Undergraduate Research Symposium

Welcome to the 2023 CLAS Undergraduate Research Symposium!

College of Liberal Arts and Sciences students are invited to present their original research in the form of posters and papers. Faculty and graduate student judges will evaluate presentations and monetary awards will be given to top students. For the first time ever, participating students are invited to share their research here online to maximize exposure. Additional prizes will be awarded to select students who participate in this unique hybrid format. All students must be available for the in-person event.

When: Friday, April 14 from 10 a.m. to 12 noon

Where: STEM Innovation Learning Center (Room 0701)

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FAQS

  • What makes a good undergraduate research presentation?

    Look for clarity of ideas and how the big picture is explained. What is the problem to be addressed, or idea to be developed? The work should make the methods clear and discuss the results in a broader context.

  • What should attendees consider before voting?

    Look for the scientific structure: Problem ➡️ hypothesis or motivation ➡️ methods ➡️ results and discussion ➡️ conclusion. Some works in humanities have a more flexible structure and do not have a working hypothesis. The work should be consistent in its objectives and accomplishments. Notice that a hypothesis is "the best guess" on how to address an idea and sometimes the observed results differ from the hypothesis. This is not a problem and only indicates that new research is needed using a different hypothesis.

  • What questions should I ask about the research?

    Any question addressing the research structure is welcome. There are no "wrong" questions, and great discussion arises when the audience asks:
     

    • Is this problem important? 
    • Were you able to validate your hypothesis?
    • If not, what would make for a better hypothesis? 
    • Are there alternative methods to test and evaluate your research?
    • Would they be better, worse, why?
    • How do your results fit with other similar data?
    • What was learned?
    • Is this applicable?

Undergraduate research at Wayne State