Faculty Advisor or Committee Member

Neil Heffernan, Department Head

Faculty Advisor or Committee Member

Erin Ottmar, Advisor

Faculty Advisor or Committee Member

Ivon Arroyo, Reader




This thesis intends to advance educational research by providing exploratory insights about the roles of, and relationships between, the actions, language, and gestures of college and elementary-aged students surrounding measurement estimation. To the best of my knowledge, prior research has examined the role of speech and gestures as they relate to areas of mathematics such as algebra and geometry, however, this work has not been extended to the area of measurement. Similarly, language and gesture have been explored but the three-way interplay between actions during problem-solving, and the language and gestures observed during explanations after problem solving has not been investigated in mathematics. To actualize the findings from this research in practice, this thesis uses the findings from two studies on behavior during measurement tasks to propose text and image support for an elementary-aged measurement game, EstimateIT!, to support students as they practice how to measure objects and develop conceptual skills through embodied game play. Specifically, this thesis intends to provide 1) a synthesis of the work on gestures in mathematics as well as the research methods used to study gestures, 2) a coding guide to analyze the gestures of mathematics learners, as well as their actions and language, 3) an application of the coding guide to explore the behavior of college and elementary students during measurement estimation tasks, and 4) proposals for action-guiding support for EstimateIT! to help elementary students develop and reinforce an understanding of measurement during gameplay based on the more mature strategies demonstrated by college students as they complete similar tasks.


Worcester Polytechnic Institute

Degree Name



Learning Sciences and Technologies

Project Type


Date Accepted





embodied cognition, gestures, learning technologies, measurement estimation