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Journal : Journal of Computer Science and Technology Application

The Impact of Educational Information Systems on Learning Accessibility in Higher Education Sudadi Pranata; Arif Komara, Maulana; Amelia, Fhia; Rangi, Noah
CORISINTA Vol 2 No 2 (2025): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i2.132

Abstract

This study explores the impact of educational information systems on enhancing learning accessibility in higher education, as digital tools increasingly become integral to academic support, and student engagement. The main objective is to assess how these systems improve access to learning resources and facilitate communication, particularly for students from diverse backgrounds and with varying educational needs. Using a mixed-methods approach, this research combines quantitative analysis of accessibility metrics with qualitative insights from surveys and interviews with students and faculty across different higher education institutions. The findings show that educational information systems significantly enhance learning accessibility by providing flexible access to resources, facilitating real-time feedback, and supporting personalized learning paths. These systems also improve student engagement by enabling convenient access to materials and fostering a collaborative learning environment that accommodates different learning styles. However, the study identifies several barriers, including gaps in digital literacy, usability challenges, and unequal access to the necessary infrastructure, which can limit the effectiveness of these systems in reaching all students equally. Additionally, concerns around data privacy and system complexity are noted as areas needing attention to build user trust and ensure smoother system integration. The study concludes that while educational information systems hold great promise for improving accessibility and inclusivity in higher education, addressing these barriers through targeted training, digital equity initiatives, and robust data protection policies is essential for maximizing their potential. These insights offer valuable guidance for educational institutions aiming to create more inclusive learning environments through strategic integration of educational information systems.
Accelerating Time to Market through Agile in AI Innovation Sibagariang, Susy Alestriani; Farisha Andi Baso; Nugroho Prihantoni; Rangi, Noah
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/f13hsp59

Abstract

Rapid digital transformation, driven by the increasing integration of Artificial Intelligence (AI) into digital products and services, has intensified competition across industries and positioned Time-to-Market (TTM) as a critical success factor for digital innovation projects. AI-oriented development requires rapid iteration, continuous data processing, and frequent model refinement, which are often difficult to support using traditional project management approaches, leading to delayed deployment and reduced adaptability. In this context, agile methodologies have emerged as a flexible and adaptive framework that aligns well with the iterative and data-driven nature of AI development. This study examines the impact of agile adoption on TTM performance in digital innovation projects, particularly those involving AI-enabled components, using a qualitative multiple-case study design based on semi-structured interviews with product managers, developers, and agile practitioners, complemented by analysis of project documentation, AI workflows, and delivery metrics. The findings show that organizations adopting agile methodologies achieve a development cycle time reduction of approximately 25% to 40% within the first two years of implementation, supported by key practices such as iterative sprint development, cross-functional collaboration between engineering and data teams, continuous feedback loops, and early testing of AI components. Overall, the study confirms that agile methodologies serve as an effective strategic mechanism for accelerating TTM in AI-driven digital innovation projects.