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Towards a Large Language Model-based Smart Learning Hub for Computing Education

Awarded
2641590Grant

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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This project, titled Towards a Large Language Model-based Smart Learning Hub for Computing Education, is an award-notice funded by the National Science Foundation through the Research on Innovative Technologies for Enhanced Learning program. The initiative focuses on leveraging Artificial Intelligence and Large Language Models to improve student engagement and persistence in college programming courses by providing timely, personalized feedback and customized pedagogical support. The research team will develop and deploy a Smart Learning Hub designed to assist students with tailored help, support instructors in material preparation and student monitoring, and enhance peer instruction and AI-assisted programming education. To promote further advancements in computing education, the project's outcomes will be shared in an open-source executable format. The project is managed by the Education Innovation and Translation Section, with Amy Baylor serving as the Program Officer.

General Info

NSF-funded project developing an AI-based Smart Learning Hub for college computing education.

Agency

National Science Foundation → Education Innovation & Translation Section

NAICS

541720 - Research and Development in the Social Sciences and Humanities

Place of Performance

Not specified

Set-Aside

NONE

Documents

0

No documents available

Documents will appear here when they are available.

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Timeline

PhaseAwarded
Posted

Award Notice

Awarded

Contract was awarded

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Organization & Contact Information

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AgencyNational Science Foundation → Education Innovation & Translation Section
Contacts1 person available
OfficeN/A
Organization / AgencyNational Science Foundation → Education Innovation & Translation Section
Office AddressN/A
Contacts
Amy BaylorProgram Officer
contact@example.gov
+1 (555) 000-0000

Full Description

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Research shows that effective personalized feedback helps students feel more engaged and persist in computer science. Furthermore, having access to help as soon as a student is confused can help both student engagement and learning. Artificial Intelligence (AI) and Large Language Models (LLMs) show promise toward providing customized help in a way that is accessible to students in a timely fashion. However, more research is needed about how to foster effective use of these new technologies in educational settings. This project investigates how LLM-based technology can help build effective pedagogical tools within the context of college programming classes. This project explores novel approaches for using AI and LLLMs in a pedagogical setting to: (1) provide customized help to students that is tailored to the class they are taking; (2) support instructors in material preparation, monitoring student engagement, and training teaching assistants; (3) augment existing pedagogical approaches, such as peer instruction; and (4) facilitate the education of AI-assisted programming. Towards these goals, the research team will create a Smart Learning Hub that interfaces with students, instructors, and teaching assistants in an integrated coordinated way, within the context of programming courses. The research team plans to deploy this Smart Learning Hub in real classroom settings and measure its pedagogical impacts. The research team plans to share the products of this project in an open-source executable format to facilitate further advancements in research and computing education. This project is funded by the Research on Innovative Technologies for Enhanced Learning (RITEL) program that supports early-stage exploratory research in emerging technologies for teaching and learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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