Date of Award

Spring 2026

Rights

Access is available to all users

Document Type

Thesis

Degree Name

Master of Science (MS) in Computer Science

Department

Computer Science and Electrical Engineering

First Advisor

Shamima Yasmin

Second Advisor

Sanmeet Kaur

Third Advisor

Yves Nievergelt

Abstract

Virtual Reality (VR) is slowly becoming more popular for more than just entertainment. VR can be found in educational, office, and even healthcare settings to help discover more intuitive ways to teach, collaborate, and treat patients. Outside of the virtual world, these environments typically rely on writing for communicating or note-taking. Currently, VR input forces users to rely on clunky on-screen keyboards which disrupts the user’s immersion and breaks the flow of natural interaction. This thesis explores the potential of VR as a learning platform by combining it with artificial intelligence (AI). It aims to develop a VR-enhanced handwriting practicing platform using different interfaces to help learners monitor their writing progress based on the feedback provided by handwritten text recognition (HTR) models. A pipeline was developed to enable users to practice handwriting using different interfaces, i.e., VR controllers and a haptic device. Next, several HTR models were explored and a feasibility analysis was conducted that led to TrOCR being used in the pipeline. A user study with 19 participants was conducted to test the feasibility of the pipeline and the functionality of each interface. Results showed that the haptic interface was rated the most usable and produced the highest model confidence and lowest error rates, while the raycast interface performed worst on both objective and subjective measures. These findings suggest that physically grounded interfaces are better suited for handwriting in VR, and that the proposed pipeline is a promising foundation for an immersive, personalized language learning environment that promotes inclusivity by allowing learners to practice using their preferred interface. Though the primary focus of this research is about learning enhancement by combining AI and VR, integration of AI and VR would also overcome the limitations of current VR input methods, as mentioned in the first paragraph. Additionally, VR would help develop a personalized learning environment and learners will be able to practice handwriting using their preferred interfaces. This research aims to promote inclusivity in learning as well.

Download

Share

COinS