Not logged in
Talk
Contributions
Create account
Log in
Navigation
Main page
About
People
Publications
Teaching
Resources
Research Blog
Wiki Functions
Recent changes
Help
Licensing
Page
Discussion
Edit
View history
Editing
Interdisciplinary Graduate Methods (Spring 2024)
(section)
From CommunityData
Jump to:
navigation
,
search
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
== Research Project Design == As a demonstration of your learning in this course, you will design a research project. I strongly urge you to work on a project that will further your academic career outside of the class. There are many ways that this can happen. Some obvious options are to prepare a project that you can submit for publication, that you can use as pilot analysis that you can report in a grant or thesis proposal, and/or that fulfills a degree requirement. The default expectation is that you will prepare the project on your own but it may be possible to work as a small team (maximum 3 people). Team projects are expected to be more ambitious than individual projects. Multiple intermediate assignments will help you to develop your idea and to get feedback from me and others. The final deliverable will be: * A proposal of no more than 8 double-spaced pages (page count does not include references, figures, tables, or appendices). ** Use 12-pt font ** Papers over the page limit will be penalized * The proposal should be organized as: a) introduction, b) background/theory, c) methods (specifying data, sampling strategy, measures, etc.), and d) dummy results (sample tables and or/figures). * A typical methods section for a quantitative study includes subsections on: Data and sampling, study design, dependent variables, independent variables, control variables, and an analytic strategy. * Measurement instruments and other supplementary material can be included as an appendix to the proposal, and will not count towards the 8 page limit. There are several intermediate milestones (outlined below), and deadlines to help you accomplish a successful research project. Unless otherwise noted, all deliverables should be submitted via Brightspace. === Hypotheses === ;Due dates: In class feedback: January 25; Final idea: January 29 ;Maximum length: 1.5 pages Early on in the class, you will bring three ideas for research projects to class. For each idea, you should provide 1) a brief description of your research topic 2) your research questions, hypotheses, or objectives, and 3) a brief description of data that you could gather or use. In total, your ideas should be no more than 1.5 pages. We will circulate ideas in class and workshop them in small groups. You will then identify what you see as the most promising project, which you will submit on Brightspace. === Literature Review === ;Due date: February 19 ;Maximum length: ~4-5 pages Based on the principles discussed in class, you will complete a full draft of a Background / Theory section. While norms differ for the length of literature reviews across disciplines and even across journals, this will be an exercise in making an argument with brevity, and your document should be no more than 5 pages (excluding references). The paper should make an argument for what the problem is that you are studying, definitions of key terms, concepts, and constructs, and an argument for your hypotheses / research questions. Typically, these will appear near the end of the literature review. === Methods and Dummy Results === ;Report due date: March 18 ;Maximum length: ~3 pages You will identify an analytical strategy that is appropriate for answering your research questions or testing your hypothesis. You will explain how you will obtain the data for your study, how you will measure the variables of interest, and (assuming you are taking a quantitative approach), what statistical tests you will run. You will also create dummy results. You will consider how you would like to explain and visualize your results and create dummy versions of these plots. This can include regression tables, scatterplots, boxplots, correlation tables, etc. You can create these either with synthetic data or create them by hand (e.g., by drawing them). === Final Presentation === ;Presentation due date: April 22 and April 24 ;Maximum length: 8 minutes The presentation will provide an opportunity to share a brief summary of your project with the other members of the class. All presentations will need to be a maximum of 8 minutes long. Concisely communicating an idea in the time allotted is an important skill in its own right. Presentations should be uploaded to Brightspace.
Summary:
Please note that all contributions to CommunityData are considered to be released under the Attribution-Share Alike 3.0 Unported (see
CommunityData:Copyrights
for details). If you do not want your writing to be edited mercilessly and redistributed at will, then do not submit it here.
You are also promising us that you wrote this yourself, or copied it from a public domain or similar free resource.
Do not submit copyrighted work without permission!
To protect the wiki against automated edit spam, we kindly ask you to solve the following CAPTCHA:
Cancel
Editing help
(opens in new window)
Tools
What links here
Related changes
Special pages
Page information