Adaptive Interaction Strategies in Healthcare Chatbots

Institut

Lehrstuhl für Ergonomie (TUM-ED)

Typ

Semesterarbeit / Masterarbeit /

Inhalt

experimentell /  

Beschreibung

Background:

Conversational agents are increasingly used for health-related information and as symptom checkers. In these high-stakes contexts, how a chatbot communicates (e.g., clarity, transparency, credibility, emotional support) strongly shapes user trust, acceptance, and safe use. A key open question is when a chatbot should adapt its communication: different user states (e.g., anxiety, confusion, skepticism) may require different response characteristics. Evidence on which user signals should trigger adaptation is still limited, especially at the level of concrete, implementable chatbot characteristics.

 

Objective:

This thesis aims to identify and validate user-state signals that should trigger adaptive chatbot responses in healthcare. Through an online user study, different user states and preferences for chatbot response characteristics (e.g., explainability/clarity, transparency/credibility, empathy/support). The outcome will be a trigger-to-response guideline that can inform the design of adaptive medical diagnosis chatbots.

Tasks:

• Literature Review (Chatbot design, dialog management, human-AI communication)
• Study design and execution
• Derivation of a “signal → preferred characteristics” mapping and design recommendations for adaptive chatbots

Voraussetzungen

• Interest in Human-AI Interaction, chatbots, UX, interaction design
• Experience with user study methods, survey tools
• Familiarity with chatbot interfaces or AI tools

Möglicher Beginn

sofort

Kontakt

Rutuja Joshi
Raum: MW3329
Tel.: +49 162 2062924
rutuja.joshitum.de

Ausschreibung