SBIR/STTR Research Award

SBIR Phase I: The Teacher Practice Feedback Tool- real-time information for teachers who want to measure and improve their talk time, wait time, and question-asking skills.

Award identifier a00a9c3a5a8d31d1de5d941af75e9baa7808e68418279520d6ab22f26f4c2539Awarding agency National Science Foundation

Award amount

$203,193

Program and phase

SBIR · Phase I

Award year

2016

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Earshot LLC
Proposal award date
2016-07-01
Contract end date
2016-12-31
UEI
KAAMHD1VPKF7
Solicitation number
Not reported
Topic code
EA

Research abstract

This SBIR Phase I project seeks to improve teaching by providing teachers with real-time, personalized feedback. Most teachers receive little regular, actionable feedback about their teaching to help them improve. Questions and discussions are the currency of great teachers, especially as teachers help students develop critical thinking, collaboration, communications and creativity skills, those skills in highest demand for careers in science, technology, engineering and math. This project is to design, develop, test and refine a mobile app that provides powerful, real-time instructional data for teachers at all grade levels and subject areas. Through the automatic analysis of questions and discussion, teachers will have access to useful data about communication in their classrooms to help them continuously improve instruction. This project is designed to help teachers incorporate more inquiry-based instruction methods into their teaching practice. Inquiry is a research-based approach to increasing student competencies. The intended outcomes for using this application are for teachers to talk less and ask more questions, to allow sufficient wait time before calling on students, and for teachers to incorporate more and higher-level questioning into their teaching. The technology can be sold to directly teachers at schools and universities throughout the United States on a subscription basis, enabling teachers to control their own data and decide how it is used, as well as ensuring that the tool is used for improvement, rather than for evaluative purposes. The technology being developed for this project builds upon recent advancements in natural language processing and voice analysis. This project uses machine learning and algorithms to develop a user-friendly app that analyzes teacher voice data around four key data points: talk time, wait time, question level (higher-order and lower-order questions based on a proprietary taxonomy), and question frequency. The objective of this project is to design, test and refine the first version of the app, to be used on an iPhone using an external microphone. Teachers representing various grade levels, subject areas, levels of experience, and voice characteristics will pilot this technology and provide feedback to inform development. This project will employ research methodologies such as pre and post surveys, observations, interviews, and think-aloud sessions, to inform usability and feasibility.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

2 SBIR/STTR records share this UEI (2016–2018). Reported award amounts total $428,193. Reported amounts are not federal obligations.

Phases: Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

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