Since the COVID-19 pandemic, the need for high-quality digital instructional materials has increased dramatically for K-12 educators. To address this need, the University of Washington College of Education is developing Colleague, an online lesson planning platform, thanks to a generous grant from the National Science Foundation Partnerships for Innovation.
Colleague (Collaborative Learning and Analytics for Global Education) is an online platform that uses education data and machine learning to empower K-12 teachers to plan for high-quality and inclusive lessons. “Colleague was designed with and for K-12 teachers and is powered by the latest developments in artificial intelligence and research on effective instruction,” said Dr. Min Sun, professor of Educational Foundations, Leadership & Policy at the UW College of Education and principal investigator for Colleague. “Colleague uses a combination of human experts and machine learning to vet the quality of digital instructional materials and builds a unique database to align them with rigorous learning standards.”
Colleague allows teachers to search, modify and save their lesson plans within a single platform and makes personalized lesson recommendations for teachers based on their subject, grade and student learning needs (e.g. language, disability, academic mastery levels and grade level knowledge). Colleague also allows teachers to create their own lesson plans by using its vetted database of high-quality instructional materials which include video, audio and text formats.
“We are creating a tool for teachers that supports them in transferring various information to improve classroom practices and student learning,” said Alex Liu, UW College of Education Ph.D. student in Education Policy, Organizations and Leadership. “Meanwhile, we are also building a framework for evaluating quality digital curriculums, offering actionable measurements for future studies.”
The platform also features a chat function in multiple languages that guides teachers through the lesson planning workflow with templates for different subjects and grades. Teachers enter their learning standards, objectives and a few keywords into the Colleague chat function and it will compose entire lesson plans. Teachers can then modify the lesson plans as needed. Using artificial intelligence, Colleague is designed to augment teachers’ work so that they can focus on tasks that have a higher yield for student learning, rather than lesson planning. The aim of the tool isn’t to replace teachers, but rather to empower teachers’ agency and work efficiency.
We're leveraging a lot of data-intensive approaches to build an experience that teachers will love.
“Our mission is to develop Colleague as a personal technological assistant for teachers to plan inclusive and high-quality lesson plans with great time efficiency,” said Dr. Sun. “K-12 teachers spend hours per day on gathering instructional materials and lesson plans, which often occurs during evenings, weekends and holidays.”
In a recent national survey by RAND, more than 90% of teachers reported using Google for finding their instructional materials, and 70% reported using social media. However, the quality of those digital instructional materials is not always guaranteed. This also presents an equity issue, because junior teachers and teachers who serve historically underserved student populations spend more time lesson planning because their students have a wider range of academic mastery levels, as well as more diverse language and cultural backgrounds. Colleague is designed to meet this market need and make access to high-quality digital instructional materials more equitable for all teachers.
“We're leveraging a lot of data-intensive approaches to build an experience that teachers will love,” said Lovenoor Aulck, data scientist in the UW Office of Planning and Budgeting. “Ultimately, we think this tool will help them sift through the mountain of information they're faced with when developing classroom resources and instead free them up to do what they do best - teach kids.”
With the help of the National Science Foundation Partnerships for Innovation grant, the multidisciplinary team behind Colleague conducted market research with over 500 teachers, school district leaders and policy makers nationwide to develop the initial prototype.
The demo version of Colleague is available now and broad user research will be conducted through the spring and summer of 2023, with the beta version of Colleague being released in the fall of 2023.
To learn more about Colleague, contact Dr. Min Sun at email@example.com.