The project will provide the opportunity for upper elementary students to learn computer science and build strong collaboration practices. Leveraging the promise of virtual learning companions, the project will collect datasets of collaborative learning for computer science in diverse upper elementary school classrooms; design, develop, and iteratively refine its intelligent virtual learning companions; and generate research findings and evidence about how children collaborate in computer science learning and how best to support their collaboration with intelligent virtual learning companions.
This project will develop and test a digital monitoring tool that will enable teachers to track student learning within a digital learning system and quickly adjust classroom instructional strategies to facilitate learning. The tool will be developed for use with an existing digital curriculum for high school genetics.
This project enhances elementary students' engagement in and learning of science through visual communication skills using student-generated graphics in science notebooks. The products include two professional development modules for each grade level 2–5 that explicitly teach specific forms of graphical representation used in science, how these representations complement written and numeric information, and how teachers can promote the thoughtful reflection and discussion of these representations in small-group and whole-class settings.
The project designs and implements technologies that combine artificial intelligence in the form of intelligent tutoring systems with multimedia interfaces (i.e., an electronic science notebook and virtual labs) to support children in grades 4-5 learning science. The students use LEONARDO's intelligent virtual science notebooks to create and experiment with interactive models of physical phenomena.