Data Science for Everyone with ISLE

Data Science for Everyone with ISLE

Data Science for Everyone with Integrated statistics learning environment (ISLE): Leveraging Web Technologies to Increase Data Acumen. At Carnegie Mellon, the Department of Statistics & Data Science teaches thousands of students with future degrees ranging from Pre-Med to Rhetoric to Chemistry to Business to Statistics & Machine Learning and partners with a wide range of industries and non-profits on data-centric problems of varying complexity. While the term “data science” is often associated with the need for high level technical skills and specific programming languages, in our experience, the struggle to fully leverage and incorporate data science is far more related to understanding how to think and talk about data, interpret data, make decisions with data - that is, data literacy and data acumen.

This presentation was recorded at GOTO Chicago 2020.

Rebecca Nugent - Professor of Statistics & Data Science

ORIGINAL TALK TITLE Data Science for Everyone with ISLE: Leveraging Web Technologies to Increase Data Acumen

ABSTRACT

Much of the first wave of Data Science programs was built on a foundation of already existing computing-oriented classes; less effort was spent on how people from diverse backgrounds and disciplines approach or could optimally collaborate on solving problems using data. At Carnegie Mellon, the Department of Statistics & Data Science teaches thousands of students with future degrees ranging from Pre-Med to Rhetoric to Chemistry to Business to Statistics & Machine Learning and partners with a wide range of industries and non-profits on data-centric problems of varying complexity. While the term “data science” is often associated with the need for high level technical skills and specific programming languages, in our experience, the struggle to fully leverage and incorporate data science is far more related to understanding how to think and talk about data, interpret data, make decisions with data - that is, data literacy and data acumen.

To empower a broader audience of savvy data consumers, our research group developed ISLE (Interactive Statistics Learning Environment, http://www.stat.cmu.edu/isle), an interactive platform with delivered functionality enabling students and professionals engaged in re-training or upskilling to easily explore Statistics & Data Science concepts through both self-directed, asynchronous materials or instructor-led, synchronous lessons. Built using web technologies, ISLE runs on any web browser, operating system, as well as both desktop and mobile devices. By leveraging statistical methods and functions implemented as part of the stdlib JavaScript library (http://stdlib.io/), the platform enables users to analyze data in a web browser, greatly reducing server load. The ultimate goal is an accessible platform for data science, which lowers the barriers for a wide range of practitioners to start working with and analyzing data.

The platform also supports student-driven inquiry and case studies, which users can complete independently or collaboratively in real-time. We track and model every click, word used, and decision made throughout the data analysis pipeline from loading the data to a final written report including real-time visualizations of collected data of mixed modality (user actions, clicks, text, audio, video, etc). The platform is flexible enough to allow adaptation, providing different modes of data analysis and active learning, and collaborative opportunities for different audiences. With ISLE, everyone can harness the power of data science!

TIMECODES

  • 00:00 Intro
  • 02:37 Interacting with data science
  • 04:46 Early definitions
  • 08:11 Data science, a view
  • 10:18 The science of data science
  • 25:48 Carnegie Mellon University
  • 27:47 Integrated statistics learning environment (ISLE)
  • 33:03 What are we learning/researching?
  • 36:38 Takeaways

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