An empirical survey on explainable ai technologies: Recent trends, use-cases, and categories from technical and application perspectives

M Nagahisarchoghaei, N Nur, L Cummins, N Nur… - Electronics, 2023 - mdpi.com
In a wide range of industries and academic fields, artificial intelligence is becoming
increasingly prevalent. AI models are taking on more crucial decision-making tasks as they …

Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning

E ŞAHiN, NN Arslan, D Özdemir - Neural Computing and Applications, 2024 - Springer
Deep learning models have revolutionized numerous fields, yet their decision-making
processes often remain opaque, earning them the characterization of “black-box” models …

Analysis of an Explainable Student Performance Prediction Model in an Introductory Programming Course.

M Hoq, P Brusilovsky, B Akram - International Educational Data Mining …, 2023 - ERIC
Prediction of student performance in introductory programming courses can assist struggling
students and improve their persistence. On the other hand, it is important for the prediction to …

Clustering-based knowledge graphs and entity-relation representation improves the detection of at risk students

B Albreiki, T Habuza, N Palakkal, N Zaki - Education and Information …, 2024 - Springer
The nature of education has been transformed by technological advances and online
learning platforms, providing educational institutions with more options than ever to thrive in …

Transforming educational insights: Strategic integration of federated learning for enhanced prediction of student learning outcomes

U Farooq, S Naseem, T Mahmood, J Li… - The Journal of …, 2024 - Springer
Numerous educational institutions utilize data mining techniques to manage student
records, particularly those related to academic achievements, which are essential in …

Exploring the Connectivity Between Education 4.0 and Classroom 4.0: Technologies, Student Perspectives, and Engagement in the Digital Era

K Joshi, R Kumar, S Bharany, DKJB Saini… - IEEE …, 2024 - ieeexplore.ieee.org
The democratic welfare government is equally committed to quality-driven, impartial, and
egalitarian education. The major contribution of this study is to examine the problems and …

Predicting Student Performance in Online Learning: A Multidimensional Time-Series Data Analysis Approach

Z Shou, M Xie, J Mo, H Zhang - Applied Sciences, 2024 - mdpi.com
As an emerging teaching method, online learning is becoming increasingly popular among
learners. However, one of the major drawbacks of this learning style is the lack of effective …

Improving academic performance predictions with dual graph neural networks

Q Huang, Y Zeng - Complex & Intelligent Systems, 2024 - Springer
Academic performance is a crucial issue in the field of Online learning analytics. While deep
learning-based models have made significant progress in the era of big data, many of these …

Optimization and Scalability of Educational Platforms: Integration of Artificial Intelligence and Cloud Computing

J Govea, E Ocampo Edye, S Revelo-Tapia… - Computers, 2023 - mdpi.com
The intersection between technology and education has taken on unprecedented relevance,
driven by the promise of transforming teaching and learning through advanced digital tools …

Explainable Machine Learning Prediction for the Academic Performance of Deaf Scholars

NR Raji, RMS Kumar, CL Biji - IEEE Access, 2024 - ieeexplore.ieee.org
Deaf and Hard of Hearing (DHH) students encounter obstacles in higher education due to
language and communication challenges. Although research aims to improve their …