Welcome to M-Powering Teachers!
Our central goal is to design tools and experiences that maximize impact on teaching and learning, especially for historically marginalized student populations.
Our team, a group of scholars with expertise in education, linguistics, economics, and computer science, designed a machine learning-based feedback tool called M-Powering Teachers (M stands for machine). This tool utilizes natural language processing to analyze verbal classroom interactions and subsequently provides formative feedback to teachers.
Our Mission
Why AI-Powered Feedback
The field of education is facing an urgent need to facilitate the effective integration of AI technologies into schools where their benefits can be maximized while reducing the burden on teachers’ time—before burn-out or ineffective use of technology aggravates teacher turnover, widens achievement gaps, and creates missed opportunities. Recent studies inform how we can use AI tools to provide feedback to teachers to improve their instruction. For example, Guskey & Link (2022) note that teachers desire personalized, non-judgmental, consistent feedback to help them improve; AI tools can help provide such feedback in a way that is cost-effective and scalable. Recent research from our team highlights that AI-powered feedback tools for teachers have demonstrated success in improving instruction and student outcomes in online learning environments (Demszky et al., 2023; Demszky & Liu, 2023).
Additionally, instructional coaching is widely regarded as one of the most promising forms of professional development (Kraft et al., 2018). However, few educators receive such effective feedback on a regular basis. This is because generating formative feedback tends to be resource-intensive (Kraft & Gilmour, 2016), limiting the number of teachers an individual coach may serve. Coaches also face challenges engaging teachers who are reluctant to deprivatize their practice, limiting their reach in many schools. Frequently, coaches are assigned more teachers than they can reach on a regular basis and as a result, they typically engage in a very limited number of coaching cycles with any one teacher. Embedding AI feedback in teacher coaching can solve these complementary challenges and enhance the effectiveness of teacher professional learning. Given that teachers are the single most influential school-based factor in student success, the M-Powering Teachers tool brings the potential to greatly reduce inequities by improving instructional quality.
