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Artificial Intelligence in Study-Abroad Program Recommendations

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 411))

Abstract

Students willing to study abroad may find it challenging to go through tons of website pages on the application process. The complication of the studying-abroad application process makes it even harder for many students to figure out their dream and fit schools. With artificial intelligence being widely promoted across different subjects and disciplines, we made attempts to incorporate artificial intelligence into education program recommendations. We thus designed a recommendation system for studying-abroad programs through the K-nearest neighbor algorithm. The designed system may recommend up to six colleges and universities to students according to their input of grade average points, language testing scores, acceptable fees, target majors, and location preference. In addition, the analysis of the application plan and the report on the academic entrance requirements are also offered through the system. The project simplifies the application process and thus saves the time and energy of the applicants.

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Correspondence to Yang Gao .

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Gao, Y., Wang, X., Shi, J., Liu, Z., Wei, Z. (2022). Artificial Intelligence in Study-Abroad Program Recommendations. In: Auer, M.E., Tsiatsos, T. (eds) New Realities, Mobile Systems and Applications. IMCL 2021. Lecture Notes in Networks and Systems, vol 411. Springer, Cham. https://doi.org/10.1007/978-3-030-96296-8_92

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  • DOI: https://doi.org/10.1007/978-3-030-96296-8_92

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-96295-1

  • Online ISBN: 978-3-030-96296-8

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