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Description
For this master's thesis, a unique set of cognitive prompts, designed to be delivered through a teachable robotic agent, were developed for students using Tangible Activities for Geometry (TAG), a tangible learning environment developed at Arizona State University. The purpose of these prompts is to enhance the affordances of the tangible learning environment and help researchers to better understand how we can design tangible learning environments to best support student learning. Specifically, the prompts explicitly encourage users to make use of their physical environment by asking students to perform a number of gestures and behaviors while prompting students about domain-specific knowledge. To test the effectiveness of these prompts that combine elements of cognition and physical movements, the performance and behavior of students who encounter these prompts while using TAG will be compared against the performance and behavior of students who encounter a more traditional set of cognitive prompts that would typically be used within a virtual learning environment. Following this study, data was analyzed using a novel modeling and analysis tool that combines enhanced log annotation using video and user model generation functionalities to highlight trends amongst students.
ContributorsThomas, Elissa (Author) / Burleson, Winslow (Thesis advisor) / Muldner, Katarzyna (Committee member) / Walker, Erin (Committee member) / Glenberg, Arthur (Committee member) / Arizona State University (Publisher)
Created2014
Description
Many English Language Learner (ELL) children struggle with knowledge of vocabulary and syntax. Enhanced Moved by Reading to Accelerate Comprehension in English (EMBRACE) is an interactive storybook application that teaches children to read by moving pictures on the screen to act out the sentences in the text. However, EMBRACE presents the same level of text to all users, and it is limited in its ability to provide error feedback, as it can only determine whether a user action is right or wrong. EMBRACE could help readers learn more effectively if it personalized its instruction with texts that fit their current reading level and feedback that addresses ways to correct their mistakes. Improvements were made to the system by applying design principles of intelligent tutoring systems (ITSs). The new system added features to track the student’s reading comprehension skills, including vocabulary, syntax, and usability, based on various user actions, as well as features to adapt text complexity and provide more specific error feedback using the skills. A pilot study was conducted with 7 non-ELL students to evaluate the functionality and effectiveness of these features. The results revealed both strengths and weaknesses of the ITS. While skill updates appeared most accurate when users made particular kinds of vocabulary and syntax errors, it was not able to correctly identify other kinds of syntax errors or provide feedback when skill values became too high. Additionally, vocabulary error feedback and adapting the complexity of syntax were helpful, but syntax error feedback and adapting the complexity of vocabulary were not as helpful. Overall, children enjoy using EMBRACE, and building an intelligent tutoring system into the application presents a promising approach to make reading a both fun and effective experience.
ContributorsWong, Audrey (Author) / Walker, Erin (Thesis advisor) / Nelson, Brian (Committee member) / Glenberg, Arthur (Committee member) / Arizona State University (Publisher)
Created2017