Version 1
: Received: 12 August 2024 / Approved: 13 August 2024 / Online: 13 August 2024 (13:11:22 CEST)
How to cite:
DelaHoz-Dominguez, E.; Hijón-Neira, R. Recommender System for University Degree Selection: A Socioeconomic and Standardized Test Data Approach. Preprints2024, 2024080905. https://doi.org/10.20944/preprints202408.0905.v1
DelaHoz-Dominguez, E.; Hijón-Neira, R. Recommender System for University Degree Selection: A Socioeconomic and Standardized Test Data Approach. Preprints 2024, 2024080905. https://doi.org/10.20944/preprints202408.0905.v1
DelaHoz-Dominguez, E.; Hijón-Neira, R. Recommender System for University Degree Selection: A Socioeconomic and Standardized Test Data Approach. Preprints2024, 2024080905. https://doi.org/10.20944/preprints202408.0905.v1
APA Style
DelaHoz-Dominguez, E., & Hijón-Neira, R. (2024). Recommender System for University Degree Selection: A Socioeconomic and Standardized Test Data Approach. Preprints. https://doi.org/10.20944/preprints202408.0905.v1
Chicago/Turabian Style
DelaHoz-Dominguez, E. and Raquel Hijón-Neira. 2024 "Recommender System for University Degree Selection: A Socioeconomic and Standardized Test Data Approach" Preprints. https://doi.org/10.20944/preprints202408.0905.v1
Abstract
Recommender systems in education are becoming more widespread, typically focusing on recommending courses or study materials. This study proposes a machine learning approach to recommend a university degree based on high school and university standardised test results, incorporating students' socioeconomic information as input variables. The objective is to develop a tool for students’ decision-making, supporting the sustainable development goal of Quality Education by providing a data schema to maximise the likelihood of a successful match between the student's profile and the academic program. With its focus on equity in education, this study provides a data-driven approach to assist students in selecting suitable university degrees, aiming to improve educational outcomes and inspire a more equitable education system.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
