Guiding Understanding via Information from Digital Environments (GUIDE)

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The Discovery Research K-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools (RMTs). Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. 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, and it will be tested in both introductory biology courses and advanced courses. The tool will be designed to analyze student progress within the digital curriculum and provide feedback to both students and teachers about challenges to learning as they are occurring. The system will simultaneously monitor and analyze the learning patterns of all students in a class, providing targeted feedback to individual students as needed, or enabling the teacher to make informed decisions about when some students need individual attention, or groups of students need help with a particular concept or learning challenge. As more digital learning experiences are incorporated into classroom practices, digital guidance systems such as this will be needed to help students and teachers effectively blend a variety of classroom learning experiences. This design and development study focuses on improving student learning of domain-specific content and practices within traditional, technology-enriched classroom environments. The project will be guided by findings from prior research in two areas: the learning outcomes of game-like, simulation-based digital learning environments, and the effectiveness of intelligent tutoring systems. The system being developed in this project will construct analytic models of student knowledge and behavior from clickstream data and provide contextualized information at optimal junctures to students or teachers. This approach will enable a three-layered response system: a) direct, targeted support to individual students struggling with basic content; b) referral of a student to another student or group of students having encountered similar learning challenges; and c) feedback to teachers that would facilitate strategic guidance of student learning. Research questions guiding this project will focus on what information about student learning is most useful for guiding learning in digital environments, how can this information improve support for student learning within classrooms, and how does the availability and use of this information improve student knowledge and practices? The design and development work will be conducted over 4 years and will involve teachers and students in 22 classrooms in New England and North Carolina.