This report shows the various collaborative projects between UNO and the community. Various filters are provided to gain a better understanding of how different UNO units collaborate with the community.
| Project | Project Focus Areas | Community Partners | Campus Partners | Engagement Type: | Activity Type: | Other Activity Type: | Start Semester: | Start Academic Year: | End Semester: | End Academic Year: | Total UNO Students: | UNO Students Hours: | UNO Faculty/Staff Hours: | Total K-12 Students: | K-12 Student Hours: | Total Number of Other Participants: | Topics: | Other Topics: | Description: | Subtags: |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SAC Museum Group Project (Fall 2023): 2023-24 (3195) | Service Learning | None | None | Fall | 2023-24 | None | 62 | 1,674 | 0 | 0 | 0 | 0 | In teams, students will design an Instagram fan page, create 11 posts, analyze their performance, suggest 5 influencers, and present their strategy and post-performance to the client at the end of the semester. Traditional MKT 3370.001 | |||||||
| Social Media Campaign Project (Spring 2024): 2023-24 (3251) | Educational Support | Strategic Air Command & Aerospace Museum | Business, Service Learning Academy (SLA) | Service Learning | None | None | Spring | 2023-24 | None | 23 | 368 | 0 | 0 | 0 | 0 | UNO students work in groups to enhance a real-world company's brand through social media presence. The students make strategic posts on a social media platform throughout the semester, and analyze the post-performance data. At the end of the project, the students present their work, providing an analysis of how effective their various post strategies were. MKT 3370.001 Traditional | ||||
| DATA ANALYSIS FROM SCRATCH (Fall 2022): 2022-23 (3311) | Educational Support | Strategic Air Command & Aerospace Museum | Business | Service Learning | None | None | Fall | 2022-23 | None | 11 | 179 | 0 | 0 | 0 | 0 | Econometrics is routinely taught as an application class using a 'black box' like Stata or SAS to perform calculations. This class takes a different approach. Using the Python programming language, we build all estimators from scratch. Additionally, we introduce numerous non-parametric and simulation techniques. This approach to econometrics results in a stronger understanding of statistical assumptions and methods, a better understanding of when a method is appropriate, and stronger programming techniques. Furthermore, a deeper understanding of the underlying mechanics provides the student the ability to program custom procedures not already built into popular software packages. As part of the course, students will work with a community partner to answer a real question with data; MBA students should consult with their advisor about this course satisfying the project-focused capstone requirement. ECON 8330.001 |