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All Journal Kajian Bahasa dan Sastra serta Pembelajaran Bahasa Indonesia
Asep Nurjamin
a:1:{s:5:"en_US";s:29:"Institut Pendidikan Indonesia";}
Arts Humanities Education Languange, Linguistic, Communication & Media Social Sciences

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Deteksi Kesalahan Pemahaman Membaca Berbasis Deep Learning untuk Pengembangan Strategi Pembelajaran Adaptif Asep Nurjamin; Aisyah Khoerunnisa Nurjamin; Zainah Asmaniah
Alusi: Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol. 1 No. 2 (2025): Alusi: Kajian Bahasa dan Sastra serta Pembelajaran Bahasa Indonesia
Publisher : Program Studi Pendidikan Bahasa dan Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/alusi.v1i2.3210

Abstract

Reading comprehension is a critical skill for academic success; however, students with reading difficulties often face significant challenges in mastering this skill. This study aims to develop a deep learning-based error detection model for reading comprehension, integrated with Barrett’s Taxonomy as the analytical framework. The model is designed to automatically identify students’ error patterns through the analysis of reading comprehension test responses, thereby providing specific and timely feedback. The research method involves collecting reading test data from elementary school students, annotating errors based on Barrett’s Taxonomy categories, training the deep learning model for error classification, and testing the model’s validity and reliability. Preliminary results indicate that the model can accurately recognize different types of errors, which are then used as the basis for designing adaptive learning strategies tailored to each student’s error profile. These findings are expected to contribute to the development of literacy learning innovations that are responsive to individual needs while enriching artificial intelligence–based educational practices at the elementary school level.
Co-Authors Aisyah Khoerunnisa Nurjamin Zainah Asmaniah