In this study, a predictive model is constructed to analyze learners' performance in programming tasks using data of programming behavioral events and behavioral sequences. First, this study identifies behavioral events from log data and applies lag sequence analysis to extract behavioral sequences that reflect learners' programming strategies.…

Self-monitoring (SM) is a behavioral intervention with a long history of successful implementation for students with autism spectrum disorder. Despite the development of sophisticated software applications, they are rarely incorporated into data collection procedures for SM interventions. The current study evaluated an SM application, goal…

Students with ADHD often struggle with self-regulation skills. One strategy demonstrating considerable success in helping these students regulate their behavior is self-monitoring. Although there is an abundance of research on self-monitoring, research on the use of technology for self-monitoring is only beginning to emerge. The primary goal of…