Brian Kokensparger - Guide to Programming for the Digital Humanities: Lessons for Introductory Python
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- Book:Guide to Programming for the Digital Humanities: Lessons for Introductory Python
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As an introduction to programming for the Digital Humanities (DH), this book presents six key assignments oriented on DH topics. The topics include Computing Change Over Time (calculating burials at a historic cemetery), Visualizing Change Over Time (visualizing the burials at the historic cemetery), Textual Analysis (finding word frequencies and stop words in public domain texts), XML Transformation (transforming a simplified version of XML into HTML styled with CSS), Stylometry (comparing the measured features of graphic images), and Social Network Analysis (analyzing extended relationships in historic circles).
The book focuses on the practical application of these assignments in the classroom, providing a range of variations for each assignment, which can be selected on the basis of students specific programming background and skills; atomic assignments, which can be used to give students the experience they need to successfully complete the main assignments; and some common pitfalls and gotchas to manage in the classroom.
The books chief goals are to introduce novice computer science (CS) students to programming for DH, and to offer them valuable hands-on experience with core programming concepts.
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An introduction to the topic of using Digital Humanities assignments for an introductory programming course in Python, which lays out the context of the book. It begins with a brief anecdote about what led the author to initially develop these assignments, provides a brief overview of the field of Digital Humanities, and introduces the reader to how the book is arranged with a hint of what is to come.
Imagine that you are a computer science instructor, moving happily along in your career. You teach the same old programming courses: introductory programming, introduction to computing, and computer organization. Your syllabi are set, and you barely need to review your notes before shuffling into class each day. Then one day, an associate dean calls: the new Digital Humanities (DH) initiative needs a Programming for the Humanities course. And wouldnt you like to teach it?
This happened to me. What should I teach? How should I teach it? How is programming for the humanities different from any other programming?
The solution, for me, was to teach all the concepts and structures typical for a regular computer science course (loops, branching structures, variables for assignment, etc.), but to incorporate programming assignments from the digital humanities domain (textual analysis, data visualization, stylometry, social network analysis, etc.). This book provides the full instructions, sample code, and resources for current introductory programming instructors to adopt these DH assignments into their own courses using the Python language.
All the assignments in this book have been used over at least 4 semesters in my classroom, in classes that average from 26 to 30 students. The assignments were originally designed for the course, and have been tweaked and assessed over time to optimize student learning. This is a tricky process, because the range of students who arrive in an introductory programming course varies from those with no coding experience at all (common especially among the humanities students), to those who already have impressive programming skills. Each of these assignments are presented specifically to be used with novice programming students, but each also includes a discussion of the flexibility allowed for students who have higher-level skills. The assignments have been successfully implemented for this entire range of student abilities.
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