Navigated Learning: Differentiated Classroom Instruction Built on Learning Science and Data Science Foundations

• In Event: Learning Analytics Tools to Improve Instruction

Abstract

Classroom teachers are often provided with instructional resources and assessment systems that dictate one pathway for every student’s learning and evaluation. These practices are common despite new affordances available through data-rich, emerging digital technologies that draw on data science and learning science foundations to complement and enhance traditional instruction. This paper presents a conceptual framework for Navigated Learning, a pedagogical approach that operationalizes learning principles using artificial intelligence and data science resulting in the continuous, real-time generation of students’ data to support a teacher’s ability to customize instruction. The paper concludes with two empirical case studies of implementation within fifth and ninth grade mathematics classrooms.

Authors

• Nancy Butler Songer, University of Utah

• Michelle Newstadt, Gooru

• Prasad Ram, Gooru