Principal Investigator: Ryan Baker
CoPrincipal Investigator(s):
Organization: Teachers College, Columbia University
Abstract:
The project researches persistence in mathematics learning in a computer-based learning environment (CBLE). The research investigates how a CBLE can provide the supportive help and promote the self-regulatory strategies necessary for students to be not just persistent, but productively persistent math learners. The project will focus on the middle school years, an important and vulnerable point in the school trajectory, as mathematical concepts become increasingly difficult and abstract in the transition from arithmetic to algebra. Persistence is critical in CBLEs. Research shows has shown that changing student academic mindsets can have strong benefits for their persistence and achievement. Sustained effort is important but not always sufficient for learning and less attention has been paid to the downside of perseverance, called wheel-spinning, the time that struggling learners spend without making progress. The project will build instrumentation, theory, and intervention strategies to address the needs of struggling math students. For technology designers, the project will distill findings to develop research-based design principles for CBLEs. For educators, the project will translate findings into pedagogical approaches that can be used to enhance teacher practice.
The research is designed to address three goals: (1) Develop automated detectors that can differentiate between wheel-spinning and productive persistence in real time; (2) Investigate student, teacher, and system factors that predict wheel-spinning and productive persistence; and (3) To design and test interventions to reduce wheel-spinning and promote productive persistence. The project will use detailed log data from thousands students who use an existing computer-based mathematics program. Learning analytic methods now provide the means to identify and study micro-level student behavioral engagement patterns. The project will use complementary data analytic, correlational, think-aloud, and experimental methods to examine productive persistence and its understudied yet common counterpart, unproductive persistence. The research will advance the state of the art in data mining-based measurement to provide instrumentation that can be used to enhance learning; extend empirical findings about the cognitive and self-regulatory processes that enable productive persistence in math learning; and extend the empirical base informing what supports in CBLEs or teacher practice are necessary for productive persistence. The project, supported through the EHR Core Research (ECR) program of fundamental research in STEM, will contribute important research findings regarding STEM learning and learning environments, which are important priorities of the ECR program.
