Collaborative Research: CueLearn: Enhancing Social Problem Solving through Intelligent Support

Information

  • NSF Award
  • 2300828
Owner
  • Award Id
    2300828
  • Award Effective Date
    8/1/2023 - 11 months ago
  • Award Expiration Date
    7/31/2027 - 3 years from now
  • Award Amount
    $ 194,616.00
  • Award Instrument
    Continuing Grant

Collaborative Research: CueLearn: Enhancing Social Problem Solving through Intelligent Support

The goal of this project is to develop CueLearn, an educational web application that will foster effective peer collaborations to improve mathematical problem solving amongst middle school students. Research suggests that learning is often better and longer lasting when students engage in well-scaffolded, shared, and collaborative learning experiences. However, educational technologies do not often leverage this research, with the focus most often being on the individual rather than a group. The CueLearn project will thus develop, test, and implement two intelligent strategies to improve students' collaborative problem solving: 1) facilitating effective student collaborations through the creation of effective peer groups within CueLearn, and 2) using real-time supports to increase student engagement and help students persist productively. The project's key aim is to design a system that will easily facilitate quality peer collaboration for all students, while also supporting teachers in their use of technology for collaborative work.<br/><br/>The project focuses on social learning experiences by automatically assigning students to work with optimized peer groups. Multiple grouping strategies will be tested through a series of observational studies and experiments to identify which grouping strategy works best. For example, students may be grouped based on their intended problem-solving strategy, so that students will be exposed to diverse approaches from peers who are using different strategies. However, intelligent student grouping methods may not be effective for learning by themselves, unless students are also provided with additional support during problem solving. Machine learning approaches will therefore be used to monitor engagement and detect unproductive forms of persistence in real-time in order to provide in-the-moment support as needed. Critically, these supports will be co-designed with students. Automated ideal grouping combined with just-in-time supports are hypothesized to improve students' problem solving performance and mathematical beliefs. Through all of these design innovations, the project aims to provide a new and effective educational technology for students and teachers.<br/><br/>The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.<br/><br/>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.

  • Program Officer
    Eric Knutheknuth@nsf.gov7032920000
  • Min Amd Letter Date
    6/30/2023 - 12 months ago
  • Max Amd Letter Date
    6/30/2023 - 12 months ago
  • ARRA Amount

Institutions

  • Name
    Georgia Southern University Research and Service Foundation, Inc
  • City
    STATESBORO
  • State
    GA
  • Country
    United States
  • Address
    261 FOREST DR
  • Postal Code
    304586724
  • Phone Number
    9124785465

Investigators

  • First Name
    Sam
  • Last Name
    Rhodes
  • Email Address
    srhodes@georgiasouthern.edu
  • Start Date
    6/30/2023 12:00:00 AM
  • First Name
    Antonio
  • Last Name
    Gutierrez
  • Email Address
    agutierrez@georgiasouthern.edu
  • Start Date
    6/30/2023 12:00:00 AM

Program Element

  • Text
    ITEST-Inov Tech Exp Stu & Teac
  • Code
    7227
  • Text
    Discovery Research K-12
  • Code
    7645

Program Reference

  • Text
    AI-Supported Learning
  • Text
    STEM Learning & Learning Environments
  • Code
    8817