From Awareness to Application: Strengthening Recruitment for NSF S-STEM Scholarships in Computer Science

2026-02-24

AI Summary

This study addresses the persistent challenge in computer science of low application rates and high perceived barriers among high-achieving students applying for the NSF S-STEM scholarship. To enhance recruitment, the authors designed and implemented a multi-channel targeted outreach strategy comprising informational sessions, early engagement initiatives, and departmental email communications. Employing a mixed-methods approach—including surveys, application data tracking, and qualitative interviews—the study systematically evaluated the influence of each channel on student decision-making. Innovatively linking recruitment sources to application pathways, the findings reveal that early communication, clear eligibility criteria, and streamlined processes significantly increased participation. Informational sessions and departmental emails emerged as the most effective channels, substantially boosting application rates among eligible students and offering a replicable, evidence-based recruitment framework for similar programs.

Technology Category

• Search and Optimization: Applications
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Applications

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: User modeling for targeted and personalized online advertising
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

Recruiting academically strong students into NSF S-STEM scholarship programs remains a persistent challenge in computer science education. This paper presents the design and initial implementation of a suite of targeted recruitment strategies for our NSF-funded project. Our recruitment strategy leverages multiple channels. Information sessions and early outreach efforts were employed to increase awareness and reduce perceived barriers to applying. Data from our recruitment includes applicant demographics, academic performance, financial aid profiles, recruitment source tracking, and survey responses on students awareness and decision-making processes. These data provide a foundation for evaluating the reach and effectiveness of various recruitment strategies and identifying factors that influence student application decisions. Quantitative and qualitative research approaches are employed to examine the implementation and outcomes of proactive recruitment strategies. Our preliminary analysis indicates that direct information sessions and departmental emails are effective recruitment strategies, accounting for a large portion of eligible applications. Our findings emphasize the importance of early communication about the program, clearly defined eligibility criteria, and a streamlined application process. By sharing ongoing progress and lessons learned from our project, this paper contributes evidence-based insights into recruitment practices and offers strategies that can be adapted by other institutions implementing NSF S-STEM programs.

Problem

• NSF S-STEM
• recruitment
• computer science education
• scholarship programs
• student recruitment

Innovation

• targeted recruitment
• data-driven evaluation
• NSF S-STEM
• student decision-making
• evidence-based practices