Impact of automated scoring on interpreting performance and self-regulated learning: evidence from a pedagogical experiment

Confronting the challenges of feedback in traditional interpreting training, this study explores how an automated scoring system affects student interpreters’ performance and self-regulated learning (SRL). Guided by Zimmerman’s cyclical model, the study employed a 14-week quasi-experimental design with two intact classes ( N = 46), with data triangulated through pre- and post-test scores, questionnaires, and semi-structured interviews. The experimental group outperformed the control group at post-test ( d = 1.03, 95% CI [0.41, 1.64]), with gains concentrated in linguistic accuracy and logical coherence but absent in information fidelity or delivery fluency, pointing to an uneven effect across interpreting dimensions. SRL results reveal an imbalance in both level and function. Although the Execution-and-Monitoring and Evaluation-and-Reflection subscales scored comparatively high, only the former was significantly associated with score gains ( r = 0.42, 95% CI [0.02, 0.70], p = 0.041), suggesting that high self-reported reflection cannot be assumed to be productive reflection. Pre-learning Planning and Emotional Motivation remained comparatively underdeveloped. The interviews specify why. Students routinely compared their scores but rarely analyzed why errors had occurred. Planning reversed direction, deriving from the previous session’s score rather than from analysis of the upcoming task, and emotional responses diverged. These findings support the value of automated scoring for sustaining deliberate practice, while highlighting the need to align teacher feedback more closely, in timing and individuation, with automated feedback, to support planning and emotional regulation. The contribution therefore lies in specifying which phase of the SRL cycle automated scoring reaches, and with what consequences.