Productive Discussion Moves in Groups Addressing Controversial Issues

TL;DR

This study explores what makes discussions about AI ethics productive among undergraduates, identifying key discussion moves and interaction patterns that foster high-quality ethical dialogue.

Contribution

It introduces a hybrid coding and topic modeling approach to identify discussion moves and analyzes their impact on discussion quality in ethical debates.

Findings

Emotive arguments and acknowledgment of ambiguity predict higher discussion quality.

Building on ideas is negatively associated with discussion quality.

Interaction patterns connecting emotional expression and reasoning characterize productive discussions.

Abstract

Engaging learners in dialogue around controversial issues is essential for examining diverse values and perspectives in pluralistic societies. While prior research has identified productive discussion moves mainly in STEM-oriented contexts, less is known about what constitutes productive discussion in ethical and value-laden discussions. This study investigates productive discussion in AI ethics dilemmas using a dialogue-centric learning analytics approach. We analyze small-group discussions among undergraduate students through a hybrid method that integrates expert-informed coding with data-driven topic modeling. This process identifies 14 discussion moves across five categories, including Elaborating Ideas, Position Taking, Reasoning & Justifications, Emotional Expression, and Discussion Management. We then examine how these moves relate to discussion quality and analyze sequential interaction patterns using Ordered Network Analysis. Results indicate that emotive and experiential arguments and explicit acknowledgment of ambiguity are strong positive predictors of discussion quality, whereas building on ideas is negatively associated. Ordered Network Analysis further reveals that productive discussions are characterized by interactional patterns that connect emotional expressions to evidence-based reasoning. These findings suggest that productive ethical discussion is grounded not only in reasoning and justification but also in the constructive integration of emotional expression.