ETQ-AI

Even though the quality of teaching is a key determinant of effective learning, getting timely, reliable feedback about one's teaching quality remains a significant challenge. Traditional methods (student evaluations, teacher self-assessments, classroom observations etc.) have limitations in predictive validity, are time-intensive and costly and lack the actionable depth needed to foster meaningful, ongoing professional growth. This gap prevents teachers from reflecting on and adapting their daily work practices if they strive for educational excellence.
 

Real-time, formative feedback on teaching practices: We aim to develop an AI-based copilot application called Teaching Copilot that teachers can use on their smartphones to self-assess the quality of their teaching. Teachers can record classroom audio using their smartphones, and the system analyzes this data (audio and transcripts) to predict teaching quality aspects such as instructional organization, cognitive stimulation, or encouragement and warmth. Teaching Copilot will be a self-assessment tool empowering teachers to self-reflect. The system adheres to GDPR and EU AI Act regulations and privacy-preserving machine learning (ML) to ensure secure, ethical data handling. This innovation will enhance teaching effectiveness, enrich student learning experiences, and promote a culture of professional growth.