roles

I frequently use roles in my teaching, inviting students to take on different hots. Explorer, Artist, Judge, and Warrior — Each is a way to see and interact with the world.

Below the introduction from the syllabus to an undergraduate class on data science, intended for students new to programming. Roles were a key element for framing the class (1).

(1) Technical Foundations for Informatics, Autumn, 2019.


As you may know, Informatics is the “study, design, and development of information technology for the good of people, organizations, and society” (see What is Informatics?).  In this class we’ll be learning the technical foundations of Informatics, focussing specifically on the R programming language and related programming tools. 

To develop programming skills and knowledge for data, we’ll pursue work that will position you to make a positive impact in our world through data science. You might think of data science as a field of study that overlaps with Informatics.  Here’s a definition:

“Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.”* 

This technical definition, unfortunately, is value-neutral. In this definition, where is the human being?  Where is society? Our global civilization? Given the current threats to rationality, democracy, and the Earth, this is a serious limitation because while data science promises awesome benefits it has also led to great harms (O’Neil, 2016). Hence, in this course, we add to the technical definition the following: 

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, with a focus on human dignity, human well-being, and environmental sustainability.

In other words, methodsprocessesalgorithms and systems 
ought to be developed to be sensitive to human values and, in addition, new knowledge and insights ought to be considered in terms of their impacts on the human condition, especially the environment and the societal challenges that come from a degraded environment.

Throughout the quarter you’ll be a coder, a thinker, and an innovator: 

You’ll learn foundational programming tools for the Information Lifecycle. Working largely individually, you’ll learn to code and, most importantly, you’ll learn how to learn to code.  You’ll learn the R programming language, and some essential tools, including the command line, source control, RStudio Interactive Development Environment, and more.

You’ll learn some theory about the Information Lifecycle, which comprises data collection, representation, storage, retrieval, modeling & prediction, and visualization. And, working with theory and method from value sensitive design, you’ll learn to think  rigorous about the benefits and harms of data science for human beings, societies, and the Earth.

You’ll apply your knowledge for the Information Lifecycle and your programming skills to address a real-world data challenge. Demonstrating strong teamwork and responsible innovation, you’ll find a problem, explain why the problem matters, and develop a robust solution. You’ll learn to give and receive criticism and you’ll reflect on your professional goals. 

*Data Science. (n.d.). In Wikipedia. Retrieved August 14, 2019, from https://en.wikipedia.org/wiki/Data_science