Study Shows Preference for Human-Like Agents in Mobile Serious Game
A study with 90 participants compared a highly human-like spoken embodied conversational agent (ECA) against a low human-like text-based agent in a mobile game about pre-decimal UK currency. The game featured two agent roles: an Instructor (Alex) and a Shopkeeper/Collaborator. Users interacted via voice and mouse. Quantitative data from usability questionnaires (CCIR MINERVA) and the Agent Persona Instrument were analyzed using paired t-test, repeated measures ANOVA, and multiple linear regression. Results showed a statistically significant preference for the highly human-like agent version with a large effect size. Qualitative findings further support this preference.
Key facts
- Study involved 90 participants
- Within-subjects design
- Compared highly human-like spoken ECA vs low human-like text-based agent
- Game developed in Unity about pre-decimal UK currency
- Two agent roles: Instructor (Alex) and Shopkeeper/Collaborator
- Data collected via CCIR MINERVA usability questionnaire and Agent Persona Instrument
- Statistical analysis: paired t-test, repeated measures ANOVA, multiple linear regression
- Significant preference for highly human-like agents with large effect size
Entities
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