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José M. Ortiz-Lozano, Pilar Aparicio-Chueca, Xavier M. Triadó-Ivern & Jose Luis Arroyo-Barrigüete. (2023) Early dropout predictors in social sciences and management degree students. Studies in Higher Education 0:0, pages 1-14.
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Italo Testa, Silvia Galano & Oreste Tarallo. (2023) The relationships between freshmen’s accuracy of self-evaluation and the likelihood of succeeding in chemistry and physics exams in two STEM undergraduate courses. International Journal of Science Education 45:5, pages 358-382.
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Emilio Jesús Lizarte Simón & José Gijón Puerta. (2022) Prediction of early dropout in higher education using the SCPQ. Cogent Psychology 9:1.
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Jarintorn Wintachai, Thi Diem Hang Khong & Eisuke Saito. (2021) COVID-19 as a game changer in a Thai university: a self-reflection. PRACTICE 3:1, pages 51-57.
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Agostino Cioffi, Silvia Galano, Raffaella Passeggia & Italo Testa. (2024) Validation of two test anxiety scales for physics undergraduate courses through confirmatory factor analysis and Rasch analysis. Physical Review Physics Education Research 20:1.
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Dominik Glandorf, Hye Rin Lee, Gabe Avakian Orona, Marina Pumptow, Renzhe Yu & Christian Fischer. (2024) Temporal and Between-Group Variability in College Dropout Prediction. Temporal and Between-Group Variability in College Dropout Prediction.
Wahid Sabbir, Md Abdullah-Al-Kafi, Arafat Sahin Afridi, Md. Sadekur Rahman & Mousumi Karmakar. (2024) Improving Predictive Analytics for Student Dropout: A Comprehensive Analysis and Model Evaluation. Improving Predictive Analytics for Student Dropout: A Comprehensive Analysis and Model Evaluation.
Miguel A. Alonso, Aitana González-Ortiz-de-Zárate, M. Ángeles Gómez-Flechoso & Marco Castrillón. (2024) Effectiveness of a Peer Mentoring on University Dropout and Academic Performance. Psicología Educativa 30:1, pages 29-37.
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Müyesser ERASLAN YALÇIN & Sevinç GÜLSEÇEN. (2023) Undergraduate Dropout Intentions in Turkey: A Systematic Review of Factors and ImplicationsÜniversite Öğrencilerinin Okulu Bırakma Niyetleri Türkiye Örneği: Faktörlerin ve Sonuçlarının Sistematik Bir İncelemesi. Eğitim ve Toplum Araştırmaları Dergisi.
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Yiyi Liu, Zijie Huang & Gong Wang. (2023) Student learning performance prediction based on online behavior: an empirical study during the COVID-19 pandemic. PeerJ Computer Science 9, pages e1699.
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Juan Sebastián Parra-Sánchez, Ingrid Durley Torres Pardo & Carmen Ysabel Martínez De Merino. (2023) Factores explicativos de la deserción universitaria abordados mediante inteligencia artificial. Revista Electrónica de Investigación Educativa 25, pages 1-17.
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Tamás Martos, Balázs Jagodics, Judit Kőrössy & Éva Szabó. (2021) Psychological resources, dropout risk and academic performance in university students – pattern-oriented analysis and prospective study of Hungarian freshmen. Current Psychology 42:10, pages 8051-8065.
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Rannveig Grøm Sæle, Tove Irene Dahl, Tore Sørlie & Oddgeir Friborg. (2023)
Note to first-year university students: Just do it! In the end, the fact
that
you study may be more important than
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Juan-Carlos de la Cruz-Campos, Juan-José Victoria-Maldonado, José-Antonio Martínez-Domingo & María-Natalia Campos-Soto. (2023) Causes of academic dropout in higher education in Andalusia and proposals for its prevention at university: A systematic review. Frontiers in Education 8.
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Roberto Bertolini, Stephen J. Finch & Ross H. Nehm. (2023) An application of Bayesian inference to examine student retention and attrition in the STEM classroom. Frontiers in Education 8.
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Nurmalitasari, Zalizah Awang Long & Mohammad Faizuddin Mohd Noor. (2023) Factors Influencing Dropout Students in Higher Education. Education Research International 2023, pages 1-13.
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Rodolfo Sanches Santos, Moacir Antonelli Ponti & Kamila Rios Rodrigues. 2023. Intelligent Systems. Intelligent Systems
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Danika Dorris, Julie Ivy & Julie Swann. (2022) An Approach to Population Synthesis of Engineering Students for Understanding Dropout Risk. An Approach to Population Synthesis of Engineering Students for Understanding Dropout Risk.
Amina Ouatiq, Sophia Faris, Khalifa Mansouri & Mohammed Qbadou. (2022) Towards the Use of teacher-chosen features to predict students’ performance. Towards the Use of teacher-chosen features to predict students’ performance.
Dalia Abdulkareem Shafiq, Mohsen Marjani, Riyaz Ahamed Ariyaluran Habeeb & David Asirvatham. (2022) A Conceptual Predictive Analytics Model for the Identification of at-risk students in VLE using Machine Learning Techniques. A Conceptual Predictive Analytics Model for the Identification of at-risk students in VLE using Machine Learning Techniques.
Adriano Bressane, Marianne Spalding, Daniel Zwirn, Anna Isabel Silva Loureiro, Abayomi Oluwatobiloba Bankole, Rogério Galante Negri, Irineu de Brito Junior, Jorge Kennety Silva Formiga, Liliam César de Castro Medeiros, Luana Albertani Pampuch Bortolozo & Rodrigo Moruzzi. (2022) Fuzzy Artificial Intelligence—Based Model Proposal to Forecast Student Performance and Retention Risk in Engineering Education: An Alternative for Handling with Small Data. Sustainability 14:21, pages 14071.
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Marina Segura, Jorge Mello & Adolfo Hernández. (2022) Machine Learning Prediction of University Student Dropout: Does Preference Play a Key Role?. Mathematics 10:18, pages 3359.
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Hsiang-Wen Hsing, Nathan Lau & Diana Bairaktarova. (2022) Relationships of eye gaze metrics between cognitive processes and strategy in spatial problem-solving. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66:1, pages 480-484.
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Parina Yamjal & Ahmed AL-Sa’di. (2022) STRATEGIES FOR RETENTION AND COMPLETION IN VOCATIONAL EDUCATION: FACULTY PERSPECTIVES. Journal of Management and Business Education 5:4, pages 247-265.
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Si Na Kew & Zaidatun Tasir. (2022) Developing a Learning Analytics Intervention in E-learning to Enhance Students’ Learning Performance: A Case Study. Education and Information Technologies 27:5, pages 7099-7134.
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Mauricio Barramuño, Claudia Meza-Narváez & Germán Gálvez-García. (2021) Prediction of student attrition risk using machine learning. Journal of Applied Research in Higher Education 14:3, pages 974-986.
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Teng Guo, Xiaomei Bai, Xue Tian, Selena Firmin & Feng Xia. (2022) Educational Anomaly Analytics: Features, Methods, and Challenges. Frontiers in Big Data 4.
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Jorge Maluenda-Albornoz, Valeria Infante-Villagrán, Celia Galve-González, Gabriela Flores-Oyarzo & José Berríos-Riquelme. (2022) Early and Dynamic Socio-Academic Variables Related to Dropout Intention: A Predictive Model Made during the Pandemic. Sustainability 14:2, pages 831.
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Dalia Abdulkareem Shafiq, Mohsen Marjani, Riyaz Ahamed Ariyaluran Habeeb & David Asirvatham. (2022) Student Retention Using Educational Data Mining and Predictive Analytics: A Systematic Literature Review. IEEE Access 10, pages 72480-72503.
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Rodolfo S. S. dos Santos, Moacir A. Ponti & Kamila Rios da Hora Rodrigues. 2022. Human Interface and the Management of Information: Visual and Information Design. Human Interface and the Management of Information: Visual and Information Design
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Mariano Méndez Suárez & Natividad Crespo Tejero. (2021) Impact of absenteeism on academic performance under compulsory attendance policies in first to fifth year university students. Revista Complutense de Educación 32:4, pages 627-637.
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Jeovani Schmitt, Maria Inês Fini, Cyntia Bailer, Rosangela Fritsch & Dalton Francisco de Andrade. (2020) WWH-dropout scale: when, why and how to measure propensity to drop out of undergraduate courses. Journal of Applied Research in Higher Education 13:2, pages 540-560.
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Italo Testa, Giuliana Capasso, Arturo Colantonio, Silvia Galano, Irene Marzoli, Umberto Scotti di Uccio & Gaspare Serroni. 2020. Rasch Measurement. Rasch Measurement
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Alvaro Ortigosa, Rosa M. Carro, Javier Bravo-Agapito, David Lizcano, Juan Jesus Alcolea & Oscar Blanco. (2019) From Lab to Production: Lessons Learnt and Real-Life Challenges of an Early Student-Dropout Prevention System. IEEE Transactions on Learning Technologies 12:2, pages 264-277.
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Muhammad Irfan Abid & Zeashan Hameed Khan. (2018) Towards a Holistic Approach to Improve the Retention Rate of Freshmen in Engineering. Towards a Holistic Approach to Improve the Retention Rate of Freshmen in Engineering.