⭐ The below is drawn from the requirements for CS224U and CS384.

General

The final project is the main assignment of the course. Projects are required to be related in a reasonable way to at least one of the central topics of the course or related to other applications of natural language processing/language technology to support teachers. Final projects can be done in groups of 1–3 people; in our experience, groups of 3 lead to the best outcomes, so we encourage you to form a team of that size. Each project team will be assigned a mentor (a member of the teaching team), who will provide feedback on all their project-related work and generally be available.

Submission Format

1. Rationale for Project (=Literature Review + Motivation)

I just uploaded the template for the project rationale:

For the rationale, we encourage you to use this LaTeX template. Instructions on how to use it can be found here. This is a short paper (4~5 pages, excluding references) providing a rationale for your proposed study or tool. The rationale should include two primary components:

  1. Literature Review: A summary and synthesis of several papers in the area of your final project. Groups of one should review 5 papers, groups of two should review 7 papers, and groups of three should review 9.

    The ideal is to have the same topic for your rationale and final project, but it's possible that you'll discover in the rationale that your topic isn't ideal for you, so you can switch topics (or groups) for the final project; your rationale will be graded on its own terms.

    Some suggestion highlights on literature review structure from Chris Potts and Bill MacCartney from CS224U (check out lots of useful materials there and there):

    1. General problem/task definition: What are these papers trying to solve, and why?
    2. Concise summaries of the articles: Do not simply copy the article text in full. We can read them ourselves. Put in your own words the major contributions of each article.
    3. Compare and contrast: Point out the similarities and differences of the papers. Do they agree with each other? Are results seemingly in conflict? If the papers address different subtasks, how are they related? (If they are not related, then you may have made poor choices for a lit review...). This section is probably the most valuable for the final project, as it can become the basis for a literature review section..
    4. Future work: Make several suggestions for how the work can be extended. Are there open questions to answer? How do the papers relate to your final project idea?
    5. References section: The entries should appear alphabetically and give at least full author name(s), year of publication, title, and outlet if applicable (e.g., journal name or proceedings name). Beyond that, we are not picky about the format. Electronic references are fine but need to include the above information in addition to the link.
  2. Motivation for your project: Building on the literature review, provide a concise (~half a page) motivation for your final project. This motivation should address questions including but not limited to the following (adapted from Nguyen et al., 2020). If you're developing a tool rather than seeking an answer to the research question, substitute "answer question" with "address need":
    • Who is waiting for the answer to your question? What would knowing the answer change, both in education research and in teachers' and students' lives?
    • Are these questions answerable with text? Are they answerable only or primarily with text?
    • Do you have access to data that will support these research questions?
    • Have you considered the ethical implications of your research (e.g. dual use)? Who will be affected by decisions made based on your results?

2. Experimental Protocol

This is a short, structured report (6~8 pages, excluding references) designed to help you establish your core experimental/computational framework.

Required sections:

  1. Research Questions: A statement of the project's core research questions.
  2. Data: A description of the dataset(s) that the project will use for either the analyses or evaluations.
  3. Methods or Approaches: A description of the methods or approaches that you'll be using, and a preliminary description of the approach that will be the focus of your investigation. At this early stage, some aspects of these approaches might not yet be worked out, so preliminary descriptions are fine.
  4. General Reasoning or Discussion: An explanation of how the data and approach come together to help answer or evaluate your core research questions.
  5. Summary of Progress: what you have been done, what you still need to do, and any obstacles or concerns that might prevent your project from coming to fruition.
  6. References: In the same format as for literature review.

3. The Project Pitch

Every group will give a 4 minute pitch, where they present their project idea to a group of teachers. The pitch should focus on the motivation for your project and provide a (high-level) summary of your experiment protocol in a way that is understandable to a non-technical person. Your goal is to convince teachers that this project is worth pursuing, and to receive honest feedback from them on how to make your project more valuable to educators. Your peers, instructors and teachers will use this rubric to evaluate your pitch.

4. Final Paper

This paper should be up to 10 pages long including references, and should adhere to the formal requirements and stylistic expectations for research contributions in computational social science / NLP.

Unlike for the lit review and experiment protocol, you are required to use one of the following templates for your submission:

If you have any questions about organizing your paper, please talk to the instructors. This handout by Chris Potts can provide helpful guidelines for presenting your research to an NLP audience, and it is helpful even if your work is targeted at a different audience (e.g. learning sciences).

There are two required paper sections that are special to our course: