This page displays the different teaching materials that have been created by members of the Digital Integration Teaching Initiative team. The materials are organized by thematic content and each have summaries, learning goals, learning objectives, examples from specific courses, and, in some instances, examples of student work.

Table of Contents

Citation Management

Summary

This module introduces Zotero, a citation management software, including how to use Zotero, its different features, and how it can be effective for research.

Learning Goals

      • Understand how to use a citation management software to organize research materials
      • Understand Zotero’s functions and features

Learning Objectives

      • Differentiate source types
      • Define several important functions of Zotero and citation management, including libraries, ISBN, tags, and more.
      • Input bibliographic information both manually and automatically into Zotero
      • Transfer a library into a Works Cited page

Examples from Courses

Introduction to Zotero in Global Justice (Serena Parekh, Philosophy)

Introduction to Zotero in Criminology Research Methods (Megan Denver, Criminology)

Example Student Work from Global Justice:

Example Student Work from Criminology Research Methods:

Computational Text Analysis

Summary

This one-day workshop, which can either be part of a larger assignment or a standalone workshop introducing the essential techniques and tools, provides an introduction to text analysis using digital methods. This workshop can either expose students to browser-based tools that perform text analysis (such as Voyant, WordTree, and WordCounter) or demonstrate to students the basics of more powerful text analysis tools, such as those that use Python or R. By the end of this workshops, students should have a basic understanding of different data types, recognize how the different tools analyze those types, and be able to do some basic analysis themselves.

Learning Goals

      • Understand the basics of text analysis and how these tools analyze input texts
      • Learn the fundamentals for corpus building and basic pre-processing methods
      • Understand the differences between tools and how they work with data

Learning Objectives

      • Use the browser-based tools provided (or have a general sense of how to run code in R or Python)
      • Explain the behind-the-scenes work of the text analysis tools
      • Retrieve data that can be analyzed by these tools
      • Explain the results of the text analysis tool

Examples from Courses

Web-based text analysis tools in International Political Economy and Political Science Research Methods (Kirsten Rodine-Hardy, Political Science)

Corpus-building and web-based text analysis tools for Introduction to Writing Studies (Neal Lerner, English)

Text analysis in practice in Environmental Politics (Daniel Aldrich, Political Science)

Data Preparation for Mapping

Summary

An in-class workshop to teach students how to prepare their data in Excel for mapping using geographic information systems (GIS). The class began by explaining how to gather data and know what a dataset contains using metadata repositories. Students then worked hands-on in Excel to import CSV files, describe the data, clean the data, and prepare a final dataset to be used in a future GIS workshop.

Learning Goals

  • Understand what datasets are and how to find, upload, and read datasets
  • Introductory skills in Excel
  • Understand file formats
  • Learn to clean and create a final dataset

Learning Objectives

  • Discuss what a dataset is, what variables are, and examples of applications in UN Sustainable Development Goals
  • Go on the UN Sustainable Goals website to upload a dataset and read the metadata repository
  • Learn to convert a CSV file into Excel format and vice versa
  • Utilize Excel charts to prepare a final dataset and delete unneeded data
  • Prepare a final dataset in Excel with the necessary data points for GIS mapping

Examples from Courses

Data Preparation for GIS in Global Governance (Denise Garcia, Political Science)

Example Student Work from Global Governance:

Data Visualizations

Summary

This module demonstrates how to use the Tableau software suite to perform spatial analysis and visualizations. It is a two-day module. The first day will go over a tutorial and introduction to Tableau to teach students how to use the specific mapping and visualization software. The second day is a hands-on workshop where students will bring their own research questions to the data provided.

Learning Goals

  • Learn the basics of Tableau, a powerful data visualization tool
  • Understand how Tableau interprets data and values
  • Learn research questions that can be answered through data visualizations and data analysis

Learning Objectives

  • Understand spatial data structure in the context of Tableau
  • Learn Tableau terminology and understand how Tableau displays data
  • Know how to plot points in Tableau based upon x/y coordinates
  • Understand filtering and visualization options for spatial data
  • Know how to visualize data using other Tableau methods like line or bar graphs

Examples from Courses
Introduction to Tableau in Race, Crime, and Criminal Justice (Ramiro Martinez, Criminology)

Example Student Work from the Race, Crime, and Criminal Justice:

Digital and Data Ethics

Summary

A guest lecture module that introduces students to computational social science, digital humanities, and how digitized methods shape our society. The module also provides examples of what types of data are being collected, how this data is being used by both large corporations and social scientists, and the ethical implications of living in a digital world.

Learning Goals

    • Introduce students to concepts such as big data; algorithms; algorithmic bias; digital surveillance; and fairness, accountability, and transparency in machine learning
    • Examine how data is being used in society
  • Understand the basic logic behind machine learning, including input data, weighing values, output results, and the impact of these results
  • Understand how digital methods can inform social science and humanities research

Learning Objectives

  • Use tech companies’ individual data collection and categorizations to understand what type of data is collected about us and how companies use this data
  • Learn concrete examples of how data impacts our daily lives
  • Become familiar with what code looks like and how social scientists use programming to answer social science questions
  • Discuss the ethical implications surrounding digitized data

Examples from Courses

Introduction to Computational Social Science and Digital Ethics in Introduction to Sociology (Steven Vallas, Sociology)

Data and digital ethics in Sociology Research Methods (Ineke Marshall, Sociology)

Data ethics, collection, and organization in First Year Writing (Kelly Garneau, Writing Program)

Digital Scholarly Editing

Summary

Multi-week assignment that asks students to develop digital scholarly editions of historical or literary documents. The project begins with an introduction to the fundamentals of WordPress and includes discussions of different, methods, tools and strategies for editing humanities materials. Students work in pairs or small groups to edit materials from a shared document, making decisions about regularization, document selection, contextualization and annotation, management of textual uncertainty, editorial transparency, and other aspects of digital scholarly editing. Students determine the goals and audiences for their editions and articulate in an editorial headnote how their digital pages support and highlight their desired readings. The project concludes with collective feedback and reflection.

Learning Goals

      • Understand the fundamentals of digital scholarly editing and the range of decisions available to editors
      • Identify a particular editorial position and edit a text for digital publication according to that position
      • Articulate the rationale behind specific editorial choices

Learning Objectives

      • Gain proficiency with the WordPress content management system
      • Learn how to edit and publish humanities research materials for the web
      • Annotate and contextualize a historical or literary document

Examples from Courses

Cacodemon Shakespeare in Introduction to Shakespeare (Erika Boeckeler, English). Digital edition of The Merchant of Venice and assignment materials.

Introduction to Programming for Statistics (Python or R)

Summary

Hands-on workshop that provides a brief introduction to the scripting language Python or R using different coding platforms, with an eye toward data representation and analysis. By the end of the workshop, students should have enough knowledge to do basic data analysis and visualization using Python or R. The assumption is these skills will be used and built on throughout the course, to equip students to do a final statistical project.

Learning Goals

      • Understand what Python or R is, why these languages are useful, and how to use Python or R for data analysis.
      • Understand how Python or R interacts with, and represents, data.

Learning Objectives

      • Explain Python or R basics—variables, variable types, manipulating variables, and dataframes
      • Explain what the different libraries R or Python offer and what they do
      • Write enough code to:
        • Read in a dataset and manipulate a few variables
        • Produce basic summary statistics from a dataframe
        • Produce three visualization from the dataframe: histogram, scatter plot, and bar chart
        • Implement a T-Test
        • Implement a simple OLS regression model and interpret the output

Examples from Courses

Introduction to Python for Statistics in Health Economics and Health Care Policy (Angela Kilby, Economics)

Introduction to R for Statistics in Labor Economics (Alicia Sasser Modestino, Economics)

Example Student Work from Labor Economics:

Introduction to Website Building

Summary

One day hands-on workshop, usually an introduction to an assignment, that provides a brief introduction to using a website building platform, such as WordPress, centering what the website platforms can offer and how students can use them effectively for their assignments. By the end of the workshop, students should know how to navigate the particular website platform as well as understand that their choices when using this platform are rhetorical and should relate to the context of the site as well as their intended audience.

Learning Goals

      • Understand the basics and more advanced features of a website building tool, as well as the constraints and affordances of the platform
      • Understand the rhetorical and digital choices that go into building a website

Learning Objectives

      • Learn the vocabulary used for the tool (ex: in WordPress, the difference between “pages” and “posts”)
      • Create a website by following a step-by-step process
      • Explain how to use the website platform as well as the rationale behind particular choices
      • Research other external resources with documentation and explanations of the platform

Examples from Courses

Introduction to WordPress in the English/Political Science Co-op Course (Lisa Doherty)

Introduction to WordPress in Feminist Resistance (Suzanna Walters, Women’s Studies, History, Sociology)

Introduction to Wix in German for Young Professionals (Carolin Fuchs, German)

Examples of student work from German for Young Professionals:

Qualitative Data Analysis

Summary

The first day of this module will go over the steps to conducting research on first years’ experiences at Northeastern by introducing survey and interview analysis tools. Specifically, this module will introduce Google Forms to create a collaborative survey; students will come to class with their potential questions, create their surveys in small groups, and then take everyone’s survey.

The second day of the module will ask students to choose one person to interview, transcribe that interview, and qualitatively code it using Nvivo. For this portion, we will use sample transcript excerpts as well as the students’ transcripts of their interviews to practice qualitative coding and visualizing results with NVivo.

Learning Goals

Day 1: Survey Creation and Analysis

      • Understand how to formulate different types of research questions, from open-ended to likert scale
      • Understand how to use Google Forms to collaboratively create a survey and view/analyze the results
      • Understand how to do follow-up questions for more interesting answers

Day 2: Qualitative Coding with NVivo

      • Define qualitative coding and why it can be useful while doing research
      • Understand what NVivo is as a research tool and what it can do
      • Learn important NVivo-specific vocabulary to aid independent research

Learning Objectives 

Day 1: Survey Creation and Analysis

      • Build a collaborative survey in a small group using Google Forms
      • Learn how to analyze the results on Google Sheets using basic functions like formulas or charts

Day 2: Qualitative Coding with NVivo

      • Create a basic set of nodes using sample transcripts
      • Learn out to import data, create nodes, code data, and see/interpret results of coding
      • Use Nvivo to begin creating nodes and coding their own interview transcripts

Examples from Courses 

Qualitative coding for text analysis in Research Methods in Sociology (Ineke Marshall, Sociology)

Qualitative coding for text analysis in Criminology Senior Capstone Seminar (Simon Singer, Criminology)

Examples of student work from Research Methods in Sociology:

Storytelling with Spatial Mapping

Summary

This module will go over components of storytelling and how these components may be integrated in maps. Specifically, this in-class workshop will teach students how to use Knight Lab’s StoryMaps web-browser application by providing step-by-step instructions, a sample map, and sample data for students to use to practice building their own maps.

Learning Goals

  • Understand components for compelling storytelling
  • Understanding particular choices made when building a map
  • Understanding how to collect data for mapping
  • Understanding KnightLab StoryMap’s interface and where it gathers its information

Learning Objectives

  • Articulate particular choices made when telling a story using a map
  • Follow a step-by-step guide for creating, saving, and publishing maps using KnightLab StoryMaps
  • Implement data into KnightLab StoryMaps, including location information, images, and text
  • Navigate StoryMaps’ map markers and location-finding system

Examples from Courses
Spatial Mapping in the Science of Play (Emily Mann, Human Services)

Example Student Work from the Science of Play:

Text Encoding

Summary

Multi-week assignment that provides an introduction to modeling archival documents using the Text Encoding Initiative (TEI) markup language. The project begins with a class visit introducing the core concepts of TEI markup and demonstrating some analytical applications of text encoding. Students then transcribe and encode a brief archival document of their own, while working in groups to make editorial decisions about how they will encode their documents in TEI/XML markup and publish them online. Individual students are responsible for encoding their archival documents, writing reflective introductions on their projects, and presenting on their work to the class; groups are responsible for authoring editorial declarations that describe all of their choices in modeling and representing their documents.

Learning Goals

      • Understand how text encoding can be used to model humanities research materials and learn some of the goals and theoretical foundations of TEI encoding
      • Understand the fundamentals of digital scholarly editing

Learning Objectives

      • Understand the basics of XML and TEI
      • Understand how to edit TEI documents using the Oxygen XML editor
      • Students learn how to:
        • Encode archival documents using TEI/XML
        • Use the TEI Guidelines to look up elements and attributes
        • Add special characters with entity references and Unicode
        • Control some basics of how encoded documents appear online using CSS
        • Recognize the ramifications of different approaches to encoding, make informed decisions about how to mark documents up, apply those decisions consistently, and articulate them clearly

Examples from Courses

Encoding Digital Editions in Gender, Sex, & the Renaissance/Restoration Body (Marina Leslie, English)

Encoding Shakespeare in Introduction to Shakespeare (Erika Boeckeler, English)

Example Student Work from Gender, Sex, & the Renaissance/Restoration Body:

Example Student Work from Introduction to Shakespeare: