Dynamic Assessment as A Strategy to Enhance Deep Learning in Narrative Writing for Elementary School Students

Background/purpose. This study aims to analyze the application and impact of dynamic assessment as an enhancement of deep learning in writing narratives for elementary school students. The main focus is DA can improve the quality of the learning process and outcomes through intervention, feedback, and reflective revision.

Materials/methods. This study used a mixed-method approach with 61 6th-grade students as subjects. The DA process involved three main stages, namely 1) pretest; 2) intervention with four topics, namely text structure, linguistic features, grammar, and moral values in ceria; 3) post-test. Feedback was given in various forms, including peer assessment, direct written feedback from teachers, and technology-based interactive discussions through Wordwall.

Results. The implementation of DA in elementary school students' narrative writing learning has a significant impact through three main stages: pretest, intervention, and post-test. DA supports mastery of text structure, linguistic features, grammar, and moral values with a responsive learning approach, such as peer assessment, class discussion, and the use of interactive digital media. Statistically, the average student score increased from 59.15 in the pretest to 75.85 in the post-test, with a significant increase (t=43.95, p<0.05).

Conclusion. DA not only improves the technical quality of students' writing, but also supports mindful, meaningful, and joyful learning through reflective revision, personal experience connections, and fun learning activities. Implications of this study include the integration of DA into the curriculum, teacher training to understand scaffolding and formative feedback, and the use of interactive technologies to support deep, inclusive, and adaptive learning

Keywords: Dynamic assessment, deep learning, narrative writing, elementary education

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