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Aisha M. A. S. Alnajdi – ProQuest LLC, 2024
Data are an essential factor in the fourth industrial revolution, demanding engineers and scientists to leverage and analyze their potential for significantly improving the efficiency of industrial processes and their control systems. In classical industrial process control systems, the models are constructed using linear data-driven approaches,…
Descriptors: Artificial Intelligence, Chemistry, Hierarchical Linear Modeling, Time
Elena C. Papanastasiou; Michalis P. Michaelides – Large-scale Assessments in Education, 2024
Test-taking behavior is a potential source of construct irrelevant variance for test scores in international large-scale assessments where test-taking effort, motivation, and behaviors in general tend to be confounded with test scores. In an attempt to disentangle this relationship and gain further insight into examinees' test-taking processes,…
Descriptors: Grade 4, Testing, Student Behavior, Test Wiseness
Julia-Kim Walther; Martin Hecht; Benjamin Nagengast; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their "cols :…
Descriptors: Data, Monte Carlo Methods, Statistical Distributions, Matrices
Fatma Ünal; Hakan Kogar – International Journal of Assessment Tools in Education, 2024
The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
Liang Zhang; Jionghao Lin; John Sabatini; Conrad Borchers; Daniel Weitekamp; Meng Cao; John Hollander; Xiangen Hu; Arthur C. Graesser – IEEE Transactions on Learning Technologies, 2025
Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…
Descriptors: Artificial Intelligence, Academic Achievement, Data, Evaluation Methods
Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Nirmal Ghimire; Kouider Mokhtari – AERA Online Paper Repository, 2024
This study examined the predictive power of students' demographic characteristics, reading attitudes, school characteristics, and teacher-informed reading activities on three metacognitive reading skills: understanding and remembering, summarizing, and assessing credibility and their influence on 15-year-old students' reading scores. The dataset…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
Syahrul Amin; Karen E. Rambo-Hernandez; Blaine A. Pedersen; Camille S. Burnett; Bimal P. Nepal; Noemi V. Mendoza Diaz – Cogent Education, 2024
This study examined the persistence of first-year engineering students at a Hispanic-Serving Institution (HSI) and a Historically Black College and University (HBCU) pre- and mid-COVID-19 interruptions and whether their characteristics (race/ethnicity, financial need status, first-generation status, SAT scores) predicted their persistence. Using…
Descriptors: College Freshmen, Engineering Education, Academic Persistence, COVID-19