Unit 1 presents the key question driving the entire course: what do people expect from AI-mediated storytelling, and how do those expectations influence their experiences? Students explore the psychological and communication mechanisms behind how expectations are formed, triggered, and either confirmed or challenged during human-AI narrative interactions — using expectancy theory, schema theory, media psychology, and early research on how people perceive AI storytelling.
Define and distinguish user expectations, perceptions, and experiences in human-AI mobile storytelling
Apply expectancy theory and schema theory to user responses to AI narrative content
Identify key factors shaping initial user expectations of AI storytelling systems
Apply the 3D framework to analyze user perception data
Document and critically evaluate CICI interactions
Reeves, B., & Nass, C. (1996). The media equation. Chapters 1–3.
Sundar, S. S. (2020). Rise of machine agency. Journal of Computer-Mediated Communication, 25(1), 74–88.
Langer, E. J. (1989). Mindlessness and mindfulness in human-computer interaction. International Journal of Human-Computer Studies, 50(4), 381–395.
Hancock, J. T., et al. (2020). AI-mediated communication. Journal of Computer-Mediated Communication, 25(1), 89–100.
Expand each activity and click "Mark as complete" to track your progress.
600–800 word reflection: CICI documentation from Activity 1.3, 3D analysis of expectation-gap patterns, schema activation insights, and 3M framework for measuring user expectations.