Search Results - Algorithms. Programming. Failure. Dropout

Profiling the Skill Mastery of Introductory Programming Students: A Cognitive Diagnostic Modeling Approach

Authors: Manuel B. Garcia (ORCID 0000-0003-2615-422X)

Source: Education and Information Technologies. 2025 30(5):6455-6481.

Peer Reviewed: Y

Page Count: 27

Descriptors: Programming, Introductory Courses, Computer Science Education, Mastery Learning, Demand Occupations, Global Approach, Employees, Dropout Rate, Cognitive Measurement, Models, Information Technology, Computer Science, College Students, Academic Standards, Program Development, Dropout Attitudes, Dropout Research, Comparative Analysis, Logical Thinking, Algorithms

LEARNING DIFFICULTIES AND MOTIVATING FACTORS FOR STUDYING PROGRAMMING: WHAT HAS CHANGED SINCE THE 2018 STUDIES IN THE IT COURSE AT UFERSA, PAU DOS FERROS CAMPUS? ; DIFICULTADES DE APRENDIZAJE Y FACTORES MOTIVADORES PARA ESTUDIAR PROGRAMACIÓN: ¿QUÉ HA CAMBIADO DESDE LOS ESTUDIOS DE 2018 EN EL CURSO DE TI DE LA UFERSA, CAMPUS PAU DOS FERROS? ; DIFICULDADES DE APRENDIZAGEM E FATORES QUE MOTIVAM PARA O ESTUDO PARA PROGRAMAÇÃO: O QUE MUDOU DESDE OS ESTUDOS DE 2018 NO CURSO DE TI DA UFERSA, CAMPUS PAU DOS FERROS?

Authors: Camara Pereira, Kleber Rolim de Sousa, Reudismam

Source: RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218; Vol. 5 No. 4 (2024): CLICK HERE TO ACCESS THE ARTICLES; e545151 ; RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218; Vol. 5 Núm. 4 (2024): HAGA CLIC AQUÍ PARA ACCEDER A LOS ARTÍCULOS; e545151 ; RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218; v. 5 n. 4 (2024): CLIQUE AQUI PARA ACESSAR OS ARTIGOS; e545151 ; RECIMA21 -Revista Científica Multidisciplinar - ISSN 2675-6218; Vol. 5 N.º 4 (2024): CLIQUE AQUI PARA ACESSAR OS ARTIGOS; e545151 ; 2675-6218

Subject Terms: Algorithms. Programming. Failure. Dropout, Algoritmos. Programación. Reprobación. Evasión, Algorítimos, Programação, Reprovação, Evasão, Algoritmos

File Description: application/pdf

Relation: https://recima21.com.br/index.php/recima21/article/view/5151/3538; https://recima21.com.br/index.php/recima21/article/view/5151

Availability: https://recima21.com.br/index.php/recima21/article/view/5151
https://doi.org/10.47820/recima21.v5i4.5151

Applications of the Bayesian method for predicting equipment failures.

Authors: Shayakhmetova, Assem Abdildayeva, Assel Akhmetova, Ardak et al.

Source: International Journal of Innovative Research & Scientific Studies; 2025, Vol. 8 Issue 5, p884-895, 12p

Subject Terms: DIGITAL twin, RELIABILITY in engineering, MANUFACTURING processes, PROGRAMMING languages, DATA analytics

Smart Campus Dropout Prediction: Hybrid Features and Ensemble Approach.

Authors: Safii, M. Nababan, Adli Abdillah Husain

Source: International Journal of Engineering Science & Information Technology; 2025, Vol. 5 Issue 4, p124-131, 8p

Subject Terms: ENSEMBLE learning, RANDOM forest algorithms, FEATURE selection, RETENTION of college students, COLLEGE environment, SCHOOL dropouts, STUDENT records

Predicting Student Performance in Introductory Programming Courses.

Authors: Pires, João P. J. Brito Correia, Fernanda Gomes, Anabela et al.

Source: Computers (2073-431X); Sep2024, Vol. 13 Issue 9, p219, 19p

Subject Terms: HIGHER education, FAILURE (Psychology), ALGORITHMS, FORECASTING, STUDENTS

Profiling the skill mastery of introductory programming students: A cognitive diagnostic modeling approach.

Authors: Garcia, Manuel B.

Source: Education & Information Technologies; Apr2025, Vol. 30 Issue 5, p6455-6481, 27p

Subject Terms: EDUCATIONAL planning, COMPUTER science education, INFORMATION technology, SCHOOL failure, EDUCATIONAL evaluation

Using Traditional Text Analysis and Large Language Models in Service Failure and Recovery.

Authors: Villarroel Ordenes, Francisco Packard, Grant Hartmann, Jochen et al.

Source: Journal of Service Research; Aug2025, Vol. 28 Issue 3, p382-388, 7p

Subject Terms: LANGUAGE models, RESEARCH methodology, CONTENT analysis, CUSTOMER service management, QUALITY of service, PYTHON programming language

Research on Optimal Control Strategies on Distribution Network Power Transfer Under Extreme Weather Conditions.

Authors: Su, Biaolong Xi, Yanna Li, Shuang et al.

Source: Electronics (2079-9292); Oct2025, Vol. 14 Issue 19, p3854, 22p

Subject Terms: EXTREME weather, POWER distribution networks, DEEP learning, REINFORCEMENT learning, MIXED integer linear programming, OPTIMAL control theory, ELECTRICAL load, DYNAMIC models

Teaching Programming in Township Schools: A Mental Model Approach to Developing Computational Thinking.

Authors: Tshidi, Mashite

Source: African Journal of Research in Mathematics, Science & Technology Education; Dec2025, Vol. 29 Issue 3, p322-334, 13p

Educational data mining to support identification and prevention of academic retention and dropout: a case study in introductory programming.

Authors: Guimarães Carneiro, Murillo Luiza Dutra, Bruna S. Paiva, José Gustavo et al.

Source: Revista Brasileira de Informática na Educação; 2022, Vol. 30, p379-395, 17p

Subject Terms: DATA mining, RF values (Chromatography), COMPUTER programming, SCHOOL dropout prevention, RISK retention

Why follow-up matters in survival analysis: comparing cox proportional hazard regression and random survival forest for predicting heart failure outcomes.

Authors: ÖZGÜR, Emrah Gökay BEKİROĞLU, Gülnaz Nural

Source: BMC Cardiovascular Disorders; 9/26/2025, Vol. 25 Issue 1, p1-9, 9p

Subject Terms: HEART failure, SURVIVAL analysis (Biometry), MACHINE learning, PREDICTION models, PROPORTIONAL hazards models, RANDOM forest algorithms, SURVIVAL rate

A Comparative Hybrid Approach for Python Bug Detection Using Syntactic Features, Random Forest, and Neural Network.

Authors: Imran, Bahtiar Wahyudi, Erfan Riadi, Selamet et al.

Source: Journal of Communication & Information Technology (CommIT Journal); Oct2025, Vol. 19 Issue 2, p141-150, 10p

Subject Terms: MACHINE learning, RANDOM forest algorithms, DEFECT tracking (Computer software development), CLASSIFICATION algorithms, COMPUTER software development, PYTHON programming language, DATA structures, ARTIFICIAL neural networks

Research on Hybrid Optimization Prediction Models for Photovoltaic Power Generation Under Extreme Climate Conditions.

Authors: Zhang, Haomin Zheng, Jie Wang, Daoyuan et al.

Source: Electronics (2079-9292); Nov2025, Vol. 14 Issue 22, p4475, 22p

Subject Terms: PHOTOVOLTAIC power generation, CLIMATE extremes, ELECTRIC power system stability, GREY Wolf Optimizer algorithm, STATISTICAL accuracy, K-means clustering, MATHEMATICAL programming

Generative Adversarial Network Based Improved Transfer Learning Models for Chronic Heart Failure Detection.

Authors: Gawande, Namrata Goyal, Dinesh Sankhla, Kriti

Source: Ingénierie des Systèmes d'Information; Apr2025, Vol. 30 Issue 4, p1087-1100, 14p

Subject Terms: HEART failure, GENERATIVE adversarial networks, DATA fusion (Statistics), HEART sounds, TRANSFER of training, MACHINE learning, CONVOLUTIONAL neural networks, CLASSIFICATION algorithms

A Structure-Aware and Condition-Constrained Algorithm for Text Recognition in Power Cabinets.

Authors: Liu, Yang Li, Shilun Zhang, Liang

Source: Electronics (2079-9292); Aug2025, Vol. 14 Issue 16, p3315, 27p

Subject Terms: TEXT recognition, OPTICAL character recognition, ALGORITHMS, REAL-time computing, CONSTRAINT programming, ELECTRONIC equipment enclosures

Research on Gas Pipeline Leakage Prediction Model Based on Physics-Aware GL-TransLSTM.

Authors: Wu, Chunjiang Lu, Haoyu Liu, Dianming et al.

Source: Biomimetics (2313-7673); Nov2025, Vol. 10 Issue 11, p743, 30p

Subject Terms: NATURAL gas pipelines, DEEP learning, DETECTION algorithms, PIPELINE failures, MULTISENSOR data fusion, MACHINE learning

Hybrid optimized remaining useful life prediction framework for lithium-ion batteries with limited data samples.

Authors: Ibrahim, Md Ansari, Shaheer Ayob, Afida et al.

Source: Scientific Reports; 11/7/2025, Vol. 15 Issue 1, p1-16, 16p

Subject Terms: REMAINING useful life, LITHIUM-ion batteries, MULTILAYER perceptrons, MATHEMATICAL programming, MEAN square algorithms, STATISTICAL sampling, MATHEMATICAL optimization

Company/Entity: UNITED States. National Aeronautics & Space Administration

Machine Learning-Based Fracture Failure Analysis and Structural Optimization of Adhesive Joints.

Authors: Liu, Yalong Gu, Zewen Sun, Mingze et al.

Source: Applied Sciences (2076-3417); Aug2025, Vol. 15 Issue 16, p9041, 18p

Subject Terms: ADHESIVE joints, STRUCTURAL optimization, MACHINE learning, ARTIFICIAL neural networks, BOND strengths, GENETIC algorithms, INHOMOGENEOUS materials, FRACTURE mechanics

Belief-Based Model of Career Dropout Under Monopsonistic Employment and Noisy Evaluation.

Authors: Aliende, Iñaki Escot, Lorenzo Sandubete, Julio E.

Source: Mathematics (2227-7390); Sep2025, Vol. 13 Issue 17, p2879, 23p

Subject Terms: EMPLOYEE retention, OPTIMAL stopping (Mathematical statistics), DYNAMIC programming, SELF-evaluation, DECISION theory, SIGNAL-to-noise ratio, LABOR market, PROFESSIONS

PREDICTION OF ROCK SLOPE FAILURE BASED ON MULTIPLE MACHINE LEARNING ALGORITHMS.

Authors: MNZOOL, Mohammed

Source: Thermal Science; 2024, Vol. 28 Issue 6B, p4907-4916, 10p

Subject Terms: ROCK slopes, SUPPORT vector machines, DECISION trees, SAFETY factor in engineering, GENETIC algorithms, RANDOM forest algorithms