This year Sandbox offers two Master's Theses Topics:
AI Tools for User Experience Design
This thesis will explore the current state of AI-enabled prototyping tools for creating web and app-based interfaces.
The research question to be answered is: What is the current landscape of AI-enabled prototyping tools and to evaluate: 1) how usable they are as a tool for creating prototypes and 2) what is the quality of the prototypes they produce?
The study will begin with an introduction and literature review to establish the relevance and significance of AI in the prototyping space. It will then compare 3 to 5 leading AI prototyping tools, focusing on key features such as usability, automation and design flexibility.
A prototype of a Bike Sharing App will be created using one of these tools and evaluated with between 5-10 participants to assess the quality and usability of the prototype produced by the AI-tool. Based upon participant feedback, improvements will be made to refine the prototype. The thesis will conclude with a discussion of current limitations, potential uses in its current state, recommendations and further work.
Level: Master's
Supervisors: Grace Eden, PhD; Yana Halas, MSc
Language: English
LLMs as a Tool for User Experience Research: A Comparison of synthetic and real-world data
This thesis will explore how Large Language Models (LLMs) could be used as a tool to create synthetic user data through ‘mock interviews’, ‘user scenarios’, and ‘personas’.
The research question to be answered is: How useful is artificially generated data compared to real-world data for understanding user needs.
The study will begin with an introduction and literature review to understand the current landscape of LLMs in User Experience Research. Next, real-world data will be gathered regarding user needs for a Bike Sharing App. This will include conducting between 5-10 interviews. From this data, user scenarios and personas will be created. After, LLMs such as ChatGPT, Gemini, Perplexity, and Claude will be used to generate synthetic user data. First, with mock interviews using the same interview questions, and then from these deriving artificial user scenarios and personas.
Level: Master's
Supervisors: Grace Eden, PhD; Yana Halas, MSc
Language: English
Interested in a topic? Please send a short motivation letter to yana.halas [at] ut.ee