Abstract
Feedback is powerful but variable. This study investigates which forms of feedback are more predictive of improvement to students’ essays, using Turnitin Feedback Studio–a computer augmented system to capture teacher and computer-generated feedback comments. The study used a sample of 3,204 high school and university students who submitted their essays, received feedback comments, and then resubmitted for final grading. The major finding was the importance of “where to next” feedback which led to the greatest gains from the first to the final submission. There is support for the worthwhileness of computer moderated feedback systems that include both teacher- and computer-generated feedback.
Highlights
One of the more powerful influences on achievement, prosocial development, and personal interactions is feedback–but it is remarkably variable. Kluger and DeNis (1996) completed an influential meta-analysis of 131 studies and found an overall effect on 0.41 of feedback on performance and close to 40% of effects were negative
This study investigates a range of feedback forms, and in particular investigates the hypothesized claim that feedback that leads to “where to ” decisions and actions by students is most likely to enhance their performance
It uses Turnitin Feedback Studio to ask about the relation of various agents of feedback, and codes the feedback responses to identify which kinds of feedback are related to the growth and achievement from first to final submission of essays
Summary
One of the more powerful influences on achievement, prosocial development, and personal interactions is feedback–but it is remarkably variable. Kluger and DeNis (1996) completed an influential meta-analysis of 131 studies and found an overall effect on 0.41 of feedback on performance and close to 40% of effects were negative. They wanted feedback that would help them “ time” they complete a similar task in the future, but that would help them develop the ability to think critically and self-regulate moving forward It is these transferable skills and understandings that students consider as important, but, as identified in this study, challenged teachers in practice as it was rarely offered. One often suggested method of improving the nature of feedback is to administer it via computer-based systems Earlier synthesis of this literature tended to focus on task or item-specific level and investigating the differences between knowledge of results (KR), knowledge of correct response (KCR), and elaborated feedback (EF). A 2013 survey about students’ perceptions of the value, type, and timing of instructor feedback reported that 67% of students claimed receiving general, overall comments, but only 46% of those students rated the general comments as “very helpful.”. It uses Turnitin Feedback Studio to ask about the relation of various agents of feedback (teacher, machine program), and codes the feedback responses to identify which kinds of feedback are related to the growth and achievement from first to final submission of essays
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