AI-driven Infrastructure for Student Audio Response Collection, Transcription, and Analysis

Brief Description

AI infrastructure that collects, transcribes, and analyzes student audio responses to deliver actionable insights on learning experiences.

Full Description

Large Language Model (LLM)-powered infrastructure that collects, transcribes, analyzes, and visualizes student audio responses. Includes unique data collection protocols, large datasets of student responses, customized AI prompts designed to extract key learning indicators and skills, and interface designs that will help educators interpret student learning experience indicators effectively.

Suggested uses

• K-12 and higher education institutions enhancing student assessment processes 
• Educators and researchers analyzing student learning and skill development 
• EdTech companies integrating AI-driven analytics into their platforms 
• Policy makers measuring and improving students' 21st-century skill acquisition

Advantages

• Automated transcription and data collection of student voice responses using specialized protocols 
• Nuanced LLM-powered analysis of student skills and competencies beyond basic sentiment analysis 
• Comprehensive data dashboards providing educators with intuitive visualizations and actionable insights