Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020
As online learning has been widely adopted in higher education in recent years, artificial
intelligence (AI) has brought new ways for improving instruction and learning in online …
intelligence (AI) has brought new ways for improving instruction and learning in online …
Analyzing and predicting students' performance by means of machine learning: A review
JL Rastrollo-Guerrero, JA Gómez-Pulido… - Applied sciences, 2020 - mdpi.com
Predicting students' performance is one of the most important topics for learning contexts
such as schools and universities, since it helps to design effective mechanisms that improve …
such as schools and universities, since it helps to design effective mechanisms that improve …
[图书][B] An introduction to ethics in robotics and AI
This open access book introduces the reader to the foundations of AI and ethics. It discusses
issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between …
issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between …
Educational data mining to predict students' academic performance: A survey study
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …
education and informatics. It has become an imperative research area due to many …
Using machine learning to predict student difficulties from learning session data
The student's performance prediction is an important research topic because it can help
teachers prevent students from dropping out before final exams and identify students that …
teachers prevent students from dropping out before final exams and identify students that …
Predicting student dropout in higher education
L Aulck, N Velagapudi, J Blumenstock… - arXiv preprint arXiv …, 2016 - arxiv.org
Each year, roughly 30% of first-year students at US baccalaureate institutions do not return
for their second year and over $9 billion is spent educating these students. Yet, little …
for their second year and over $9 billion is spent educating these students. Yet, little …
Dropout prediction in e-learning courses through the combination of machine learning techniques
I Lykourentzou, I Giannoukos, V Nikolopoulos… - Computers & …, 2009 - Elsevier
In this paper, a dropout prediction method for e-learning courses, based on three popular
machine learning techniques and detailed student data, is proposed. The machine learning …
machine learning techniques and detailed student data, is proposed. The machine learning …
Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data
Predicting student failure at school has become a difficult challenge due to both the high
number of factors that can affect the low performance of students and the imbalanced nature …
number of factors that can affect the low performance of students and the imbalanced nature …
Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades
SB Kotsiantis - Artificial Intelligence Review, 2012 - Springer
Use of machine learning techniques for educational proposes (or educational data mining)
is an emerging field aimed at developing methods of exploring data from computational …
is an emerging field aimed at developing methods of exploring data from computational …
Predicting school failure and dropout by using data mining techniques
C Márquez-Vera, CR Morales… - … de Tecnologias del …, 2013 - ieeexplore.ieee.org
This paper proposes to apply data mining techniques to predict school failure and dropout.
We use real data on 670 middle-school students from Zacatecas, México, and employ white …
We use real data on 670 middle-school students from Zacatecas, México, and employ white …