Daily automated feedback enhances self-regulated learning: a longitudinal randomized field experiment - Bellhäuser, Henrik; Dignath, Charlotte; Theobald, Maria (Frontiers in Psychology, 2023)
The goal of the present study was to investigate the effects of automatically generated, adaptive feedback on daily self-regulated learning (SRL) in an experimental field study. University students reported their application of SRL strategies in the morning and in the evening over the course of 36 days using electronic learning diaries. Students were randomly assigned to the experimental group with feedback (LDF, n = 98) or the control group without feedback (LD, n = 96). Based on their self-reports, students in group LDF received daily written feedback regarding their satisfaction with the study day, adherence to time schedule, procrastination, and effort. This feedback either reinforced students in their study approach (confirmative feedback), encompassed information on learning outcomes or processes (informative feedback), or included feed forward on how to improve learning processes (transformative feedback). Multilevel analysis of daily process data revealed better average goal setting, planning and adherence to time schedule, as well as higher self-efficacy, and satisfaction with the study day in group LDF compared to group LD. Motivation, procrastination and effort were not affected by feedback. In contrast to the process measures, pre-post comparisons of students’ self-reported general use of SRL strategies (trait measures) did not reveal any effects of feedback on SRL. Further explorative analyses investigated the effects of confirmative, informative, and transformative feedback on next day’s learning behavior, showing that confirmative and transformative feedback had stronger effects on students' satisfaction and procrastination than informative feedback. Transformative feedback, which included specific strategies for moving forward, was effective in improving time management. Results provide theoretical insight into the interplay of feedback and SRL and offer practical implications regarding the design of feedback in a learning context.