Mobile Device-Assisted Peer Review in High School Poetry Analysis: The Role of Revision Intensity
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| Title: | Mobile Device-Assisted Peer Review in High School Poetry Analysis: The Role of Revision Intensity |
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| Language: | English |
| Authors: | Ngatmini (ORCID |
| Source: | Educational Process: International Journal. Article e2026046 2026 22. |
| Availability: | UNIVERSITEPARK Limited. iTOWER Plaza (No61, 9th floor) Merkez Mh Akar Cd No3, Sisli, Istanbul, Turkey 34382. e-mail: editor@edupij.com; Web site: http://www.edupij.com/ |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | High Schools Secondary Education |
| Descriptors: | Peer Evaluation, Telecommunications, Handheld Devices, High School Students, Poetry, Revision (Written Composition), Feedback (Response), Program Effectiveness, Foreign Countries |
| Geographic Terms: | Indonesia |
| ISSN: | 2147-0901 2564-8020 |
| Abstract: | Background/purpose: This study investigates how peer feedback translates into actual improvements in high school poetry analysis. It aims to connect feedback processes, feedback network structures, and final product quality by integrating process mining, social network analysis (SNA), and outcome modeling. Materials/methods: Thirty-four students (N = 34) from a high school in Semarang participated in two 90-minute sessions following the sequence: briefing -- peer assessment -- revision -- presentation. Process mining (Optimal Matching and Partitioning Around Medoids) was used to identify workflow archetypes, while SNA examined how feedback was distributed across students. Feedback quantity and quality were linked to final task scores using ANCOVA and linear mixed models, and path analysis was used to test whether revision behavior mediated the effect of feedback on product quality. Results: Process mining revealed three workflow archetypes: Presentation-Leap, Linear-Fast, and Iterative-Revision. SNA indicated a sparse but moderately modular feedback network (density = 0.070; modularity = 0.448; Gini = 0.437; reciprocity = 7.7%). ANCOVA/LMM results showed that revision intensity was the strongest predictor of final quality, followed by weighted incoming feedback, whereas betweenness centrality contributed less. Path analysis confirmed that the effect of feedback on final quality was partially mediated by revision behavior. Conclusions: Meaningful revisions serve as a key mechanism linking peer feedback to improved performance in poetry analysis. Teachers are advised to incorporate mandatory revision checkpoints and to distribute feedback opportunities more equitably across students. The study is limited by its small sample size, single-school context, and nonrandom design; future research should employ multi-site or randomized designs and explore long-term learning outcomes to strengthen generalizability. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1505161 |
| Database: | ERIC |
| Abstract: | Background/purpose: This study investigates how peer feedback translates into actual improvements in high school poetry analysis. It aims to connect feedback processes, feedback network structures, and final product quality by integrating process mining, social network analysis (SNA), and outcome modeling. Materials/methods: Thirty-four students (N = 34) from a high school in Semarang participated in two 90-minute sessions following the sequence: briefing -- peer assessment -- revision -- presentation. Process mining (Optimal Matching and Partitioning Around Medoids) was used to identify workflow archetypes, while SNA examined how feedback was distributed across students. Feedback quantity and quality were linked to final task scores using ANCOVA and linear mixed models, and path analysis was used to test whether revision behavior mediated the effect of feedback on product quality. Results: Process mining revealed three workflow archetypes: Presentation-Leap, Linear-Fast, and Iterative-Revision. SNA indicated a sparse but moderately modular feedback network (density = 0.070; modularity = 0.448; Gini = 0.437; reciprocity = 7.7%). ANCOVA/LMM results showed that revision intensity was the strongest predictor of final quality, followed by weighted incoming feedback, whereas betweenness centrality contributed less. Path analysis confirmed that the effect of feedback on final quality was partially mediated by revision behavior. Conclusions: Meaningful revisions serve as a key mechanism linking peer feedback to improved performance in poetry analysis. Teachers are advised to incorporate mandatory revision checkpoints and to distribute feedback opportunities more equitably across students. The study is limited by its small sample size, single-school context, and nonrandom design; future research should employ multi-site or randomized designs and explore long-term learning outcomes to strengthen generalizability. |
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| ISSN: | 2147-0901 2564-8020 |
