AI-Driven Personalization in International University Admissions: A Case Study of Central Asian Student Success Rates

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@article{1708665,
      author = {Dana Maulenova},
      title = {AI-Driven Personalization in International University Admissions: A Case Study of Central Asian Student Success Rates},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {5},
      number = {9},
      pages = {764-773},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1708665.pdf},
      abstract = {The list of new progress in the world system of university admissions is driven further by the rise of artificial intelligence among the globalization-digitalization advances at present. In this paper, the effects of the personalized AI systems on the student?s achievement are studied when the Central Asian students continue their studies in the international institutions at high education level. The admissions landscape changes by means of AI-driven mechanisms which are initiated by smart application screening and grow to customized academic advisory interventions which can enhance student results and improve the diversity in universities. The introduction of technological systems has led to largely inadequate scientific investigation concerned with investigating impacts of such systems on students belonging to underrepresented Central Asian zones, represented by Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan. The research base is a mixed methods case study of AI enhanced admissions methods in three universities. The research integrates numerical performance figures relating to student retention with interviews with admissions personnel and the undergraduate participants. According to the study, AI personalization strategies assist Central Asian students in aligning their educational profiles with university offerings thus increasing the statistics of their academic performance. In spite of these positive outcomes, the study admits to the presence of algorithmic bias and culture differences that affect data collection of personalization algorithms. This research moves the discussion on the implementation of effective ethical AI systems at higher education forward by reporting location-specific results. Studies indicate that AI may provide opportunities for equal opportunities and achievement outcomes in global higher education but requires local design input and monitoring in AI system deployment. The stated research outcomes provide particular benefits to decision-makers in educational policy as well as university leadership teams and experts who create AI platforms.},
      keywords = {AI-Driven Personalization, International University Admissions, Central Asian Students, Student Success Rates, Educational Technology},
      month = {March},
  }