Using encoding to teach textual analysis

Using encoding to teach textual analysis

By Jessica Kane, Visiting Assistant Professor of English at Albion College

This collaboration was part of the WWP’s Teaching Partners program; for more information, see the digital edition created by the students or watch this short video on the project

Eliza Haywood’s novella “Fantomina” (1725) begins by introducing the reader to “A YOUNG Lady of distinguished Birth, Beauty, Wit, and Spirit” (258) who creates four different personas, seduces the same man four different times, and ends up banished to a convent in France after an accidental pregnancy unravels the whole scheme. The beautiful, witty, and spirited students of my ENG 255 course at Albion College faced the contradiction of all survey courses: combining breadth (British Literature 1660-1900) and depth (textual analysis). One way we sought to balance these competing goals was through using textual encoding.

Our project, “Encoding Fantomina”, required the students to use TEI/XML encoding to tag several different categories of information in the text. We identified  elements needed for the text to show up cleanly online, like paragraphs and page numbers. We also identified textual elements useful for future researchers, like names, places, dialogue, and letters.

A screenshot of the Oxygen Editor view of the first few sentences of “Fantomina” with structural and textual element encoding. It includes tags like <code><p></code>, <code><hi style="text-transform:uppercase"></code>, and <code><rs type="person"></code>.
Structural and textual element encoding.

We also identified sections of text that referred to class, gender, and various emotions – interpretive categories that the class collectively determined. The class, gender, and emotion sections were styled to show up as different colors when published on a website, to help us identify relationships between these different categories.

A screenshot of both the Oxygen Editor view and the html view of several sentences from “Fantomina” with analytical encoding. It includes tags like <code><seg ana="#deception":></code>, <code><seg ana="#happiness"></code>, and <code><seg ana="#gender"></code> in the Oxygen Editor view, and the words so tagged in different colors in the html view.
Analytical encoding

Both the process and results of this project exceeded my expectations, and provide a model for incorporating textual encoding into future courses. Two key patterns stood out in the student reflections: first, that the process of encoding helped them pay more attention to the details of the text and discover things they’d previously missed; and second, that they were surprised and often delighted by the use of technology in literary analysis.

This project began when I emailed the Women Writers Project in January 2022 to ask if they ever collaborated with classes outside of Northeastern. WWP Assistant Director Sarah Connell generously agreed to try out a collaboration, and we determined the project’s schedule and scope via lots of emails and a video chat. We chose “Fantomina” because it was a text we had already read and discussed in the class, was short enough to complete within the time available, and fit the scope of the Women Writers Project. Sarah and WWP encoder Colleen Nugent (Ph.D. Candidate, History) worked hard to design the lessons the students would need, and the three of us met by video chat in early March to teach me the basics of TEI/XML.

Sarah and Colleen virtually attended four classes in March and early April to help students decide on interpretive categories and teach them TEI/XML. The students began encoding during those classes and had Sarah and Colleen on hand to troubleshoot with us when we ran into questions. I set aside time during several other class periods without Sarah and Colleen for the students to be able to encode together, and they finished any remaining encoding as homework. We ended the semester with a student showcase at the Albion College Library, where the students got to show off both their encoding and interpretive work.

Three pictures of glass display cases that each have three shelves and mixed gold and white vertical rectangles along the back wall. On the shelves are printed-out placards of different parts of the “Fantomina” text with smaller explanatory placards next to them. Some of the “Fantomina” placards are of the Oxygen Editor view, showing the encoding, while others are of the html view, showing the interpretive sections in different colors.
Showcase
Three pictures of glass display cases that each have three shelves and mixed gold and white vertical rectangles along the back wall. On the shelves are printed-out placards of different parts of the “Fantomina” text with smaller explanatory placards next to them. Some of the “Fantomina” placards are of the Oxygen Editor view, showing the encoding, while others are of the html view, showing the interpretive sections in different colors.
Showcase
Three pictures of glass display cases that each have three shelves and mixed gold and white vertical rectangles along the back wall. On the shelves are printed-out placards of different parts of the “Fantomina” text with smaller explanatory placards next to them. Some of the “Fantomina” placards are of the Oxygen Editor view, showing the encoding, while others are of the html view, showing the interpretive sections in different colors.
Showcase

In their project reflections, several students noted that encoding made them read the text more than once, and “pay more attention to the context in which things are being stated”. One student commented that encoding made her realize her section included the expected emotions of “happiness, sadness, and desire”, but also “other emotions in the section that were not given a name in the encoding…[like] anger (or words associated with anger in some way), modesty, dissatisfaction, and possibly hurt”. Another student wrote that he “kept seeing things I found in my sections in the other sections of the story”, an example of intratextual connection that is a key part of close reading and analysis. Most students talked about how various emotions intertwined in the story, something they had not really noticed when we discussed the text earlier in the semester. They were also able to discuss their analysis of a small section of the text during the showcase, when they had to translate the work we had done together to an audience that knew nothing about the text or project.

The project was a huge success from a textual analysis standpoint. Students were forced to slow down in their reading, they practiced identifying elements of the text, they thought about how those different textual elements fit together, and they expressed this analysis and significance to a new audience. My primary goal for the project was teaching and practicing textual analysis, so this was a wonderful outcome.

Another outcome came as a surprise: many students expressed shock and delight that they could combine literature and technology in this way. Some had previous coding experience, but many found the idea “scary”, “difficult”, or “confusing” before they started. One commented that it was “something I wasn’t expecting in an English course”. Several students wrote that the process was easier and made more sense than they originally expected, and nearly all discussed feeling proud of themselves for tackling the project. Some of our showcase visitors also expressed surprise and interest in this particular iteration of digital humanities, and the students had rich conversations with people interested in exploring similar approaches in their own fields.

I am immensely proud of the work the students did to learn this new set of skills and apply them in our class. They all agreed that I should use this approach to teaching and practicing close reading and textual analysis in the future. We are grateful to Sarah, Colleen, and the Women Writers Project for the time and energy they put into this project – and I am particularly grateful to Sarah, who said “yes” over and over to someone who emailed her out of the blue.

 

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