SBIR-STTR Award

Using Algorithmic Understanding of Student Comprehension of Computer Science Concepts to Support Teacherswith Personalized Student Recommendations
Award last edited on: 10/28/2024

Sponsored Program
SBIR
Awarding Agency
DoEd
Total Award Amount
$1,250,000
Award Phase
2
Solicitation Topic Code
91990022R0001
Principal Investigator
Vishal Goenka

Company Information

2sigma School Inc

1227 Doyle Circle
Santa Clara, CA 95054
   (650) 284-9898
   N/A
   www.2sigma.school
Location: Single
Congr. District: 17
County: Santa Clara

Phase I

Contract Number: 91990022C0035
Start Date: 5/16/2022    Completed: 1/16/2023
Phase I year
2022
Phase I Amount
$250,000
In a previous project, the company developed, and pilot tested a high school-level computer science intervention for remote teaching and learning with live and pre-recorded lectures describing hands-on activities and online exercises. The project team will develop a prototype of a Machine Learning dashboard to track student learning progressions in computer science and generate fine-grained pedagogical recommendations that educators can use to inform practice. At the end of Phase I, the project team will conduct a pilot study with four educators and 250 high school students to test if the prototype functions as intended, and if the machine learning component generates information that educators find useful for providing individualized information about how students are learning.

Phase II

Contract Number: 91990023C0035
Start Date: 7/17/2023    Completed: 7/17/2025
Phase II year
2023
Phase II Amount
$1,000,000
___(NOTE: Note: no official Abstract exists of this Phase II projects. Abstract is modified by idi from relevant Phase I data. The specific Phase II work statement and objectives may differ)___ In a previous project, the company developed, and pilot tested a high school-level computer science intervention for remote teaching and learning with live and pre-recorded lectures describing hands-on activities and online exercises. The project team will develop a prototype of a Machine Learning dashboard to track student learning progressions in computer science and generate fine-grained pedagogical recommendations that educators can use to inform practice. At the end of Phase I, the project team will conduct a pilot study with four educators and 250 high school students to test if the prototype functions as intended, and if the machine learning component generates information that educators find useful for providing individualized information about how students are learning.