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Research Methods and Design

A guide on common research methods.

Data Literacy

Overview

Data literacy is the ability to read, analyze, create, manage, and talk about data. Understanding how data functions is both important at an academic level--whether you are writing a dissertation or working on a data science project---but also at a personal level. Data regularly informs our daily decisions. The ability to read, analyze, and understand data can impact something as simple as reading a weather report or as important as who to vote for or how money for social services is allocated. Lastly, understanding data use is an important disposition to have when protecting your own privacy and information. 

Data Literacy Crash Course [YouTube Video Playlist]

Study Hall: Data Literacy presented by Arizona State University + Crash Course

Building the dispositions required for data literacy takes time and patience. However, there are some good primer courses available to you should you like to improve your data literacy skills. We recommend the one below.

Course Overview

"Data is everywhere. We expect it on our computers and in science labs, but it’s also in things like the food we eat, the websites we surf, and the cars we drive. We use it at work, school, or even just scrolling through YouTube. In this 15 episode playlist, your host Jessica Pucci will help us learn to think about the data we're presented with."

Watch below or click through to YouTube to see the full list of videos.

 

Equity and Data Literacy

What is Data Equity?

Data equity is the process of considering data--how it is gathered, analyzed, and disseminated--through an equity lens. The number one rule of data equity is recognizing that, in every data project, we make subjective, human choices that have real, human impacts. Throughout the research and data collection processes, choices are constantly being made. Data equity is working towards ensuring those choices align with the goals, priorities, and contexts of the projects in which you are working.

Key Questions for Data Equity

  • Who is getting prioritized?
  • Are you factoring in the human, lived experiences of the data and its potential impacts?
  • Whose value system is being centered and privileged? Whose definition of success?
Information in this overview was inspired by We All Count (https://weallcount.com/)

Resources on Data Equity

The following items cover a variety of topics surrounding data and research equity. 

Online Resources, Tools, and Frameworks

Books