%ANagashima, T.%ABartel, A.%ATseng, S.%AVest, N.%ASilla, E.%AAlibali, M.%AAleven, V.%AFitch, T. Ed.%ALamm, C. Ed.%ALeder, H. Ed.%ATeßmar-Raible, K. Ed.%D2021%I %K %MOSTI ID: 10328976 %PMedium: X %TScaffolded self-explanation with visual representations promotes efficient learning in early algebra. %XAlthough visual representations are generally beneficial for learners, past research also suggests that often only a subset of learners benefits from visual representations. In this work, we designed and evaluated anticipatory diagrammatic self-explanation, a novel form of instructional scaffolding in which visual representations are used to guide learners’ inference generation as they solve algebra problems in an Intelligent Tutoring System. We conducted a classroom experiment with 84 students in grades 5-8 in the US to investigate the effectiveness of anticipatory diagrammatic self-explanation on algebra performance and learning. The results show that anticipatory diagrammatic self-explanation benefits learners on problem-solving performance and the acquisition of formal problem-solving strategies. These effects mostly did not depend on students’ prior knowledge. We analyze and discuss how performance with the visual representation may have influenced the enhanced problem-solving performance. Country unknown/Code not availablehttps://doi.org/https://doi.org/10.31219/osf.io/sbwfjOSTI-MSA