“My goals for the course are to introduce students to research in digital humanities through a variety of case studies, hands on labs, and readings of transmedia projects.” - Hemphill, 2014

“Just give me the bullet points” - Anonymous

In a few short paragraphs, I will reintroduce Hemphill’s Digital Humanities class with a focus on developing text analysis skills. Her publication narrows down the logistics of her course and provides specific expectations on how students can improve their data analysis skills. Moreover, Hemphill encourages students to use online libraries, such as Project Gutenberg, and learn basic Python programming skills. All of these are major keys, so please follow this blog through the journey of success in Digital Humanities.

To start, Hemphill’s class structure is organized and interactive in way where students work in flexibility when analyzing data. There are various opportunities to present one’s findings through oration, blog postings, group work, and projects. Students often have the opportunity to analyze texts that interest them. With that, class participation is made essential in Research Methods because it’s what makes up lively discussions and a productive atmosphere within the classroom. To support this claim, according to Hemphill, “My excitement about comparing Jane Austen’s Emma to the film adaptations Emma (1996) and Clueless (1995) was met with blank stares for 45 minutes.” Hemphill describes how dull class chemistry can get when students lack the interest to participate. Therefore, in Digital Humanities, it is important to stay intrigued by the textual analysis at hand so that each class can carry its own significance.

Aside from expectations and class structure, the learning experience is the most invaluable in Digital Humanities. The course encourages the use of online databases such as Project Gutenberg, which is an online library that produces free eBooks. Plus, students also learn basic Python programming skills within the GitHub repository service. Although, the use of Python and Project Gutenberg are minor components in this course, these are what supplements a number Hemphill’s discussions. On the other hand, Hemphill explains how she interchanges her methods between single text analysis and text comparison so that students develop the realization on why text analysis is important in digital literature. She emphasizes how repetition and practice are key to learning proper text analysis. Thus, in conclusion, Hemphill’s “research methods” uses specific tools that are geared towards producing an interactive atmosphere with a focus on developing text analysis skills.

Sources

Hemphill, Libby. 2014. “Introducing Text Analytics to Undergraduates.” Libby Hemphill. October 16. http://libbyh.com/2014/10/16/introducing-text-analytics-to-undergraduates/.