Abstract: Caregivers of children often need to interpret complex emotional states to appropriately provide care, yet these inferences can be challenging and subjective. The rise of affective-aware artificial intelligence (AI) has led to systems that can identify people’s emotions from multimodal data, yet it remains unclear how these systems can influence human judgment. This paper examines the question: how effectively can AI explain children’s emotional states compared to human caretakers, in terms of explanatory accuracy, depth, and ability to influence human reasoning? 

This research paper was done over the course of Fall 2025. We conducted an empirical study and used a Gemini application to analyze videos of children and create an explanation to back its analysis. Our participants were college students with experience in childcare, who were asked to analyze the videos and the AI's responses. Our results show that AI's explanation had a small influence on a large number of participants by increasing nuance and interpretive logic in their judgments. These findings suggest that conversational AI might function less as an authority but more as a scaffolding technique in supporting emotional reasoning in caregiving contexts.

This paper explores the popular social game Mafia through the lens of teaching misinformation in an eighth-grade civics classroom. Learning goals are backed by RAND Corp. Media Literacy standards. Modifications were made to the original Mafia game to increase constructivist learning and help create an engaging atmosphere for every student. 

This was researched and created for CMS.590: Design and Development of Games for Learning, taken at MIT, Spring 2026.

Comparison Curator is a game-based learning experience designed to help ninth-grade students develop creative fluency with similes and metaphors through play. The project shifts figurative language from memorization to active creation by using prompts, rotating peer evaluation, and anonymous submissions to encourage risk-taking and highlight the subjectivity of meaning. Grounded in constructionist learning theory, the game emphasizes collaboration, creativity, and learning through making, reflecting my interest in designing joyful and socially engaging educational experiences.

This was researched and created for CMS.590: Design and Development of Games for Learning, taken at MIT, Spring 2026.