https://ojs.ijemd.com/index.php/ComputerScienceAI <p>International Journal of Emerging Multidisciplinaries: Computer Science &amp; Artificial Intelligence (IJEMD-CSAI) publishes research and review articles in the areas of theoretical and experimental studies in all fields of CS and AI. IJEMD-CSAI is an open access, free publication and peer-reviewed journal. Subscribed users can read, download, copy, distribute, print, search, or link to the full texts of the articles. Furthermore, there is no Article Processing Charges (APC) for publication of research articles. Authors must submit articles that have not been published elsewhere with a similarity index of less than 20%. </p> <p>The goal of IJEMD-CSAI is to publish original quality research papers that bring together the latest research and development in all areas of CS and AI. IJEMD-CSAI is published based on Continuous Article Publication (CAP) model. All research articles are indexed through unique links using the Digital Object Identifier (DOI) system by CrossRef. Estimated publication timeframe is within 2-4 months.</p> Publishing House International Enterprise en-US International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence 2791-0164 https://ojs.ijemd.com/index.php/ComputerScienceAI/article/view/385 <p>The process of selecting colleges and securing admissions is influenced by numerous elements, particularly academic performance, behavioral tendencies, and equity considerations. Academic metrics such as high school grades and standardized exam results often form the cornerstone of admission criteria. However, behavioral factors, including decision-making styles, personal motivations, and self-image, play an equally critical role in shaping students' application choices. For instance, while some students may aspire to enroll in elite universities, others, constrained by financial limitations or self-imposed doubts, might opt for less competitive institutions. Social influences, access to advisory resources like school counselors, and awareness of the admissions process further shape students' choices and behaviors. Students from underserved or marginalized communities often face additional hurdles, leading them to prioritize institutions based on proximity, affordability, or program flexibility that aligns with their unique needs. This paper explores agent-based modeling techniques adopted by international universities to study secondary education pathways and student behaviors in the context of admissions. By examining these models, the research highlights how they simulate complex decision-making processes and systemic interactions to foster equitable practices in university admissions. Emphasizing behavioral dimensions, these models underscore the importance of creating fairer systems that address the diverse needs and aspirations of students while promoting inclusivity and justice in higher education.</p> Suha Khalil Assayed Sana'a Alsayed Copyright (c) 2025 International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence https://creativecommons.org/licenses/by/4.0 2025-01-21 2025-01-21 4 1 8 8 10.54938/ijemdcsai.2025.04.1.385