GrayUR Undergraduate Research for Credit - Natural Language Processing
Natural Language Processing
Project Overview
Natural language processing (NLP) techniques can use machine learning to process large amounts of free response data into more easily digestible information, enabling researchers to rapidly collect meaningful feedback on services, processes, pedagogy and more. There exist many open-source packages written for multiple platforms that can be collected and integrated to serve a specific feedback purpose. The purpose of this research effort is to develop an integrated system that can support research in an academic environment to enable instructors or researchers to to collect and process large amounts of free-response written or transcribed data to inform and improve educational practices.
Objectives
- Benchmark Current System Architecture and Function
- Determine User Requirements
- Revise Existing NLP System
- Develop a ‘Best-Practices’ Document
Major Tasks
The major tasks of the project are outlined below. These are nominal and are likely to change somewhat throughout the course of the year. These are meant to illustrate the general nature of the work that the position entails.
- Project Management
- Benchmark Current System
- Survey or Interview Faculty
- Process Faculty Preferences into Design Requirements
- Design Beta System
- Develop and Implement Beta System
- Beta System Validation
- Documentation
General Responsibilities of the Group
Students participating in the GrayUR undergraduate research group will register for an ENGE 2994 or ENGE 4994 undergraduate research course. Typically, students enroll for a 1 credit-hour course load. Under certain circumstances, we can look at extending this up to as many as 3 credits per semester and can sometimes explore technical elective credit within your major. Though not required, the expectation is that you will continue on with the team for two semesters, though we will examine the relationship at the end of the fall semester.
In addition to the major technical tasks listed above, all members of the GrayUR undergraduate research team should expect
- To devote ~3 hours/week to research for each credit hour
- To attend a biweekly team meeting with Dr. Gray
- To attend a monthly all-hands meeting with Dr. Gray
- To participate in periodic reporting (symposia, research poster sessions, etc.)
Major Deliverables
All student teams will have the following deliverables
- One progress presentation to the entire GrayUR group each semester
- Final project reporting
- Final report
- Final slides
- Final personal reflection
Open Positions
Specific Role(s)
- Team lead
- Software designers
Preferred Majors
- CS
- CpE
- EE
- CMDA
- Education
Preferred Academic Years
Looking for First-year/Sophomore/Junior level students
Preferred Skills and Interests
- machine learning
- coding
- AI
- Teaching
- Pedagogy
- software design
How to Apply
Applications will be reviewed by Dr. Gray and by continuing researchers on the team. After a review of the application, our team will contact candidates to schedule an interview (likely to be conducted via zoom). Review for the positions will begin on Bastille Day, 2022, and will continue until all positions are filled. Please send an email to Dr. David Gray (dagray3@vt.edu) with the following deliverables;
- A brief (~1 page) essay or cover letter explaining which of the projects you are interested in, and why you think you might be a good fit for that project (or those projects). If you are applying for multiple projects, extend your essay a little and describe your interest and qualifications for each position. Be sure to let us know your major and where you are in your academic career (sophomore, junior, etc.)
- A resume outlining your work experience and education
Please reach out if you have any questions or concerns.
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