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Managing Machine Learning Integration in English Language Curriculum: Challenges and Innovations in Teacher Training Zailani Iman, Muhammad; Monic Veronica, Ayu; Airlangga Asis, Alfian
TechComp Innovations: Journal of Computer Science and Technology Vol. 2 No. 1 (2025): TechComp Innovations: Journal of Computer Science and Technology
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/techcompinnovations.v2i1.91

Abstract

The integration of machine learning (ML) into English language teaching is gaining traction due to its potential to support personalized learning and increase student engagement. However, its implementation presents critical challenges. Many educators lack the pedagogical training needed to use ML tools effectively, such as adaptive learning platforms and automated assessment systems. Institutional approaches often remain fragmented and reactive, offering limited support, vague curricular links, and few opportunities for collaboration. Ethical concerns—such as data privacy, algorithmic bias, and diminished teacher autonomy—further complicate the adoption process. This study employs a qualitative library research method to examine recent literature on ML in English education and teacher preparation. Results emphasize the need for inclusive training strategies, including blended learning, mentorship, and AI-focused modules, that enable teachers to use ML tools thoughtfully and ethically. Yet these efforts are still limited in reach, highlighting the importance of systemic reforms that ensure ethical and equitable ML integration across diverse educational contexts.
Establishment of a Special Education School for Women Nur Ihsan Purwanto, Ahmad; Siti Julaeha, Lia; Nur Fauziyah, Widya; Aprina Pradistya, Dhelia; Ziradine Syahrani, Hilda; Eka Salsabila, Indriyana; Salsabila, Jihan; Airlangga Asis, Alfian
SocietalServe: Journal of Community Engagement and Services Vol 1 No 2 (2024): Societal Serve: Journal of Community Engagement and Services
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/societalserve.v1i2.40

Abstract

This study explores the establishment of a specialized educational institution, The House of Humaira, aimed at empowering young Muslim women through a blend of homeschooling and boarding school methods. Located in Purwakarta, this initiative addresses the significant issue of gender disparities in education by providing a model that integrates Islamic principles with academic and cognitive development. Through targeted social outreach, financial planning, and operational management, the project enhances awareness of the importance of education for women, emphasizing their roles as future mothers and contributors to societal growth. By creating tailored educational programs and sustainable management systems, the initiative seeks to produce competent, productive, and cooperative young women, serving as a blueprint for similar institutions nationwide. Key outcomes include an operational framework, a financial planning template, and community engagement through digital platforms. This project underscores the critical role of education in fostering self-reliance and leadership among women, ensuring long-term societal impact.
Enhancing Personalized Learning: The Impact of Artificial Intelligence in Education Zailani Iman, Muhammad; Airlangga Asis, Alfian; Uzma Zein Rahma, Aynu
Edu Spectrum: Journal of Multidimensional Education Vol. 1 No. 2 (2024): Edu Spectrum: Journal of Multidimensional Education
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/eduspectrum.v1i2.55

Abstract

This research explores the transformative impact of artificial intelligence (AI) on personalized learning in educational settings. As traditional teaching methods struggle to cater to the diverse needs of students, AI offers innovative solutions that can tailor educational experiences to individual learning styles, preferences, and paces. This study investigates the various applications of AI technologies, including intelligent tutoring systems, adaptive learning platforms, and data-driven insights, to enhance personalized learning outcomes. By employing a mixed-methods approach that combines quantitative analysis of academic performance metrics with qualitative feedback from students and educators, the research aims to assess the effectiveness of AI-driven personalized learning initiatives. The findings reveal that AI not only improves student engagement and motivation but also facilitates differentiated instruction that addresses learning gaps and strengths. Additionally, the study identifies challenges such as data privacy concerns and the need for professional development for educators to effectively integrate AI solutions into their teaching practices. Ultimately, this research contributes to the ongoing discourse on the role of AI in education, offering actionable recommendations for educators and policymakers to optimize personalized learning experiences for all students.