The Waggle Math research evidence paper summarizes the research and theory supporting the instructional design of Waggle Math. Download the full Waggle Math Research Evidence Base paper to learn more about the program and instructional model, including how Waggle Math aligns with research regarding:
- improving student learning and outcomes through the effective incorporation of AI and machine learning to support personalized learning in classrooms; personalized learning through a continuous, adaptive digital learning system; purposeful, meaningful practice (effective distributed practice to support students’ long-term mastery and application of knowledge and skills); ongoing feedback to best support each student’s progress; and formative assessment to guide instruction;
- enhancing student learning experiences through fostering student persistence and productive struggle; positive effects of embedded gamification within instruction; boosting student engagement in digital learning environments; and how self-regulated learning models benefit students;
- supporting all learners through promoting equity, access, and rigor and supporting multilanguage learners in developing content knowledge and language skills in tandem; and
- supporting educators by facilitating classroom management, planning, and instruction and informing and optimizing data-driven instructional decision-making.