Purpose: Traditional approaches to teaching and learning STEM use a conventional one–size fits-all delivery model where students are taught the same content at the same pace at identical challenge levels. In prior research and development, the team developed a beta version SciQuiry, an Artificial Intelligence-based website for students to learn science by writing questions about real-world STEM questions and receiving formative feedback as they progress. The purpose of this project is to develop a new prototype that will be added to the existing version of SciQuiry to strengthen its capacity to personalized student learning trajectories toward mastery of different topics in STEM.

Project Activities: In this project, the research team will develop a new prototype that integrates text-to-speech technology for greater accessibility, and a prototype dashboard for educators to generate question types for accurate assessment and to support implementation as a classroom STEM intervention. At the end of Phase I, the team will carry out a pilot study with 20 educators and 350 middle school students. The researchers will examine if the prototype functions as intended, if educators can use the dashboard to track student progress, and if student gain content knowledge on specific STEM topics.

Company Website: http://sciquiry.com/