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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 Deep Learning for University Dropout Prediction
Máté Baranyi, Marcell Nagy, Roland Molontay
(2020), pp. 13-19
Closed Access | Times Cited: 54

Showing 26-50 of 54 citing articles:

Machine learning evidence from PISA 2018 data to integrate global competence intervention in UAE K–12 public schools
Xin Miao, Ali Nadaf, Zhuotong Zhou
International Review of Education (2023) Vol. 69, Iss. 5, pp. 675-690
Closed Access | Times Cited: 4
A hybrid approach for early-identification of at-risk dropout students using LSTM-DNN networks
Houssam El Aouifi, Mohamed El Hajji, Youssef Es-Saady
Education and Information Technologies (2024) Vol. 29, Iss. 14, pp. 18839-18857
Closed Access | Times Cited: 1
SDA-Vis: A Visualization System for Student Dropout Analysis Based on Counterfactual Exploration
Germain Garcia-Zanabria, Daniel A. Gutierrez-Pachas, Guillermo Cámara-Chávez, et al.
Applied Sciences (2022) Vol. 12, Iss. 12, pp. 5785-5785
Open Access | Times Cited: 7
CNN autoencoders and LSTM-based reduced order model for student dropout prediction
Ke Niu, Guoqiang Lu, Xueping Peng, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 30, pp. 22341-22357
Closed Access | Times Cited: 3
XAI-Based Student Performance Prediction: Peeling Back the Layers of LSTM and Random Forest’s Black Boxes
Navin Kartik, R. Mahalakshmi, K. A. Venkatesh
SN Computer Science (2023) Vol. 4, Iss. 5
Closed Access | Times Cited: 3
Exploring statistical approaches for predicting student dropout in education: a systematic review and meta-analysis
Raghul Gandhi Venkatesan, Dhivya Karmegam, Bagavandas Mappillairaju
Journal of Computational Social Science (2023) Vol. 7, Iss. 1, pp. 171-196
Closed Access | Times Cited: 3
A Comparison between Using Fuzzy Cognitive Mapping and Machine Learning to Predict Students’ Performance in Higher Education
Khalid Oqaidi, Sarah Aouhassi, Khalifa Mansouri
(2022)
Closed Access | Times Cited: 5
Ripple: Concept-Based Interpretation for Raw Time Series Models in Education
Mohammad Asadi, Vinitra Swamy, Jibril Frej, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 13, pp. 15903-15911
Open Access | Times Cited: 2
E-Learning at-Risk Group Prediction Considering the Semester and Realistic Factors
Chenglong Zhang, Hyunchul Ahn
Education Sciences (2023) Vol. 13, Iss. 11, pp. 1130-1130
Open Access | Times Cited: 2
Not Another Hardcoded Solution to the Student Dropout Prediction Problem: A Novel Approach Using Genetic Algorithms for Feature Selection
Yixin Cheng, Bernardo Pereira Nunes, Rubén Manrique
Lecture notes in computer science (2022), pp. 238-251
Closed Access | Times Cited: 4
Predicting Student Performance to Boost Educational Outcomes: The Efficacy of a Random Forest Approach
Florlyn Mae C. Remegio
(2024) Vol. 23, pp. 253-260
Closed Access
Predicting the Risk of Course Change in Online Education Using the Causal Shapley Method
Miki Katsuragi, Kenji Tanaka
(2024) Vol. 33, pp. 13-17
Closed Access
Student Attrition in Higher Education: A Systematic Mapping of Causes and Retention Strategies
Luz Marina Zaparan-Cardona, Mariana Isabel Cervantes-Lozano, Ramón García-González, et al.
Communications in computer and information science (2024), pp. 163-178
Closed Access
Predição da evasão estudantil: uma análise comparativa de diferentes representações de treino na aprendizagem de modelos genéricos
Miriam Pizzatto Colpo, Tiago Thompsen Primo, Marílton Sanchotene de Aguiar
Anais do XXXII Simpósio Brasileiro de Informática na Educação (SBIE 2021) (2021), pp. 873-884
Open Access | Times Cited: 4
Investigação da Evasão Estudantil por meio da Mineração de Dados e Aprendizagem de Máquina: Um Mapeamento Sistemático
Jeferson Andrade de Jesus, Renê Pereira de Gusmão
Revista Brasileira de Informática na Educação (2024) Vol. 32
Open Access
Educational Data Mining for Dropout Prediction: Trends, Opportunities, and Challenges
Miriam Pizzatto Colpo, Tiago Thompsen Primo, Marílton Sanchotene de Aguiar, et al.
Revista Brasileira de Informática na Educação (2024) Vol. 32, pp. 220-256
Open Access
Prediction of MOOCs Dropout Based on IQPSO-PLSTM Model
Xiao Chen, Hanqiang Liu, Feng Zhao
(2023), pp. 7-12
Closed Access | Times Cited: 1
Generating and Understanding Predictive Models for Student Attrition in Public Higher Education
Tiago De Souza Fernandes, Guilherme Ramos
2021 IEEE Frontiers in Education Conference (FIE) (2023), pp. 1-5
Closed Access | Times Cited: 1
Student Dropout Prediction in High Education, Using Machine Learning and Deep Learning Models: Case of Ecuadorian University
Gonzalo Dávila, Juan Haro, Alexandra González-Eras, et al.
2021 International Conference on Computational Science and Computational Intelligence (CSCI) (2023), pp. 1677-1684
Closed Access | Times Cited: 1
Comparing Automated Machine Learning Against an Off-the-Shelf Pattern-Based Classifier in a Class Imbalance Problem: Predicting University Dropout
Leonardo Cañete-Sifuentes, Vı́ctor Robles, Ernestina Menasalvas, et al.
IEEE Access (2023) Vol. 11, pp. 139147-139156
Open Access | Times Cited: 1
Dropout Prediction by Interpretable Machine Learning Model Towards Preventing Student Dropout
Miki Katsuragi, Kenji Tanaka
Advances in transdisciplinary engineering (2022)
Open Access | Times Cited: 2
A Case Study of Interpretable Counterfactual Explanations for the Task of Predicting Student Academic Performance
Maria Tsiakmaki, O. Ragos
(2021) Vol. 51, pp. 120-125
Closed Access | Times Cited: 2
Academic Performance Evaluation Using Data Mining in Times of Pandemic
Edgar Taya Acosta, Hugo Manuel Barraza Vizcarra, Ruth de Jesus Ramirez-Rejas, et al.
TECHNO REVIEW International Technology Science and Society Review /Revista Internacional de Tecnología Ciencia y Sociedad (2022) Vol. 11, Iss. 1, pp. 89-106
Closed Access | Times Cited: 1
Lemorzsolódás előrejelzése személyre szabott értelmezhető gépi tanulási módszerek segítségével
Marcell Nagy
Scientia et Securitas (2023) Vol. 3, Iss. 3, pp. 270-281
Open Access
Educational Data Science: An “Umbrella Term” or an Emergent Domain?
Alejandro Peña‐Ayala
Big data management (2023), pp. 95-147
Closed Access

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