An Immersive Computational Text Analysis Course for Non-Computer Science Students at Barnard College (2021)

Abstract: We provide an overview of a new Computational Text Analysis course that will be taught at Barnard College over a six week period in May and June 2021. The course is targeted to non Computer Science at a Liberal Arts college that wish to incorporate fundamental Natural Language Processing tools in their re- search and studies. During the course, students will complete daily programming tutorials, read and review contemporary research papers, and propose and develop independent research projects.

## introduction as computing has become foundational to 21st century literacy @xcite , students across many disciplines are increasingly interested in gaining computing literacy and skills. barnard college is meeting this increased demand through its thinking quantitatively and empirically and thinking technologically and digitally requirements that respectively aim for students "to develop basic competence in the use of one or more mathematical, statistical, or deductive methods" and "foster students' abilities to use advanced technologies for creative productions, scholarly projects, scientific analysis or experimentation." 1 this new 3-credit computational text analysis course will enable roughly 25 students to leverage advanced nlp technologies in their work. 2 the goal of the course is to introduce students to the tools and quantitative methods to discover, measure, and infer phenomena from large amounts of text. unlike a traditional natural language processing class, students will not implement key algorithms from scratch. rather, students will learn how to use existing python libraries like nltk @xcite , gensim @xcite , spacy @xcite , and sklearn @xcite to analyze large amounts of textual data. students will also gain famillarity with webscraping tools and apis often used to collect textual data. ## course design due to covid-19 schedule changes, the course will meet remotely for 95 minutes four days a week over 6 weeks. each week will revolve around a class of methods used in computational text analysis, shown in ## prospective students with summer course registration underway, 25 students are currently registered for the course. since the course is under active development and students come from a range of academic backgrounds, we have asked students to complete a brief survey to help us prepare and tailor the class as much as possible. figure 1 shows results from the 12 students who have completed the survey so far. while we see interest from computer science students, most of the students are programming novices -half of the survey participants indicated they have no prior programming experience outside of one or two programming courses. 10 many students indicated they 8 specifically chapters 4 and 5 for machine learning. 9 https://melaniewalsh.github.io/ intro-cultural-analytics/welcome.html 10 the larger number of interested computer science students might be due to the course being offered by the computer have corpora in mind that they are interested in studying or that they plan on using these methods to enhance their undergraduate theses in other fields. ## measuring stem-related attitudes & beliefs the beliefs and attitudes students possess about learning play a significant role in their academic performance @xcite . given the fact that our course is targeting non-computer science majors, we are interested in seeing how the academic attitudes held by participating students relate to and change throughout their participation in the course. we are particularly interested in measuring students' beliefs about the malleability of their own intelligence, as these beliefs have been shown to predict student motivation, engagement, and performance in academic courses @xcite . to measure the effect such beliefs on students in this course, we will administer the self-theory implicit theories of intelligence scale @xcite . we will also measure students' motivation for computer science using an adapted version of the science motivation questionnaire @xcite . we will have students complete these surveys at the beginning and end of the course, which will enable us to a) measure whether students' initial attitudes significantly relate to their performance in the course, and b) measure whether participation in the course leads to changes in student attitudes over time. ## conclusion we described a new computational text analysis course that will be taught at barnard college in science department. may-june 2021. the broad goal of the course is for students to gain technical skills allowing them to successfully incorporate natural language processing methods into their respective fields and research. we will rely on proven methods to measure the effect the course has on students' perception of their abilities and skills. all material developed for the course (slides, assignments, autograders) will be available for instructors to adopt at their institutions. an updated version of this paper will be available on the first author's webpage with reflections and lessons learned once the course is completed.