Innovating Online Ethics Training Using a Dynamic Narrative Learning Environment

Ethical dilemmas arise in all aspects of STEM research. To help mitigate the problems associated with unethical research behavior, universities and granting agencies, such as the NSF, require training in responsible conduct of research (RCR). However, while there are a variety of approaches to teaching ethical behavior, including case studies, workshops, and toolkits, ethics training instruction is often reduced to simplified text-based online tutorials.

Ethical oversight agencies and training experts have emphasized the need for additional RCR learning tools that are more engaging, scalable, and offer a hands-on approach to exploring real world problems. This project explores the use of artificial intelligence (AI) techniques within an educational game-based ethics training tool to maximize player motivation and learning.

Specifically, the AI will be used to create realistic interactive ethical scenarios that adjust to the player and choices they make. This research will provide a novel artificial intelligence-based approach to learning ethics and produce an educational game-based ethics training tool that is freely accessible and ready for incorporation into responsible conduct of research training programs nationwide.

Furthermore, by enhancing methods used for training scientists to understand and engage in ethical behavior, this research aims to drive improvements in the quality and accuracy of STEM research as well as encourage healthier workplace practices that support a diverse and inclusive environment.

This project will address the need for engaging, scalable, and hands-on ethics training by applying the Self-Determination Theory (SDT) of motivation through an innovative combination of four state-of-the-art AI-based narrative systems: 1) a social simulation system, 2) a pedagogy manager, 3) a drama manager, and 4) a dynamic content selection architecture (CSA) that dynamically selects texts and options based on author goals and state maintained by the first three systems. Compared to existing approaches to dynamic CSA, this approach enables interactive stories with more flexible delivery of choice-based story content.

The project develops contributions in modeling complex ethical contexts and facilitating learners’ feelings of autonomy, relatedness, and competence. The forms of these contributions are AI-driven narrative techniques to maximize diverse learner motivations, a novel dynamic CSA architecture, and a new approach to ethics training that utilizes AI to improve learner engagement, knowledge, and moral reasoning skill development.

The project takes a design-based research approach to iteratively build out each AI-based narrative system and evaluates the impact this new AI narrative training architecture has on player motivation, engagement, and learning outcomes for ethics training. A randomized controlled trial will also be employed to compare the efficacy of the adaptive interactive narrative game with dynamic CSA to a static narrative version of the same game.

The results are expected to advance understanding of AI-based approaches to leveraging SDT within educational narratives and ethics training, which will enable further innovations in learning technologies.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.