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Vahid Roshanaei; Bahman Naderi; Opher Baron; Dmitry Krass – INFORMS Transactions on Education, 2024
We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…
Descriptors: Spreadsheets, Interaction, Classification, Computation
C. J. Van Lissa; M. Garnier-Villarreal; D. Anadria – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Latent class analysis (LCA) refers to techniques for identifying groups in data based on a parametric model. Examples include mixture models, LCA with ordinal indicators, and latent class growth analysis. Despite its popularity, there is limited guidance with respect to decisions that must be made when conducting and reporting LCA. Moreover, there…
Descriptors: Multivariate Analysis, Structural Equation Models, Open Source Technology, Computation
Dan Wei; Peida Zhan; Hongyun Liu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. The present study developed a versatile fit index, named Weighted Root Mean Squared Errors (WRMSE), based on individual case residuals (ICRs) with the aim…
Descriptors: Structural Equation Models, Goodness of Fit, Error of Measurement, Computation
Xuelin Liu; Hua Zhang; Yue Cheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…
Descriptors: Artificial Intelligence, Data, Text Structure, Classification
Bayan Masarwa; Hagit Hel-Or; Sharona T. Levy – Journal of Research in Childhood Education, 2024
Computational thinking (CT) activities are increasingly being integrated into early childhood schools. We focus on studying children's learning using an "unplugged" (non-computational) learning unit that considers a teacher's knowledge and classroom space and affords seamless adaptation into the classroom given the objects used in the…
Descriptors: Kindergarten, Computation, Thinking Skills, Educational Games
Salomé Do; Étienne Ollion; Rubing Shen – Sociological Methods & Research, 2024
The last decade witnessed a spectacular rise in the volume of available textual data. With this new abundance came the question of how to analyze it. In the social sciences, scholars mostly resorted to two well-established approaches, human annotation on sampled data on the one hand (either performed by the researcher, or outsourced to…
Descriptors: Computation, Social Sciences, Natural Language Processing, Artificial Intelligence
Chunhua Cao; Benjamin Lugu; Jujia Li – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…
Descriptors: Structural Equation Models, Bayesian Statistics, Measurement, Error of Measurement
Cross-Classified Item Response Theory Modeling with an Application to Student Evaluation of Teaching
Sijia Huang; Li Cai – Journal of Educational and Behavioral Statistics, 2024
The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…
Descriptors: Classification, Data Collection, Data Analysis, Item Response Theory
Marianthi Grizioti; Chronis Kynigos – Informatics in Education, 2024
Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…
Descriptors: Computation, Thinking Skills, Data Science, Classification
Junfeng Man; Rongke Zeng; Xiangyang He; Hua Jiang – Knowledge Management & E-Learning, 2024
At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…
Descriptors: Cognitive Ability, Student Evaluation, Algorithms, Learning Processes