Project Overview
Summary
Increasing enrollments in computer science (CS) courses lead to a low instructor-to-student ratio, especially for introductory CS courses, which often include non-CS majors who need to learn fundamental computing skills. In large courses, students are more likely to interact with the course Teaching Assistants (TAs) rather than the main instructor. Modern CS courses have a high cognitive load and require the students to use various complex tools. To succeed in CS courses, students must be independent, highly self-regulated learners (SRL) who can navigate multiple help resources.
This proposal builds upon previous work from the PIs, which investigated student interactions in office hours and online forums. We plan to extend this research to characterize the complex help resource landscape in CS courses, including both formal (TAs, office hours, online forums) and informal resources (peers, online resources, AI models). This research aims to provide a comprehensive understanding of the help resource landscape and develop strategies to enhance its effectiveness, particularly for underrepresented groups in CS. A key outcome of this research will be the design and implementation of an intervention to teach students how to navigate and use help resources effectively, with a focus on improving learning outcomes and retention in CS courses.
Prior Grants and Foundational Work
This project builds on a strong foundation of prior research, supported by the following grants:
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CUE: Collaborative Research on Effective Peer Teaching Across Computing Pathways
- NSF Award Numbers: NC State #1934975, Duke #1934965, UNC Chapel Hill #1935111, University of Florida #1935045
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Google Computer Science Capacity Award
- Research Triangle Peer Teaching Fellows: Scalable Evidence-Based Peer Teaching for Improving CS Capacity and Diversity
- Lead PIs: Jeff Forbes (Duke University), Ketan Mayer-Patel (UNC Chapel Hill), Kristy Boyer (University of Florida), Sarah Heckman (NC State)
- News Article
- Old Project Website
- Research Triangle Peer Teaching Fellows: Scalable Evidence-Based Peer Teaching for Improving CS Capacity and Diversity
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Related Award: Developing Integrated Teaching Platforms to Enhance Blended Learning in STEM
- PI: Collin Lynch, Co-PI: Sarah Heckman, Tiffany Barnes
- NSF Award Number: DUE-1821475.
These grants funded critical studies that investigated peer teaching and help-seeking interactions in large computing courses, with a focus on equitable student support. Insights from these projects directly inform the current research on help-seeking behaviors and strategies, allowing us to expand our understanding to a broader range of help-seeking resources and interventions.
Goals
- Characterize the help resource landscape, how and why students traverse it, and whether their help resource use is effective.
- Empower students to effectively use the help resource landscape for their learning.
Research Questions
- How do students use help resources in terms of the landscape, frequency, and order?
- Why do students use the help resources the way they did, and is it effective?
- Will our intervention help students be more effective when seeking help? Does explicitly teaching students about the help resource landscape and having them plan how they will seek help influence student outcomes?
Methods
- Quantitative analysis of help resource usage and patterns.
- Qualitative interviews with students and TAs to understand help-seeking behaviors.
- Designing an intervention to teach students effective help-seeking strategies.
Motivation & Impact
The increasing demand for undergraduate computing programs necessitates adequate support for students to learn and complete assignments. As class sizes grow, scalable support mechanisms like near-peers, synchronous office hours, and asynchronous discussion forums are commonly used. However, little is known about how these resources impact student proficiency, help-seeking behavior, affective states, and retention. Most help-seeking interactions are expedient, addressing immediate assignment completion but not fundamental knowledge gaps. This research seeks to improve help-seeking strategies, particularly for underrepresented students, to enhance their learning outcomes and retention in computing classes.
Research Context
This research is a collaborative effort between PIs from NC State University and Duke University. These institutions provide a comprehensive and supportive infrastructure for exploring help-seeking behaviors in computer science education, focusing on the experiences of underrepresented groups. The combined resources, diverse student populations, and commitment to inclusive education create a robust context for this research, aiming to improve help-seeking strategies and support systems for all students.
NC State University
NC State University, located in Raleigh, North Carolina, is a public land-grant research institution that is part of the University of North Carolina system. The Department of Computer Science is housed within the College of Engineering and offers a Bachelor of Science in Computer Science (BSCS) degree. NC State is known for its strong emphasis on engineering and technology, providing a robust infrastructure for research and education. Research at NC State is supported by various facilities such as conference rooms, modern libraries, and classrooms equipped with advanced media presentation tools. This environment supports extensive research activities and collaboration among students and faculty.
Key aspects of NC State’s environment include:
- A diverse student body with 14% from rural areas and 19.5% receiving Pell Grants, indicating financial need.
- Comprehensive computing services, including access to high-end computing resources, the North Carolina Supercomputing Center, and extensive networking capabilities.
- A focus on undergraduate and graduate support, with faculty and graduate assistants having access to a range of hardware and software tools for research and teaching.
Duke University
Duke University, a private research university located in Durham, North Carolina, is renowned for its rigorous academic programs and research initiatives. The Department of Computer Science is part of the College of Arts and Sciences, offering both Bachelor of Arts in Computer Science (BACS) and Bachelor of Science in Computer Science (BSCS) degrees. Duke’s approach to computer science education integrates computing with other fields, promoting interdisciplinary learning. Duke provides a supportive environment for both students and faculty, with extensive resources for teaching, research, and student support, including initiatives to enhance cultural competence and inclusivity in the field of computer science.
Key features of Duke’s environment include:
- A significant proportion of first-generation college students, with 20% coming from economically disadvantaged backgrounds.
- A diverse student population, with efforts to support first-generation and low-income scholars through programs and initiatives.
- Strong emphasis on cultural competence and inclusive teaching practices, with faculty involved in initiatives like the Cultural Competence in Computing (3C) Fellows program to foster more inclusive computing environments.