Personalized regulatory guidance during online cloze tasks: Performance, emotions, and exploratory self-efficacy differences

Abstract

This study examined whether personalized regulatory guidance supports students' performance, emotions, motivation, and strategy use during online cloze tasks, and whether problem-solving self-efficacy is associated with variability in students' responses to such guidance. Forty-eight secondary school students were randomly assigned to common emotion-regulation instruction with or without additional personalized real-time guidance. The guidance included emotion-focused, task-focused, and regulation-focused prompts delivered during task performance. Outcomes included pre- and pos t -test cloze performance, emotional and motivational experiences, emotion-regulation strategy use, and exploratory moderation by self-efficacy. Personalized guidance improved task performance, positive emotions, and motivation, but did not produce significant average differences in reported strategy use. Exploratory analyses suggested that students with higher self-efficacy may show stronger emotional benefits and engage more frequently in emotion-focused strategies after receiving personalized regulatory guidance. The findings provide preliminary evidence that personalized regulatory support can facilitate online task performance, but the active mechanisms and individual-difference effects require replication. Educational relevance and implications statement Personalized regulatory guidance helped students perform better and experience more positive emotions during complex online cloze tasks. However, the guidance included emotional, task-focused, and metacognitive prompts, so the findings should be interpreted as evidence for a broader support package rather than for emotion-regulation guidance alone. The study also suggests that students may differ in how they benefit from such support, although the self-efficacy findings are preliminary. In practice, one-to-one guidance may be difficult to scale, so future work should examine more feasible forms of adaptive support, such as standardized prompts, teacher dashboards, or AI-supported guidance.