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Giannakas, Filippos; Troussas, Christos; Krouska, Akrivi; Sgouropoulou, Cleo; Voyiatzis, Ioannis – Education and Information Technologies, 2022
Working in groups is an important collaboration activity in the educational context, where a variety of factors can influence the prediction of the teams' performance. In the pertinent bibliography, several machine learning models are available for delivering predictions. In this sense, the main goal of the current research is to assess 28…
Descriptors: Comparative Analysis, Artificial Intelligence, Prediction, Cooperative Learning
Kye, Anna – ProQuest LLC, 2023
Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…
Descriptors: Comparative Analysis, Classification, College Enrollment, Prediction
Long, J. Scott; Mustillo, Sarah A. – Sociological Methods & Research, 2021
Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes. Unlike approaches based on the comparison of regression coefficients across groups, the methods we propose are unaffected by the scalar identification of the coefficients and are expressed in…
Descriptors: Regression (Statistics), Comparative Analysis, Probability, Groups
Yuang Wei; Bo Jiang – IEEE Transactions on Learning Technologies, 2024
Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…
Descriptors: Cognitive Mapping, Models, Prediction, Short Term Memory
Cong Xie; Shuangfei Zhang; Xinuo Qiao; Ning Hao – npj Science of Learning, 2024
This study investigated whether transcranial direct current stimulation (tDCS) targeting the inferior frontal gyrus (IFG) can alter the thinking process and neural basis of creativity. Participants' performance on the compound remote associates (CRA) task was analyzed considering the semantic features of each trial after receiving different tDCS…
Descriptors: Stimulation, Brain Hemisphere Functions, Semantics, Comparative Analysis
Sharma, Sunny; Rana, Vijay; Malhotra, Manisha – Education and Information Technologies, 2022
Web recommendation systems are ubiquitous in the world used to overcome the product overload on e-commerce websites. Among various filtering algorithms, Collaborative Filtering and Content Based Filtering are the best recommendation approaches. Being popular, these filtering approaches still suffer from various limitations such as Cold Start…
Descriptors: Web Sites, Purchasing, Computer Software, Profiles
Raykov, Tenko – Measurement: Interdisciplinary Research and Perspectives, 2023
This software review discusses the capabilities of Stata to conduct item response theory modeling. The commands needed for fitting the popular one-, two-, and three-parameter logistic models are initially discussed. The procedure for testing the discrimination parameter equality in the one-parameter model is then outlined. The commands for fitting…
Descriptors: Item Response Theory, Models, Comparative Analysis, Item Analysis
Jang, Yoona; Hong, Sehee – Educational and Psychological Measurement, 2023
The purpose of this study was to evaluate the degree of classification quality in the basic latent class model when covariates are either included or are not included in the model. To accomplish this task, Monte Carlo simulations were conducted in which the results of models with and without a covariate were compared. Based on these simulations,…
Descriptors: Classification, Models, Prediction, Sample Size
I Remembered the Chorm! Word Learning Abilities of Children with and without Phonological Impairment
Stephanie Hearnshaw; Elise Baker; Ron Pomper; Karla K. McGregor; Jan Edwards; Natalie Munro – International Journal of Language & Communication Disorders, 2024
Background: Children with phonological impairment present with pattern-based errors in their speech production. While some children have difficulties with speech perception and/or the establishment of robust underlying phonological representations, the nature of phonological impairment in children is still not well understood. Given that…
Descriptors: Phonology, Vocabulary Development, Speech Communication, Auditory Perception
Hyemin Yoon; HyunJin Kim; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…
Descriptors: Classification, Artificial Intelligence, Prediction, Decision Making
Hertog, Steffen – Sociological Methods & Research, 2023
In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…
Descriptors: Case Studies, Generalization, Prediction, Mixed Methods Research
Meyer, Marlene; van Schaik, Johanna E.; Poli, Francesco; Hunnius, Sabine – Developmental Science, 2023
When teaching infants new actions, parents tend to modify their movements. Infants prefer these infant-directed actions (IDAs) over adult-directed actions and learn well from them. Yet, it remains unclear "how" parents' action modulations capture infants' attention. Typically, making movements larger than usual is thought to draw…
Descriptors: Infants, Attention Control, Prediction, Brain Hemisphere Functions
Nooshin Khobzi Rotondi; David Rudoler; William Hunter; Olayinka Sanusi; Chris Collier; Michael Anthony Rotondi – Statistics Education Research Journal, 2023
This article reports on an evaluation the effectiveness of e-mailed grade "nudges" on students' performance and engagement in an introductory statistics course for undergraduate health science students. In 2020-2021, 358 students were randomized to an e-mail (n = 178) or no e-mail (n = 180) group. The intervention e-mail contained…
Descriptors: Introductory Courses, Statistics Education, Grades (Scholastic), Learner Engagement
Ke-Hai Yuan; Yongfei Fang – Grantee Submission, 2023
Observational data typically contain measurement errors. Covariance-based structural equation modelling (CB-SEM) is capable of modelling measurement errors and yields consistent parameter estimates. In contrast, methods of regression analysis using weighted composites as well as a partial least squares approach to SEM facilitate the prediction and…
Descriptors: Structural Equation Models, Regression (Statistics), Weighted Scores, Comparative Analysis
Sarah Staveteig Ford; Matthew Kirwin – International Journal of Social Research Methodology, 2023
International survey researchers are increasingly turning to a geospatial sampling approach known as gridded population sampling for finer resolution and a more updated sampling frame than conventional census-based sampling. To date, there have been no direct comparisons of accuracy between survey results derived from the two methods. This…
Descriptors: Accuracy, Sampling, Elections, Census Figures