Work

Shall We Play a Game? Distributed Games with a Generative AI Player

Year: 2024

Type: conference-paper

Abstract: The prevalence of generative AI tools -especially large language models that enable human-like conversation -provides an opportunity to study how human learners interact with AI as collaborative ideators in the learning process.We expand the framework of distributed games (which initially focused on epistemic games of discovery as distributed processes) to investigate learner interaction with generative AI in design tasks.Through a comparative case study of two undergraduates using a generative AI tool in design tasks, we illustrate different ways in which learners orient themselves to the elements of the game (task, form, other players, etc.) and the corresponding complexity of the game played.We discuss implications for the design of learning environments that facilitate interaction with AI tools in distributed creative tasks.

Source: Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference

DOI: 10.22318/cscl2024.638463

Authors: Jenna Matthews, Ha Nguyen, Hillary Swanson

Institution: Utah State University

Language: English

Topic: Innovative Teaching and Learning Methods

Subfield: Developmental and Educational Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: bronze

OpenAlex ID: W4399489080