Attention Monitoring and Engagement Analytics Dataset from an AI-Supported Gamified Flipped ADHD Course

The course was designed as an artificial intelligence-supported, gamified, and mostly asynchronous flipped learning environment. The dataset includes anonymized quantitative records related to objective attention monitoring, gamified engagement, screen-time monitoring, course participation, and instructional design alignment.Objective attention performance was measured using the d2 Test of Attention before and after the instructional implementation.

Gamified engagement indicators include task completion records, point-producing activities, game-based learning records, bonus tasks, process-related tasks, and final competition scores. Screen-time indicators were collected to contextualize students’ digital participation during the course. A separate video-game design alignment dataset documents how instructional videos were connected with gamified, assessment-related, monitoring-related, and data-related course components.The dataset is intended to support transparency, reproducibility, secondary analysis, and methodological understanding of how AI-supported content preparation, gamified self-monitoring, flipped learning, screen-time contextualization, and objective attention monitoring were integrated within special education teacher preparation.