Designing an Education Database in a Higher Education Institution for the Data-Driven Management of the Educational Process

TA Kustitskaya, RV Esin, AA Kytmanov, TV Zykova - Education Sciences, 2023 - mdpi.com
During the past two decades, higher education institutions have been experiencing
challenges in transforming the traditional way of in-class teaching into blended learning …

A Comparison between Using Fuzzy Cognitive Mapping and Machine Learning to Predict Students' Performance in Higher Education

K Oqaidi, S Aouhassi… - 2022 IEEE 3rd International …, 2022 - ieeexplore.ieee.org
Higher education quality (HEQ) stakeholders increasingly see the student as the core of the
teaching operation. To improve HEQ a good prediction of students' performance is a …

Design of a Machine Learning Model to Predict Student Attrition.

T Fauszt, K Erdélyi, D Dobák… - … Journal of Emerging …, 2023 - search.ebscohost.com
Higher education institutions are facing a major issue with student dropout rates, which is a
global phenomenon that affects a significant portion of enrolled students, particularly those …

[PDF][PDF] Trustworthy and Explainable AI for Learning Analytics.

MJ Li, ST Li, ACM Yang, AYQ Huang, SJH Yang - LAK Workshops, 2024 - ceur-ws.org
In recent years, there has been a surge of interest in combining artificial intelligence (AI) with
education to enhance learning experiences. However, one major concern is the lack of …

AN EARLY WARNING SYSTEM FOR SCHOOL DROPOUT IN THE STATE OF ESPÍRITO SANTO: A MACHINE LEARNING APPROACH WITH VARIABLE SELECTION …

GAA Pereira, KD Demura, IC Nunes, KC Paula… - Pesquisa …, 2024 - SciELO Brasil
School dropout has significant consequences for individuals and society, including
increased crime, reduced productivity, and limited economic innovation. Identifying students …

Ethical Imperatives and Challenges: Review of the Use of Machine Learning for Predictive Analytics in Higher Education

E Barnes, J Hutson, K Perry - International …, 2024 - digitalcommons.lindenwood.edu
The escalating integration of machine learning (ML) in higher education necessitates a
critical examination of its ethical implications. This article conducts a comprehensive review …

Comparative analysis of performance of AutoML algorithms: Classification model of payment arrears in students of a private university

H Villarreal-Torres, J Ángeles-Morales… - EAI Endorsed …, 2024 - publications.eai.eu
The impact of artificial intelligence in our society is important due to the innovation of
processes through data science to know the academic and sociodemographic factors that …

Implementing a Risk Assessment System of Electric Welders' Muscle Injuries for Working Posture Detection with AI Technology.

C Ruengdech, S Howimanporn… - … Journal of Online & …, 2024 - search.ebscohost.com
Maintaining health and safety is essential for workers' quality of life, and thus, this has
become one of the main priorities for industrial enterprises. Electric welders want required …

Ameliorating Heart Diseases Prediction Using Machine Learning Technique for Optimal Solution.

N Narisetty, A Kalidindi… - … Journal of Online & …, 2023 - search.ebscohost.com
In the era of lacking physical fitness, folks in society are facing vital health complications
which can be due to a variety of reasons such as pollution, work pressure, food, and …

[HTML][HTML] Explaining Factors of Student Attrition at Higher Education

I Alcauter, L Martinez-Villasenor, H Ponce - Computación y Sistemas, 2023 - scielo.org.mx
The examination of student attrition within higher education is a dynamic field that seeks to
tackle the complex task of preventing dropout occurrences and formulating effective …