Abstract

In large-scale assessments, disengaged participants might rapidly guess on items or skip items, which can affect the score interpretation’s validity. This study analyzes data from a linear computer-based assessment to evaluate a micro-intervention that blocked the possibility to respond for 2 s. The blocked response was implemented to prevent participants from accidental navigation and as a naive attempt to prevent rapid guesses and rapid omissions. The response process was analyzed by interpreting log event sequences within a finite-state machine approach. Responses were assigned to different response classes based on the event sequence. Additionally, post hoc methods for detecting rapid responses based on response time thresholds were applied to validate the classification. Rapid guesses and rapid omissions could be distinguished from accidental clicks by the log events following the micro-intervention. Results showed that the blocked response interfered with rapid responses but hardly led to behavioral changes. However, the blocked response could improve the post hoc detection of rapid responding by identifying responses that narrowly exceed time-bound thresholds. In an assessment context, it is desirable to prevent participants from accidentally skipping items, which in itself may lead to an increasing popularity of initially blocking responses. If, however, data from those assessments is analyzed for rapid responses, additional log data information should be considered.