unit Title	Unit Description
Unit1	Data and Visualizations	Introduces students to fundamental notions of data analysis—such as distribution and multivariate associations and emphasizes creating and interpreting visualizations of real-world processes as captured by data
Unit2	Distributions, Probability, and Simulations	Students use numerical summaries to describe distributions and introduces probability through the lens of computer simulations for informal inference
Unit3	Data Collection Methods: Traditional and Modern	Prepares students to learn about the various ways of collecting data, including Participatory Sensing, and the effect that data collection has on their interpretation of the patterns theydiscover
Unit4	Predictions and Models	Students learn to make and how to use mathematical and statistical models to predict future observations and how data scientists measure the success of these predictions