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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:

Towards Predicting Student’s Dropout in University Courses Using Different Machine Learning Techniques
Janka Pecuchova, Martin Drlík
Applied Sciences (2021) Vol. 11, Iss. 7, pp. 3130-3130
Open Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

Recent advances in Predictive Learning Analytics: A decade systematic review (2012–2022)
Nabila Sghir, Amina Adadi, Mohammed Lahmer
Education and Information Technologies (2022) Vol. 28, Iss. 7, pp. 8299-8333
Open Access | Times Cited: 100
Predicting student's dropout in university classes using two-layer ensemble machine learning approach: A novel stacked generalization
Jovial Niyogisubizo, Lyuchao Liao, Eric Nziyumva, et al.
Computers and Education Artificial Intelligence (2022) Vol. 3, pp. 100066-100066
Open Access | Times Cited: 88
Student Retention Using Educational Data Mining and Predictive Analytics: A Systematic Literature Review
Dalia Abdulkareem Shafiq, Mohsen Marjani, Riyaz Ahamed Ariyaluran Habeeb, et al.
IEEE Access (2022) Vol. 10, pp. 72480-72503
Open Access | Times Cited: 72
All-Year Dropout Prediction Modeling and Analysis for University Students
Zihan Song, Sang-Ha Sung, Do-Myung Park, et al.
Applied Sciences (2023) Vol. 13, Iss. 2, pp. 1143-1143
Open Access | Times Cited: 23
Multi-Class Phased Prediction of Academic Performance and Dropout in Higher Education
M.V. Martins, Luís Baptista, Jorge Machado, et al.
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 4702-4702
Open Access | Times Cited: 12
A Comprehensive Review of Dropout Prediction Methods Based on Multivariate Analysed Features of MOOC Platforms
Saad Alghamdi, Ben Soh, Alice Li
Multimodal Technologies and Interaction (2025) Vol. 9, Iss. 1, pp. 3-3
Open Access
Early Identification of Vulnerable Students with Machine Learning Algorithms
Mohammad Awedh, Ahmed Mueen
WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS (2025) Vol. 22, pp. 166-188
Open Access
Rule-Based Expert System with Bayesian Theory and Fuzzy Inference for Vocational Guidance: A Tool to Prevent School Dropouts
C. Padilla Aranda
Lecture notes in computer science (2025), pp. 143-162
Closed Access
A Machine Learning Framework for Student Retention Policy Development: A Case Study
Sidika Hoca, Nazife Dimililer
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 2989-2989
Open Access
Factors and conditions that affect the goodness of machine learning models for predicting the success of learning
László Bognár, Tibor Fauszt
Computers and Education Artificial Intelligence (2022) Vol. 3, pp. 100100-100100
Open Access | Times Cited: 16
Preserving integrity in online assessment using feature engineering and machine learning
Manika Garg, Anita Goel
Expert Systems with Applications (2023) Vol. 225, pp. 120111-120111
Closed Access | Times Cited: 10
A review of machine learning methods used for educational data
Zara Ersozlu, Sona Taheri, Inge Koch
Education and Information Technologies (2024) Vol. 29, Iss. 16, pp. 22125-22145
Open Access | Times Cited: 3
Data Analytics and Machine Learning in Education
Juan A. Gómez‐Pulido, Young Joo Park, Ricardo Soto, et al.
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1418-1418
Open Access | Times Cited: 8
University Student Dropout Prediction Using Pretrained Language Models
Hyun-Sik Won, M Kim, Dohyun Kim, et al.
Applied Sciences (2023) Vol. 13, Iss. 12, pp. 7073-7073
Open Access | Times Cited: 7
How can valid and reliable automatic formative assessment predict the acquisition of learning outcomes?
Blaženka Divjak, Barbi Svetec, Damir Horvat
Journal of Computer Assisted Learning (2024) Vol. 40, Iss. 6, pp. 2616-2632
Closed Access | Times Cited: 2
AI in Preventing Dropout in Distance Higher Education: A Systematic Literature Review
Fatna Ennibras, Es-Saâdia Aoula, Bouchra Bouihi
(2024) Vol. 28, pp. 1-7
Closed Access | Times Cited: 2
Optimised SMOTE-based Imbalanced Learning for Student Dropout Prediction
Sheikh Wakie Masood, Munmi Gogoi, Shahin Ara Begum
Arabian Journal for Science and Engineering (2024)
Closed Access | Times Cited: 2
Mitigating Academic Institution Dropout Rates with Predictive Analytics Algorithms
Bongs Lainjo
International Journal of Education Teaching and Social Sciences (2023) Vol. 3, Iss. 1, pp. 29-49
Open Access | Times Cited: 6
Predicting Student Dropout based on Machine Learning and Deep Learning: A Systematic Review
Daniel Andrade-Girón, Juana Sandivar, William Joel Marín Rodriguez, et al.
ICST Transactions on Scalable Information Systems (2023)
Open Access | Times Cited: 6
Global challenges of students dropout: A prediction model development using machine learning algorithms on higher education datasets
Meseret Yihun Amare, Stanislava Šimonová
SHS Web of Conferences (2021) Vol. 129, pp. 09001-09001
Open Access | Times Cited: 14
The Effect of Resilience and Gender on the Persistence of Higher Education Students
Tímea Ceglédi, Hajnalka Fényes, Gabriella Pusztai
Social Sciences (2022) Vol. 11, Iss. 3, pp. 93-93
Open Access | Times Cited: 10
Using Virtual Learning Environment Data for the Development of Institutional Educational Policies
Emanuel Marques Queiroga, Carolina Rodríguez Enríquez, Cristian Cechinel, et al.
Applied Sciences (2021) Vol. 11, Iss. 15, pp. 6811-6811
Open Access | Times Cited: 13
Prognostic model for assessing the success of subject learning in conditions of digitalization of education
Mikhail V. Noskov, Yuliya V. Vaynshteyn, Marina Valerievna Somova, et al.
RUDN Journal of Informatization in Education (2023) Vol. 20, Iss. 1, pp. 7-19
Open Access | Times Cited: 5
Development of predictive model for students’ final grades using machine learning techniques
Nurul Habibah Abdul Rahman, Sahimel Azwal Sulaiman, Nor Azuana Ramli
AIP conference proceedings (2024) Vol. 3080, pp. 060003-060003
Open Access | Times Cited: 1
Mathematical model for early prediction of learning success
Michail Noskov, И. Б. Федотова, Marina Valerievna Somova, et al.
AIP conference proceedings (2024) Vol. 3045, pp. 070001-070001
Open Access | Times Cited: 1
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