This annual event, sponsored by the EHE Office of Research, Innovation and Collaboration (ORIC) at The Ohio State University, highlights the research of our faculty, research staff, postdocs, graduate, and undergraduate students. The full program can be found here.

Thursday, February 19 (date for all presentations)

8:00 a.m. - 9:00 a.m. EST 

Session Title: The Red-Blue Divide: Sociopolitical Influences on Faculty’s DEI Perspectives 

Presenters: Kara Graham and Dr. Emily Creamer 

Location: Barbie Tootie Meeting Room, Ohio Union 

Abstract: This study examines how faculty perspectives about diversity programming align with state political contexts. Using national data, findings reveal ideological divides between red- and blue-state faculty, with shared support for religious inclusion. Our findings underscore sociopolitical influences. 

10:00 a.m. - 11:00 a.m. EST 

Session Title: Bridging the Gap: Employer Perceptions of Postsecondary Preparation for STEM Careers in Clean Tech Manufacturing 

Location: Hays Cape Meeting Room, Ohio Union 

Presenters: Dr. Emily T. Creamer and Yun-Han Weng 

Abstract: As demand grows for a highly skilled clean-tech workforce, we use a descriptive-interpretive qualitative framework to examine employers' views on how well associate and bachelor’s STEM programs, as well as the NSF-funded Green Internship, prepare students for advanced battery and renewable energy careers. 

10:00 a.m. - 11:00 a.m. EST 

Session Title: Innovation for Whom? Cross-Group Validity of Innovation Capacity Measures for Graduate Students 
Location: Hays Cape Meeting Room, Ohio Union 

Presenter: Yun-Han Weng 

Abstract: This study presents early psychometric findings on whether the Innovation Capacities Scale validly measures innovation among international graduate students, using structural validity and invariance testing to evaluate whether the scale functions equivalently across groups.

10:00 a.m. - 11:00 a.m. EST 

Presenter: Anyi Ma and Warren Lor 

Session Title: Understanding the Role of AI in First-Generation Career Maturity: A Phenomenology Research on Graduate Students in Education 

Location: Tanya Rutner Meeting Room, Ohio Union 

Abstract: This phenomenological research explores how first-generation graduate students in education engage with AI to develop career maturity. It examines their lived experiences, reflections on employability and professional growth, and aims to inform equitable career counseling in the AI era. 

11:15 a.m. – 11:45 a.m. EST 

Poster Presentation Presenter: Hind Haddad 

Location: Cartoon Room 3rd Floor, Ohio Union 

Title: Religious Identity and Faculty Confidence in Addressing Sensitive Religious and Political Issues in the Classroom: A Foundation for Future Inquiry 

Abstract: This study examines whether demographic characteristics predict faculty confidence in addressing antisemitism, Islamophobia, and Israel-Palestine discussions in the classroom. Results show demographics do not significantly explain confidence, highlighting the need to explore other factors affecting preparedness 

1:15 p.m. - 2:15 p.m. EST 

Presenter: Anyi Ma 

Session Title: Boosting Career Maturity: The Impact of Interdisciplinary Hands-on Training on First-generation STEM Undergraduates 

Location: Suzanne M. Scharer Meeting Room, Ohio Union 

Abstract: Federal STEM investments promote hands-on, interdisciplinary training for emerging careers. First-generation college students (FGCS), over half of U.S. undergraduates, often face barriers to these opportunities. This phenomenological study examines FGCS engagement in such training and its influence on career maturity. 

1:15 p.m. - 2:15 p.m. EST 

Poster Presentation Presenter: Yun-Han Weng 

Session Title: Understanding Belonging in Community Colleges: An Analysis of Career Attitudes and Campus Engagement 

Location: Cartoon Room, 3rd Floor, Ohio Union 

Abstract: This study examines how career attitudes and campus engagement influence sense of belonging among community college students. Guided by Karp’s (2011) Community College Student Success Model, we use a structural equation model to assess measurement validity and estimate effects. Findings will clarify how motivation and engagement shape belonging.