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All Journal JUPE : Jurnal Pendidikan Mandala Riwayat: Educational Journal of History and Humanities
Husnaini, Azizah Nurul
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Humanities Education Social Sciences

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Urban Areas' Readiness in Providing Learning Accommodations for Students with Disabilities Post-COVID-19 Pandemic Sholihah, Lintang Al mar'atus; Ningsih, Kholifatul Novita; Hardiani, Wahyu; Insani, Nur Hanifah; Husnaini, Azizah Nurul
JUPE : Jurnal Pendidikan Mandala Vol 10, No 3 (2025): JUPE : Jurnal Pendidikan Mandala (September)
Publisher : Lembaga Penelitian dan Pendidikan Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/jupe.v10i3.9379

Abstract

The shift in learning models following the COVID-19 pandemic, which occurred without adequate preparation, has added new challenges for students with special needs. As an educational institution in an urban area, Jakarta State University should be an ideal example of an inclusive campus. Although opportunities for students with special needs to enroll have expanded, this has not been matched by specific preparations for learning accommodations. This study aims to identify the challenges faced by students with special needs in obtaining appropriate learning accommodations. Additionally, this study seeks to explore the shift in learning accommodation needs of students with special needs post-pandemic COVID-19. A mixed-method research approach was selected, with quantitative data as the primary focus. Data collection was conducted through questionnaires and interviews, while quantitative data analysis utilized descriptive statistical analysis. The research subjects consisted of 34 students with special needs from eight faculties, enrolled between 2018 and 2024. The students with special needs involved in this study had visual impairments, hearing impairments, physical impairments, low vision, ADHD, learning difficulties, and autism. The results of the study showed diversity in learning accommodation needs for each type of special need. However, these differences could be predicted based on the type and level of special needs. The five aspects studied—course materials, teaching methods, facilities and equipment, peer support, and the need for self-regulation skills—highlight the importance of further attention from the university. These aspects of learning accommodations reflect a shift in learning modes influenced by the COVID-19 pandemic. This shift adds challenges for students with special needs in preparing themselves for the workforce.
Analysis of Vocational High School Students' Skills Through Deep Learning Husnaini, Azizah Nurul; Irianto, Tenri Ugi; Munawwar, Muhammad Subchan
Riwayat: Educational Journal of History and Humanities Vol 8, No 4 (2025): Oktober, Social Issues and Problems in Society
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v8i4.49499

Abstract

This study explores the application of deep learning techniques in assessing and enhancing the skills of vocational high school (VHS) students. Vocational education plays a critical role in preparing students for the workforce, and the integration of artificial intelligence, particularly deep learning, has the potential to transform how students practical and theoretical skills are evaluated. Through a comprehensive review of existing literature, this research investigates the effectiveness of deep learning models, such as deep neural networks (DNNs) and convolutional neural networks (CNNs), in predicting and assessing vocational students' competencies. The findings reveal that deep learning offers promising accuracy in skill prediction and personalized feedback, with applications ranging from automated grading systems to skill-specific assessments in technical fields. However, challenges such as data quality, model interpretability, and integration with traditional education systems remain significant obstacles. The study concludes with recommendations for further research, including expanding deep learning applications to real-time assessments and hybrid evaluation methods. Overall, this research highlights the potential of deep learning to enhance vocational education but underscores the need for addressing existing challenges to ensure its effective implementation.
Co-Authors Hardiani, Wahyu Insani, Nur Hanifah irianto, tenri ugi Munawwar, Muhammad Subchan Ningsih, Kholifatul Novita Sholihah, Lintang Al mar'atus