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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Interpretable Dropout Prediction: Towards XAI-Based Personalized Intervention
Marcell Nagy, Roland Molontay
International Journal of Artificial Intelligence in Education (2023) Vol. 34, Iss. 2, pp. 274-300
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Predicting student dropouts with machine learning: An empirical study in Finnish higher education
Matti Vaarma, Hongxiu Li
Technology in Society (2024) Vol. 76, pp. 102474-102474
Open Access | Times Cited: 11
Could the Use of AI in Higher Education Hinder Students With Disabilities? A Scoping Review
Oriane Pierrès, Markus Christen, Felix Schmitt, et al.
IEEE Access (2024) Vol. 12, pp. 27810-27828
Open Access | Times Cited: 11
A Systematic Review of Generative AI and (English Medium Instruction) Higher Education
Peter Bannister, Alexandra Santamaría Urbieta, Elena Alcalde Peñalver
Aula Abierta (2023) Vol. 52, Iss. 4, pp. 401-409
Open Access | Times Cited: 15
The role of IoT and XAI convergence in the prediction, explanation, and decision of customer perceived value (CPV) in SMEs: a theoretical framework and research proposition perspective
Kwabena Abrokwah-Larbi
Discover Internet of Things (2025) Vol. 5, Iss. 1
Open Access
Educational Data Mining and Predictive Modeling in the Age of Artificial Intelligence: An In-Depth Analysis of Research Dynamics
Eloy López Menéses, Pedro C. Mellado-Moreno, Celia Gallardo Herrerías, et al.
Computers (2025) Vol. 14, Iss. 2, pp. 68-68
Open Access
Predicting University Dropout Rates Using Machine Learning: UniCt Case
Vincenzo Miracula, Francesco Mazzeo Rinaldi, Giovanni Giuffrida
Lecture notes in computer science (2025), pp. 55-66
Closed Access
Using Local Explainability to Analyze Learner Performance in Education
Lynda Dib, Laurence Capus
Lecture notes in networks and systems (2025), pp. 603-620
Closed Access
An Explainable AI-based Approach for Predicting Undergraduate Students Academic Performance
Fatema-Tuz- Johora, Muhammad Hasan, Aditya Rajbongshi, et al.
Array (2025), pp. 100384-100384
Open Access
Student dropout prediction through machine learning optimization: insights from moodle log data
Milena Soriano Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Model interpretability on private-safe oriented student dropout prediction
Hao Liu, Mao Mao, Xia Li, et al.
PLoS ONE (2025) Vol. 20, Iss. 3, pp. e0317726-e0317726
Open Access
A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment
Jingjing Liang, Jason M. Stephens, Gavin Brown
Frontiers in Education (2025) Vol. 10
Open Access
Deep FM-Based Predictive Model for Student Dropout in Online Classes
Nuha Alruwais
IEEE Access (2023) Vol. 11, pp. 96954-96970
Open Access | Times Cited: 9
Review on the Artificial Intelligence-based methods in Landslide Detection and Susceptibility Assessment: Current Progress and Future Directions
Yange Li, Bangjie Fu, Yueping Yin, et al.
Intelligent geoengineering. (2024) Vol. 1, Iss. 1, pp. 1-18
Open Access | Times Cited: 3
Interpretable Prediction of Student Dropout Using Explainable AI Models
Prasadini Padmasiri, Sanvitha Kasthuriarachchi
(2024), pp. 1-7
Closed Access | Times Cited: 2
Human-centered evaluation of explainable AI applications: a systematic review
Jenia Kim, Henry Maathuis, Danielle Sent
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access | Times Cited: 2
Towards Trustworthy and Explainable AI Educational Systems
Wasswa Shafik
(2024), pp. 17-41
Closed Access | Times Cited: 2
Predicting Student Attrition in University Courses
László Bognár
(2024), pp. 129-157
Closed Access | Times Cited: 1
Enhancing High-School Dropout Identification: A Collaborative Approach Integrating Human and Machine Insights
Okan Bulut, Tarid Wongvorachan, Surina He, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Enhancing high-school dropout identification: a collaborative approach integrating human and machine insights
Okan Bulut, Tarid Wongvorachan, Surina He, et al.
Discover Education (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 1
Balancing Performance and Explainability in Academic Dropout Prediction
Andrea Zanellati, Stefano Pio Zingaro, Maurizio Gabbrielli
IEEE Transactions on Learning Technologies (2024) Vol. 17, pp. 2140-2153
Open Access | Times Cited: 1
Leveraging Explainable AI Methods and Tools for Educational Data
Gabriella Casalino, Giovanna Castellano, Pietro Ducange, et al.
Communications in computer and information science (2024), pp. 95-111
Closed Access | Times Cited: 1
Why explainable AI may not be enough: predictions and mispredictions in decision making in education
Mohammed Saqr, Sonsoles López‐Pernas
Smart Learning Environments (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 1
Machine Learning Algorithms for Early Predicting Dropout Student Online Learning
Meta Amalya Dewi, Felix Indra Kurniadi, Dina Fitria Murad, et al.
(2023), pp. 1-4
Closed Access | Times Cited: 2
Exploring the Methodological Contexts and Constraints of Research in Artificial Intelligence in Education
Irene‐Angelica Chounta, Bibeg Limbu, Lisa van der Heyden
Lecture notes in computer science (2024), pp. 162-173
Closed Access
Predict Rich Learner School Dropout and Improve Success Rates Using a Datamining Study and Machine Learning Algorithms
M. Sabiri, Yousef Farhaoui, Saïd Agoujil
(2024), pp. 524-534
Closed Access
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