Three Digital and Computational Studies courses will be offered in Fall 2016. More information on these courses can be found under the Digital and Computational Studies subject category on Polaris. Each course is interdisciplinary and students will learn both technical and analytical skills.
DCS 1100: Introduction to Digital and Computational Studies
Professor Mohammad Irfan and Professor Crystal Hall
Distribution Requirement: MCSR
How are digital tools and computational methods being applied and studied in different fields? How are they catalyzing changes in daily life? Uses two case studies to introduce these new tools and methods, and to analyze and evaluate their scholarly and practical applications. The first case study is based on Bowdoin’s own history: how can the use of new methods recreate what Joshua Chamberlain could see at the Battle of Gettysburg, and thus better understand the battle and his decisions? Next, considers the contemporary, and asks what is identity in the era of social media and algorithms? Students learn the basics of the Python programming language, introductory spatial analysis with ArcGIS, elementary text and social network analysis, and basic environmental modeling. Assumes no prior knowledge of a programming language.
This course has a separate lab.
Fields represented include:
English, History, Environmental Studies, Biology, Government, Sociology, Mathematics
Scroll through the examples below to see the kinds of projects Introduction to Digital and Computational Studies students completed in Fall 2015:
Original Joshua Chamberlain letter (left) that was then decoded and transcribed in an oXygen file (right). Credit: Ana Timoney-Gomez (created for Introduction to Digital and Computational Studies, Fall 2015).
Joshua Chamberlain’s correspondence network, based on original letters, is visualized in Gephi.
ArcGIS Map of Present Day Topo Map and Historical Map of Gettysburg layered on top. Credit: Ana Timoney-Gomez (created for Introduction to Digital and Computational Studies, Fall 2015).
ArcGIS 3-D image model. The pink color shows what Joshua Chamberlain was able to see at Gettysburg. Credit: Ana Timoney-Gomez (created for Introduction to Digital and Computational Studies, Fall 2015).
DCS 2020: Forecasting and Predictions
Instructor: Michael Kowal
There are few human endeavors as important as making good predictions. Being able to make good predictions is central to effective decision making. Computers and the internet have enabled an explosion in the prediction market where everyone from political consultants to large corporations rely on an ever increasing amount of data to make the predictions that drive their decision making. This course looks at the topic of predictions through the lens of how it is currently impacting our world. By understanding how predictions are made we can better understand how the actors shaping our world are making their decisions. In the Fall of 2016, for example, the focus of the course will be on the Presidential election and will examine questions such as how data analysts forecast the election and how those forecasts in turn are used to alter the behavior of the candidates. Students will learn the techniques used to make predictions and how to asses the quality of those predictions.
Fields represented include:
Government, Computer Science, Mathematics