University Recommendation System for Higher Studies in USA

Abstract

With the increasing number of graduates seeking to pursue higher education, getting a student's admission into the university becomes more challenging. New graduate students are typically unaware of the postgraduate admission criteria and procedures and may spend a substantial amount of time obtaining guidance from consulting firms to help them define their admission opportunities. But this methodology can be biased and misleading considering the small number of universities that a human consultant may consider. Thus, a machine learning approach was built in this paper to automatically predict the prospects for postgraduate admissions, enabling graduates to recognise and target the most appropriate universities for their profile. The University Recommendation System for Higher Studies is a system framework that prescribes universities for students or users of the system who recommend universities to students looking for education for their higher studies. The main parameters used to recommend university are CGPA percentages, GRE Score, TOFEL Score, university rank, etc. This system uses machine learning algorithms and compares the accuracy of the algorithms.

Could the Use of AI in Higher Education Hinder Students With Disabilities? A Scoping Review

“…In profiling and prediction applications, three types of decisions were identified: 1) identification of students at risk of dropping out of a course, study programme, or school [20], [42], [46], [47], [49], [51]- [63], 2) prediction of student performance prior to their admission [21], [64]- [67], 3) identification of students' learning profile [43], [50], [68]. The first two types of decisions have a more significant impact on access to studies than the last one.…”

“…This type of decision has a rather low impact as it simply provides a list of courses or materials that could be of interest to students. In comparison, five articles utilised AI to recommend higher education institutions or programmes to students [21], [64]- [67]. These recommendations can potentially impact students' decision to apply to a specific programme or university, impacting their future job and salaries.…”

“…These applications provide a list of recommendations. Some also added a percentage of success to the recommendations [65], [67].…”

The Barcelona Conference on Education 2023: Official Conference Proceedings

“…Knowing the educational context allows directing efforts towards educational quality objectives. The commonly identified educational levels are primary, secondary, higher (da Silva et al, 2022) and postgraduate (Nalawade & Tiple, 2022), however, the U.S. educational system includes K-12 schools, the "K" refers to "Kindergarten", which is the first year of formal education, and the "12" refers to the 12 years of education that includes primary and secondary (Zayet et al, 2022). It should be noted that some ERS were implemented for 2 or more levels and the same happens with educational modalities; some articles indicated that ERS were used in 2 or more modalities.…”