CSCI 270 - Project 50%

Description

A major portion of this course will be an in-depth exploration of computational humanities tools and algorithms. You and a partner will be researching and applying one such tool to a dataset of your choice. This will involve a proposal, three presentations, a paper, and code.

Sample Project Topics

This list is by no means exhaustive of possible topics. Please use it as inspiration for your own exploration of the concepts in this course.

Proposal 10%

The first step in your project is developing a proposal. This two-page document will be due at the beginning of class on March 1st. There are three required sections of your proposal.

Research Question 4%

Most importantly, you must clearly state a research question you wish to address through your project. Introduce your topic and its relevance to the course material.

Data Set 4%

Every project must involve the analysis of data. Identify the corpus of data you will be using for your analysis. Who gathered and organized this data? How large is the data (number of individual files/documents/images, total file size?)

Academic References 2%

Include references to sources you will use to inform your analysis. At least one source should be an academic paper, published in a peer-reviewed journal or conference.

Presentations 20%

You will give three presentations about your project.

First Presentation 5%

Presentation Schedule

You will be giving a 4-5 minute overview of your project to the rest of the class. You should focus on the three main elements of the proposal above, clearly explaining the research question, your selected dataset, and the supporting references you will use.

Second Update 5%

Your presentation will be 3 minutes, covering two pieces of your project, one slide for each: First, you will overview the algorithmic details involved. Is your approach to answer your question rule-based, probabilistic, or a mixture of the two? Does it involve machine learning algorithms? How is your data represented and processed?

Second, you will describe a graph/image/sound-file of results based on your research. As you will be in the middle of your project, this could be an aspirational graph (IF everything works correctly, these are the results I hope to get). Clearly identify your axes, use colors and labels to quickly convey your information.

To ensure that these presentations all fit within the April 10th class period, I will need you to submit your slides to me via Moodle by April 9th at 11:55pm. I will assemble them all into one large presentation.

Final Presentation 10%

Finally, you will give a 10 minute in-class presentation. Time and material should be split evenly between all project partners. Your objective in the presentation is to fill us in on the main ideas of how you approached and analyzed your topic. Leave at least one (1) minute for questions at the end of your presentation.

Practice is strongly encouraged prior to your actual presentation. The best way to be comfortable with presenting in front of an audience is to practice. You will be graded on both the organization and the presentation of your talk. The 10 minute time-limit will be strictly enforced to ensure equal time for all presentations.

Paper and Code 20%

Summary Paper 15%

Your paper must be at least 12 pages. Your paper should be readable by a layperson who is not familiar with your tools and algorithms but has a basic understanding of computer science; essentially, write the paper for yourself before you took this class, based on the prereqs of CSCI 150: Foundation of CSCI. You should include the following sections Be sure to make good use of figures and graphs to demonstrate your results, use proper grammar and spelling, and use proper citations.

Data and Implementation 5%

Finally include any code and IPython documents along with your dataset. Your notebook should be well-organized including headers and Markdown blocks to denote the different sections of your analysis.
© Mark Goadrich, Hendrix College