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Julien Boelaert; Samuel Coavoux; Étienne Ollion; Ivaylo Petev; Patrick Präg – Sociological Methods & Research, 2025
Generative artificial intelligence (AI) is increasingly presented as a potential substitute for humans, including as research subjects. However, there is no scientific consensus on how closely these in silico clones can emulate survey respondents. While some defend the use of these "synthetic users," others point toward social biases in…
Descriptors: Artificial Intelligence, Models, Opinions, Surveys
Hernandez-Gonzalez, Jeronimo; Herrera, Pedro Javier – IEEE Transactions on Learning Technologies, 2023
In peer assessment, students assess a task done by their peers, provide feedback and usually a grade. The extent to which these peer grades can be used to formally grade the task is unclear, with doubts often arising regarding their validity. The instructor could supervise the peer assessments, but would not then benefit from workload reduction,…
Descriptors: Peer Evaluation, Supervision, Models, Computation
Hans-Peter Piepho; Johannes Forkman; Waqas Ahmed Malik – Research Synthesis Methods, 2024
Checking for possible inconsistency between direct and indirect evidence is an important task in network meta-analysis. Recently, an evidence-splitting (ES) model has been proposed, that allows separating direct and indirect evidence in a network and hence assessing inconsistency. A salient feature of this model is that the variance for…
Descriptors: Maximum Likelihood Statistics, Evidence, Networks, Meta Analysis
Jinsook Lee; Yann Hicke; Renzhe Yu; Christopher Brooks; René F. Kizilcec – British Journal of Educational Technology, 2024
Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education…
Descriptors: Artificial Intelligence, Technology Uses in Education, Equal Education, Algorithms
Bartoš, František; Maier, Maximilian; Wagenmakers, Eric-Jan; Doucouliagos, Hristos; Stanley, T. D. – Research Synthesis Methods, 2023
Publication bias is a ubiquitous threat to the validity of meta-analysis and the accumulation of scientific evidence. In order to estimate and counteract the impact of publication bias, multiple methods have been developed; however, recent simulation studies have shown the methods' performance to depend on the true data generating process, and no…
Descriptors: Robustness (Statistics), Bayesian Statistics, Meta Analysis, Publications
Liang, Qianru; de la Torre, Jimmy; Law, Nancy – Journal of Educational and Behavioral Statistics, 2023
To expand the use of cognitive diagnosis models (CDMs) to longitudinal assessments, this study proposes a bias-corrected three-step estimation approach for latent transition CDMs with covariates by integrating a general CDM and a latent transition model. The proposed method can be used to assess changes in attribute mastery status and attribute…
Descriptors: Cognitive Measurement, Models, Statistical Bias, Computation
Sooyong Lee; Suhwa Han; Seung W. Choi – Journal of Educational Measurement, 2024
Research has shown that multiple-indicator multiple-cause (MIMIC) models can result in inflated Type I error rates in detecting differential item functioning (DIF) when the assumption of equal latent variance is violated. This study explains how the violation of the equal variance assumption adversely impacts the detection of nonuniform DIF and…
Descriptors: Factor Analysis, Bayesian Statistics, Test Bias, Item Response Theory
Kylie L. Anglin – Annenberg Institute for School Reform at Brown University, 2025
Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…
Descriptors: Validity, Artificial Intelligence, Models, Best Practices
Sha, Lele; Rakovic, Mladen; Das, Angel; Gasevic, Dragan; Chen, Guanliang – IEEE Transactions on Learning Technologies, 2022
Predictive modeling is a core technique used in tackling various tasks in learning analytics research, e.g., classifying educational forum posts, predicting learning performance, and identifying at-risk students. When applying a predictive model, it is often treated as the first priority to improve its prediction accuracy as much as possible.…
Descriptors: Prediction, Models, Accuracy, Mathematics
Dudel, Christian; Schneider, Daniel C. – Sociological Methods & Research, 2023
Multistate models are often used in social research to analyze how individuals move between states. A typical application is the estimation of the lifetime spent in a certain state, like the lifetime spent in employment, or the lifetime spent in good health. Unfortunately, the estimation of such quantities is prone to several biases. In this…
Descriptors: Models, Computation, Bias, Disabilities
Mark Onslow; Brett Dyer; Mark Jones; Robyn Lowe; Sue O’Brian; Ross Menzies – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Stuttering is associated with clinically significant social anxiety, which emerges during early childhood for some, but not all, children who begin to stutter. The purpose of this review article is to develop a model of social anxiety development during early childhood stuttering and to present an empirical method by which it can be…
Descriptors: Anxiety Disorders, Interpersonal Competence, Child Development, Stuttering
Yasushi Tsujimoto; Yusuke Tsutsumi; Yuki Kataoka; Akihiro Shiroshita; Orestis Efthimiou; Toshi A. Furukawa – Research Synthesis Methods, 2024
Meta-analyses examining dichotomous outcomes often include single-zero studies, where no events occur in intervention or control groups. These pose challenges, and several methods have been proposed to address them. A fixed continuity correction method has been shown to bias estimates, but it is frequently used because sometimes software (e.g.,…
Descriptors: Meta Analysis, Literature Reviews, Epidemiology, Error Correction
Julia Meisters; Adrian Hoffmann; Jochen Musch – Sociological Methods & Research, 2024
Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting…
Descriptors: Foreign Countries, Native Speakers, Adults, Cheating
Martijn Schoenmakers; Jesper Tijmstra; Jeroen Vermunt; Maria Bolsinova – Educational and Psychological Measurement, 2024
Extreme response style (ERS), the tendency of participants to select extreme item categories regardless of the item content, has frequently been found to decrease the validity of Likert-type questionnaire results. For this reason, various item response theory (IRT) models have been proposed to model ERS and correct for it. Comparisons of these…
Descriptors: Item Response Theory, Response Style (Tests), Models, Likert Scales
The Connections Matter: Bi-Directional Learning in Program Evaluation and Practice-Oriented Research
Susan Douglas; Andrew C. Page; Christian Moltu; Michael Kyron; Tim Satterthwaite – Administration and Policy in Mental Health and Mental Health Services Research, 2024
Intended for researchers and clinical leaders, this article suggests that embedded program evaluation is a good fit with the desired features of practice-oriented research. The systematic nature of evaluation that is built into the operational workflow of a practice setting may increase the diversity of methods available to explore processes and…
Descriptors: Program Evaluation, Evidence Based Practice, Feedback (Response), Systems Approach