EVALUATING THE TRANSLATION QUALITY OF CHILDREN'S LITERATURE IN THE LET’S READ MOBILE APPLICATION USING ANGELELLI'S SCORING RUBRIC TO ASSESS SOURCE TEXT MEANING ACCURACY

Authors

  • Harris Hermansyah Setiajid
  • Natalia Krisnarani Universitas Sanata Dharma
  • Diksita Galuh Nirwinastu Universitas Sanata Dharma

DOI:

https://doi.org/10.25170/kolita.21.4844

Keywords:

Angelelli’s scoring rubric, children’s literature translation, Let’s Read mobile application, translation quality

Abstract

This study aims to comprehensively evaluate the translation quality of a children's story, "Dive", featured in the Let's Read mobile application. Utilizing Angelelli's scoring rubric, the research focuses on assessing the accuracy of source text meaning in the translated children's literature, examining elements such as fluency, readability, cultural adaptation, and style. By conducting an in-depth analysis of the Indonesian translation of "Dive," the study uncovers the strengths and weaknesses of the translation process, as well as any challenges encountered in adapting the text for a young Indonesian audience. The research methodology involves selecting the story "Dive" and its Indonesian translation, "Menyelam," from the Let's Read mobile application, and assessing the translation using Angelelli's scoring rubric, which ranges from 1 (poor) to 5 (excellent). The findings from this study contribute significantly to the ongoing discourse on translation quality assessment, particularly in the context of children's literature. The results offer valuable insights for improving the translation process and enhancing the reading experience for young audiences accessing the Let's Read mobile application. Furthermore, the study highlights the importance of accurately conveying the source text meaning to maintain the educational and entertainment value of translated children's literature, while also emphasizing the need for cultural sensitivity and adaptation in order to create an engaging and relatable reading experience for children from diverse backgrounds.

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Published

2023-10-30
Abstract views: 78 | PDF downloads: 54