Gesture during math instruction supports learning in children and adults. The mechanism by which gesture enhances learning across development is not known. One possibility is that instruction with gesture engages different cognitive abilities during learning than instruction without gesture. Our previous work showed a positive relationship between visuospatial working memory capacity and learning only when gesture was present, and a positive relationship between verbal working memory capacity and learning only when gesture was absent, suggesting that gesture may be processed using visuospatial working memory. The aim of the current experiment was to replicate and extend these prior findings with new instruction, random assignment to instructional condition, and improved measures of both learning and cognitive abilities. Participants observed video instruction in a novel mathematical system that either included speech and gesture or only speech. After instruction, participants completed a posttest to assess learning. Finally, participants completed tasks to assess verbal and visuospatial working memory capacity as well as fluid and crystallized intelligence. We found that gesture benefitted learning in adults. Contrary to previous findings, both learning with gesture and learning without gesture were supported by visuospatial working memory. These findings suggest that changing characteristics of instruction does not necessarily change the cognitive resources supporting learning in a novel math task.

Education research has shown that instructor gestures can help capture, maintain, and direct the student's attention during a lecture as well as enhance learning and retention. Traditional education research on instructor gestures relies on video stimuli, which are time consuming to produce, especially when gesture precision and consistency across conditions are strictly enforced. The proposed system allows users to efficiently create accurate and effective stimuli for complex studies on gesture, without the need for computer animation expertise or artist talent.

A beneficial effect of gesture on learning has been demonstrated in multiple domains, including mathematics, science, and foreign language vocabulary. However, because gesture is known to co-vary with other non-verbal behaviors, including eye gaze and prosody along with face, lip, and body movements, it is possible the beneficial effect of gesture is instead attributable to these other behaviors. We used a computer-generated animated pedagogical agent to control both verbal and non-verbal behavior. Children viewed lessons on mathematical equivalence in which an avatar either gestured or did not gesture, while eye gaze, head position, and lip movements remained identical across gesture conditions. Children who observed the gesturing avatar learned more, and they solved problems more quickly. Moreover, those children who learned were more likely to transfer and generalize their knowledge. These findings provide converging evidence that gesture facilitates math learning, and they reveal the potential for using technology to study non-verbal behavior in controlled experiments.

Students benefit from instruction with hand gestures when learning to solve mathematical equivalence problems. However, the mechanism by which gestures support student’s learning is unknown. One way that gestures may support student learning is by influencing students’ visual attention. To investigate this, we taught children how to solve mathematical equivalence problems using video instruction with or without gestures and used eye-tracking to observe how gestures influenced visual attention when solving problems after instruction. When compared to children taught without gestures, children taught using instruction with gestures had increased attention to the answer blank, but not to the numbers in the problem. Children’s visual attention to the blank also varied by problem features and whether children learned from the instruction. Attention to the answer blank may be an important characteristic of children’s equivalence problem solving, and observing gestures can influence children’s visual attention beyond the moment in which gestures are perceived.

We examined the effect of instructor gesture and distractorpresence on students’ encoding of slope and intercept ingraphs of linear functions. In Experiment 1, participantswatched an instructor avatar introduce a linear graph whileeither pointing to the intercept, tracing the over-and-upincrease for slope, or not gesturing (i.e., gaze only). They thenreconstructed the graph on paper. Participants weresignificantly more successful at encoding slope after watchingthe slope gesture than after watching no gesture. InExperiment 2, participants watched the avatar either point tothe intercept or trace the slope, each either in the presence orabsence of a visual distractor. Participants were significantlymore successful at encoding slope after watching the tracinggesture than after watching the pointing gesture. Distractorpresence did not affect performance. Taken together, theseresults suggest that teachers’ gestures promote students’encoding of relevant information and could help explain whyteachers’ gestures often benefit students’ learning.

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.