Feedback is an invaluable tool used in educational settings. In writing, teachers often provide feedback to their students, paving the way for improvement in their writing performance. For feedback to be truly effective, students must actively process them, connect it to their own writing, and decide on how to incorporate them. To further explore this idea, Bouwer and Dirkx (2023) examined the underlying process behind feedback engagement by conducting two studies.
Study 1 consisted of 16 Dutch-native-speaking university students from a one-year pre-master’s program on Management Science. Prior to the study, the participants completed a written report. During the study, participants were presented on a computer screen with actual teacher feedback that they received on the report and were instructed to work on improving the assignment as they normally would when working at home. However, they were required to think out loud throughout the entire time. A remote SMI eye-tracker was placed under a computer screen to track participants’ gaze patterns while a microphone recorded thoughts spoken out loud. All verbal data and revisions made on the report were coded by the researchers, allowing it to be used in combination with eye-tracking data, allowing various feedback processing strategies to be derived.
Study 2 consisted of 41 Dutch-native speaking, third-year Bachelor students at the Technical University of Delft, the Netherlands. The study was divided into two phases: Phase 1 and Phase 2. During Phase 1, participants were presented with an average-quality text written by a student from the previous year along with ten actual feedback comments from a teacher. They were instructed to only read the text and feedback as of that moment. The comments varied in focus and directiveness (i.e. four comments focused on lower-order aspects, such as grammatical errors and language use, and six comments focused on higher-order aspects, such as content and structure). Using a remote desktop eye tracking system, their attention while reading was measured through their eye movements. During Phase 2, the participants were given a laptop and instructed to revise the text. Their revision behavior was tracked through their keystrokes (e.g. mouse clicks and pause times) using a keystroke logging program.
Study 1 found that there existed three different types of feedback processing strategies: superficial processing (reading the feedback once and not going back to it or the text), local processing (reading the feedback multiple times and constantly referring to it and the commented text), and deep processing (incorporating the feedback all throughout the text). The results also showed that the deep processing strategy was related to effective feedback use behaviors including frequently referring back to the feedback while evaluating the text, and making revisions to the text based on the feedback. Similarly, Study 2 found a relationship between deep processing strategy, longer reading times, and higher frequency of revisits for various parts of the text (commented and uncommented), as compared with local feedback processing. It also found that lower-order feedback was more successful in getting students to make revisions than higher-order feedback. The directiveness of the feedback was revealed to have no effect on their revision behavior. Despite the findings produced by the studies, some of their limitations include unintentionally giving the students an advantage in the study by allowing them to only review the feedback and text prior to revising the text, students not fully understanding the teacher’s feedback due to the language used in it, and not measuring their evaluation process for both studies.
These results highlight the importance for students to actively engage in deep levels of feedback processing in order to enhance their writing performance. Teachers may work towards integrating deep processing strategies among their students by demonstrating how to process feedback deeply and use them to revise the text. Additionally, there is a relationship that can be drawn between the study’s focus on understanding and integrating feedback and EPIC’s study on how students react to different types of failures and setbacks. Future EPIC studies can examine in greater detail how students use different types of feedback to improve their writing.
If you want to learn more about Bouwer and Dirkx’s (2023) study, check it out at:
https://doi.org/10.1016/j.learninstruc.2023.101745
This post is written by Jessica Wang.
Reference:
Bouwer, R., & Dirkx, K. (2023). The eye-mind of processing written feedback: Unraveling how students read and use feedback for revision. Learning and Instruction, 85, 101745.
