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IMPLICATION OF A 12 PERCENT VALUE ADDED TAX INCREASE ON FARMERS’WELFARE IN INDONESIA Andi Asrijal; Mardi Mardi; Abdul Rahman; Asriadi Asriadi
INJOSEDU: International Journal of Social and Education Vol. 2 No. 4 (2025): APRIL
Publisher : Adisam Publisher

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Abstract

This study is a qualitative study with a descriptive approach, namely an approach that describes the main problem, namely around the twelve percent value added tax increase policy on farmer welfare. The data used in this article is secondary data that researchers obtain from various credible sources such as books, scientific journals, scientific magazines, credible websites, and various other sources that are commonly used in each study. The existing data is analyzed by the stages of data collection, data selection, data reduction, and drawing conclusions with a more comprehensive explanation below.
Integrating AI in ELT: A Case Study of Self-Directed Sustainable Learning in Education 5.0 Abdul Rahman; Gunawan Gunawan; Abdul Rahman R; Fahriadi Muhdar; Dewi Sartika
GLENS: Global English Insights Journal Vol. 3 No. 2 (2026): GLENS, April 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/glens.v3i2.561

Abstract

This study investigates the integration of artificial intelligence in English language teaching (ELT) within the Education 5.0 framework to support adaptive and sustainable learning, particularly to address the gap between technical AI use and pedagogical integration. A qualitative case study was conducted at Cahaya Prima University in Bone Regency over eight weeks, involving 23 students from diverse non-English disciplines (Public Administration, Retail Management, and Library Science) and three lecturers selected through purposive sampling. Data were collected through observations, interviews, and documentation, and analyzed using thematic analysis. The findings highlight three key outcomes. First, AI tools, primarily ChatGPT, Gemini, Dola, and Google Translate promote self-directed learning through flexible access, personalized feedback, and autonomous practice, improving vocabulary, grammar, and productive skills. Second, AI fosters adaptive and sustainable learning by enhancing engagement, intrinsic motivation, and personalized learning experiences while reducing linguistic barriers in a supportive human-centered learning environment. Third, AI improves students’ learning experiences by increasing confidence and addressing limitations in language use. However, the risk of cognitive dependency remains, requiring balanced pedagogical strategies. These findings provide practical implications for higher education institutions and policymakers in designing AI-integrated, student-centered learning models. Overall, AI supports a more flexible, adaptive, and sustainable ELT environment.