This research looks at the interaction between children and their home reading companion robot - Luka. Children's interaction and perception of the robot, along with the influence of their family context are measured and evaluated over time.

This project investigates the relationship between multisensory systems and cognition, specifically focusing on how they contribute to the conceptual understanding of dynamic scientific systems within VR simulations. By leveraging the advancements in accessible virtual reality technologies and sensing technologies to trace students’ responses, actions, and interactions, we have the unique opportunity to explore how multisensory perception can enhance learning outcomes.

GPT-4 has proven to be a language model that is proficient at understanding and producing English sentences. Less is known about its ability to handle dialectal variation or English spoken by those outside of the “Inner Circle” (Kachru, 1985). This may place postcolonial English speakers outside of the Inner Circle at a disadvantage as they may not be able to use this technology in the same ways as speakers of more dominant Englishes, thereby perpetuating inequity. This research aims to initially determine if such a problem exists and subsequently explore ways to rectify it if it does.

This ongoing research project leverages multi-agent large language models (LLMs) to develop an AI-powered chatbot that significantly advances communication for autistic individuals, their families, and caregivers. By integrating cutting-edge AI technology with community-focused goals, the chatbot serves as both a personalized communication tool and a centralized resource hub, providing tailored access to academic research, services, and recommendations. It fosters social interaction and reduces frustration by helping families better understand and address the needs of autistic individuals. Collaborating with My Autism Guide Canada and the Autism Alliance of Canada, the project facilitates knowledge-sharing among researchers, service providers, and families. Using multi-agent LLMs, the chatbot customizes responses based on user age, knowledge, and language proficiency, with future plans to enhance predictive communication capabilities and integrate multimedia inputs, such as images and visual aids, to accommodate diverse communication styles and needs.

Our current project investigates the transformative role of Generative Artificial Intelligence (Gen-AI) in creative industries, focusing on its unique affordances in the artistic process. Moving beyond traditional perspectives that center on human creators, we explore creativity as a relational dynamic involving human and nonhuman agents. This research highlights how Gen-AI influences not just the execution but also the ideation and conceptualization phases of art, redefining creative agency and collaboration. By examining Gen-AI's capacity to co-create through cognitive and conceptual affordances, this work challenges established paradigms and opens new possibilities for artistic innovation.