Date of Conferral
Application of clearly defined feedback types, which have been correlated with improved student performance, has great potential for maximizing instructor use of feedback and its effect on a learner's self-regulatory learning (SRL) for optimized learning. Within SRL, where learner performance is influenced by a recursive internal process, instructional feedback plays a critical role. Yet, the characteristics of external feedback that influence SRL to improve performance are unclear in the literature. Within a theoretical framework where feedback catalyzes self-regulation, this quantitative study sought to integrate feedback type research to expand the SRL model. Data were graded assignments from 23 undergraduate level and 8 graduate level online university courses randomly selected from a pool of 86 possible courses. Applying non-experimental logistic regression and using descriptive statistics, feedback was categorized to determine the quantity of each of the 5 feedback types [task correctness (FC), task elaboration (TE), task process (FP), self-regulation (FR), and personal or self-related (FS)], as well as how they correlated with improved performance. The results indicate that the feedback types were not normally distributed, FS was statistically not present and FE was most used, and the logistical regression indicated that the presence of FC and FR was minimally associated with improved performance. Additional experimentation is needed to normalize the type distribution and test the strength of the FC and FR effect. This study initiated a clarification in understanding the external component of feedback in the SRL model, which is necessary to harness feedback to create positive change in the self-regulatory processes of learners.
Hemerda, Jodie Maria, "Maximizing Feedback for Self-Regulated Learning" (2016). Walden Dissertations and Doctoral Studies. 1895.