Rewriting Math Word Problems To Improve Learning Outcomes For Emerging Readers: A Randomized Field Trial In Carnegie Learning's Mathia

We present a randomized field trial delivered in Carnegie Learning’s MATHia’s intelligent tutoring system to 12,374 learners intended to test whether rewriting content in “word problems” improves student mathematics performance within this content, especially among students who are emerging as English language readers. In addition to describing facets of word problems targeted for rewriting and the design of the experiment, we present an artificial intelligence-driven approach to evaluating the effectiveness of the rewrite intervention for emerging readers. Data about students’ reading ability is generally neither collected nor available to MATHia’s developers. Instead, we rely on a recently developed neural network predictive model that infers whether students will likely be in this target sub-population. We present the results of the intervention on a variety of performance metrics in MATHia and compare performance of the intervention group to the entire user base of MATHia, as well as by comparing likely emerging readers to those who are not inferred to be emerging readers. We conclude with areas for future work using more comprehensive models of learners. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.