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Bridging Gaps in STEM: An Evaluation of a STEM Intervention Program and its Impact on Degree Attainment and Career Pathways for Low-Income Undergraduate Students
No full textPersistent disparities in Science, Technology, Engineering, and Mathematics (STEM) degree completion and career attainment continue to disadvantage students from low-income, firstgeneration, and underrepresented racial and ethnic backgrounds, despite sustained national efforts to diversify the STEM workforce. STEM Intervention Programs (SIPs) have emerged as promising strategies to address these inequities, yet limitations in SIP evaluation literature including the lack of comparison groups, limited longitudinal data, and minimal attention to psychosocial outcomes impede our understanding of their long-term impact. This dissertation uses a mixed-methods, three-project design to evaluate the Strategic Undergraduate STEM Talent Acceleration INitiative (SUSTAIN), a comprehensive SIP at a private, Predominantly White Institution (PWI) in the northeastern United States, serving high-achieving, low-income STEM undergraduates. Project 1 uses institutional data to assess academic disparities in STEM prior to and after SUSTAIN implementation. Part one this project (Chapter 1) establishes a baseline by comparing GPA and STEM graduation outcomes by income status among pre-SIP cohorts (2014–2016). Results indicated no statistically significant difference in GPA or six-year graduation rates between groups, but low-income students were significantly more likely to require more than four years to complete their degree. Part two of Project 1 (Chapter 2) evaluates outcomes for the first SUSTAIN cohort (2017) relative to matched low- and high-income peers, using regression analyses to assess effects on GPA, time to degree, and STEM graduation rates. SUSTAIN participants had comparable graduation rates and GPA to their higher-income peers and outperformed their lowincome peers, especially in terms of time-to-degree completion. Project 2 (Chapter 3) investigates changes in “identity as a scientist” during the first year of college, comparing SUSTAIN participants to STEM peers using a two-way mixed ANOVA. Results reveal that SIP participants began college with higher identity scores that remained stable over time, while comparison students demonstrated significant gains, suggesting the program buffered against potential identity decline. Project 3 (Chapter 4) explores career outcomes for the original SUSTAIN cohort using a convergent mixed-methods design. Follow-up surveys and in-depth interviews conducted 3–5 years post-graduation revealed that participants’ STEM trajectories were shaped by structural barriers, mentoring and support networks, evolving interests, and personal growth in science identity and self-efficacy. Together, these three projects provide a multidimensional evaluation of an SIP’s impact on both academic and psychosocial outcomes, including STEM degree attainment, identity development, and career pathways. The findings inform more equitable program design and policy recommendations, including the need to reconsider merit-based eligibility and expand definitions of STEM success beyond degree completion to include translational, interdisciplinary, and policy-related careers
Source attribution and detection strategies for AI-era journalism
No full textContinued access to genuine, verified news is important in providing news audiences with information about events of social importance. Sophisticated methods of detection and attribution must be applied to counter the proliferation of AI-generated mis- and disinformation and uphold journalistic values. This study examines the complexities of transparency in journalism and AI in relation to source attribution. While various AI analytics claim performance capabilities on specific tasks related to media detection, there remains a need for a standard evaluative framework that can comparatively measure the success of these various analytics. This paper explores how the Theory of Content Consistency (ToCC) can be leveraged as a framework to facilitate validation of AI analytics attempting to detect misattributed and manipulated media
Social Media Semantics: Enhancing Manipulated Media detection Through An Artificial Intelligence Weakness
No full textAs fake news and disinformation continue to proliferate in digital journalism, the development of artificial intelligence (AI) analytics to identify synthetic content inconsistencies is increasingly important. This study explores trained AI analytics’ struggle to detect semantic gaps within AI-generated media. Findings reinforce human semantic capabilities and a direction for detection tools. AI analytics designed for semantic detection-related tasks are evaluated through the application of the Theory of Content Consistency, with insights for combatting social media news truth erosion
Addressing the Racial Wealth Gap -- Event Information
No full textA press release for the Addressing the Racial Wealth Gap event
Interrogating the Racial Wealth Gap: Thinking Locally -- Event Program
No full textA pamphlet for the Interrogating the Racial Wealth Gap: Thinking Locally event
“The Lender Conversation: Interrogating the Racial Wealth Gap” -- Event Information
No full textA press release for the “The Lender Conversation: Interrogating the Racial Wealth Gap” event
Be Seriously Scared! A Shot Across the Bow Toward Nuclear Disarmament
No full textA save-the-date poster for a lecture on the future of nuclear disarmament
Veterans, Did You Know? Children of Veterans May Be Eligible for Education Benefits
No full textA five-minute video on the educational benefits that the children of veterans may utilize
Veterans, Did You Know?The Military is Required to Offer Financial LiteracyTraining to Service Members
No full textA five-and-a-half minute video on the financial literacy training the United States Military is required to provide to veterans
Veterans, Did You Know?You or Your Surviving Spouse May Be Eligible for Aid and Attendant Benefits When You Need Consistent Elderly Care
No full textA three-and-a-half minute video on elderly care options for veterans