If you Cheat, I Cheat: Cheating on a Collaborative Task with a Social Robot

TL;DR

This study explores how the presence of a social robot influences college students' cheating behavior during a collaborative task, revealing that prior exposure to cheating increases likelihood of cheating regardless of task clarity.

Contribution

It provides new insights into how social robots and normative behaviors affect academic integrity in educational settings.

Findings

Prior cheating exposure increases cheating likelihood

Task clarity does not significantly affect cheating behavior

Normative peer behavior influences cheating decisions

Abstract

Robots may soon play a role in higher education by augmenting learning environments and managing interactions between instructors and learners. Little, however, is known about how the presence of robots in the learning environment will influence academic integrity. This study therefore investigates if and how college students cheat while engaged in a collaborative sorting task with a robot. We employed a 2x2 factorial design to examine the effects of cheating exposure (exposure to cheating or no exposure) and task clarity (clear or vague rules) on college student cheating behaviors while interacting with a robot. Our study finds that prior exposure to cheating on the task significantly increases the likelihood of cheating. Yet, the tendency to cheat was not impacted by the clarity of the task rules. These results suggest that normative behavior by classmates may strongly influence the decision to cheat while engaged in an instructional experience with a robot.