Systematic review of research on artificial intelligence applications in higher education–where are the educators?

O Zawacki-Richter, VI Marín, M Bond… - International Journal of …, 2019 - Springer
According to various international reports, Artificial Intelligence in Education (AIEd) is one of
the currently emerging fields in educational technology. Whilst it has been around for about …

Recent advances in deep learning theory

F He, D Tao - arXiv preprint arXiv:2012.10931, 2020 - arxiv.org
Deep learning is usually described as an experiment-driven field under continuous criticizes
of lacking theoretical foundations. This problem has been partially fixed by a large volume of …

[HTML][HTML] Empowering educators to be AI-ready

R Luckin, M Cukurova, C Kent, B Du Boulay - Computers and Education …, 2022 - Elsevier
In this paper, we present the concept of AI Readiness, along with a framework for
developing AI Readiness training.'AI Readiness' can be framed as a contextualised way of …

Implications of AI (un-) fairness in higher education admissions: the effects of perceived AI (un-) fairness on exit, voice and organizational reputation

F Marcinkowski, K Kieslich, C Starke… - Proceedings of the 2020 …, 2020 - dl.acm.org
Algorithmic decision-making (ADM) is becoming increasingly important in all areas of social
life. In higher education, machine-learning systems have manifold uses because they can …

Harnessing Artificial Intelligence for innovation in education

S Tan - … Innovative and digital transformative learning strategies …, 2023 - Springer
In the field of educational technology, Artificial Intelligence in Education (AIEd) is an
emerging field that is projected to have a profound impact on the teaching and learning …

Toward predicting student's academic performance using artificial neural networks (ANNs)

Y Baashar, G Alkawsi, A Mustafa, AA Alkahtani… - Applied Sciences, 2022 - mdpi.com
Student performance is related to complex and correlated factors. The implementation of a
new advancement of technologies in educational displacement has unlimited potentials …

A practical model for the evaluation of high school student performance based on machine learning

M Zafari, A Sadeghi-Niaraki, SM Choi, A Esmaeily - Applied Sciences, 2021 - mdpi.com
The objective of this research is to develop an machine learning (ML)-based system that
evaluates the performance of high school students during the semester and identify the most …

A practical model for educators to predict student performance in K-12 education using machine learning

JL Harvey, SAP Kumar - 2019 IEEE symposium series on …, 2019 - ieeexplore.ieee.org
Predicting classifiers can be used to analyze data in K-12 education. Creating a
classification model to accurately identify factors affecting student performance can be …

A new adaptive Cuckoo search algorithm

M Naik, MR Nath, A Wunnava… - 2015 IEEE 2nd …, 2015 - ieeexplore.ieee.org
This paper presents a new adaptive Cuckoo search (ACS) algorithm based on the Cuckoo
search (CS) for optimization. The main thrust is to decide the step size adaptively from its …

A decision support system for predicting students' performance

I Livieris, T Mikropoulos, P Pintelas - Themes in Science and …, 2016 - learntechlib.org
Educational data mining is an emerging research field concerned with developing methods
for exploring the unique types of data that come from educational context. These data allow …