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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
Edoardo Bertone; Cecilia Bischeri; Jennifer Boddy – Environmental Education Research, 2025
Addressing the Sustainable Development Goals (SDGs) has become of paramount importance for higher education institutions; however, a lack of a transparent, transferrable approach to identifying and quantifying the extent of SDG contributions hinders the ability to benchmark against past performance or other institutions. In this study, a…
Descriptors: Foreign Countries, Architectural Education, Undergraduate Students, College Faculty
Yang Du; Susu Zhang – Journal of Educational and Behavioral Statistics, 2025
Item compromise has long posed challenges in educational measurement, jeopardizing both test validity and test security of continuous tests. Detecting compromised items is therefore crucial to address this concern. The present literature on compromised item detection reveals two notable gaps: First, the majority of existing methods are based upon…
Descriptors: Item Response Theory, Item Analysis, Bayesian Statistics, Educational Assessment
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
Huey T. Chen; Liliana Morosanu; Victor H. Chen – Asia Pacific Journal of Education, 2024
The Campbellian validity typology has been used as a foundation for outcome evaluation and for developing evidence-based interventions for decades. As such, randomized control trials were preferred for outcome evaluation. However, some evaluators disagree with the validity typology's argument that randomized controlled trials as the best design…
Descriptors: Evaluation Methods, Systems Approach, Intervention, Evidence Based Practice
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
W. Jake Thompson – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…
Descriptors: Bayesian Statistics, Classification, Psychometrics, Goodness of Fit
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
Mark, Melvin M. – American Journal of Evaluation, 2022
Premised on the idea that evaluators should be familiar with a range of approaches to program modifications, I review several existing approaches and then describe another, less well-recognized option. In this newer option, evaluators work with others to identify potentially needed adaptations for select program aspects "in advance." In…
Descriptors: Evaluation Research, Evaluation Problems, Evaluation Methods, Models
Bonifay, Wes; Depaoli, Sarah – Prevention Science, 2023
Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit…
Descriptors: Bayesian Statistics, Programming Languages, Psychopathology, Classification
Wolkowitz, Amanda A. – Journal of Educational Measurement, 2021
Decision consistency (DC) is the reliability of a classification decision based on a test score. In professional credentialing, the decision is often a high-stakes pass/fail decision. The current methods for estimating DC are computationally complex. The purpose of this research is to provide a computationally and conceptually simple method for…
Descriptors: Decision Making, Reliability, Classification, Scores
Razmgir, Maryam; Panahi, Sirous; Ghalichi, Leila; Mousavi, Seyed Ali Javad; Sedghi, Shahram – Research Evaluation, 2021
This article explores the models and frameworks developed on "research impact'. We aim to provide a comprehensive overview of related literature through scoping study method. The present research investigates the nature, objectives, approaches, and other main attributes of the research impact models. It examines to analyze and classify models…
Descriptors: Evaluation Research, Models, Evaluation Methods, Classification
Bengough, Theresa; Sommer, Isolde; Hannes, Karin – Research Synthesis Methods, 2023
Contextual factors such as cultural values and traditions impact on implementation processes of healthcare interventions. It is one of the reasons why local stakeholders may decide to role out a programme differently from how it has originally been developed or described in scientific literature. This can result in different but most likely more…
Descriptors: Context Effect, Evaluation Methods, Cultural Influences, Intervention
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Young, Lisa; O'Connor, Justen; Alfrey, Laura; Penney, Dawn – Curriculum Studies in Health and Physical Education, 2021
This paper utilises Bernstein's theorising of curriculum and pedagogical relations to analyse Physical Literacy (PL) assessment with implications for the field of Health and/Physical Education (H/PE). It acknowledges the significance of assessment for what knowledge and skills are valued in PL and in turn, H/PE. PL takes different forms and is…
Descriptors: Multiple Literacies, Physical Education, Health Education, Student Evaluation

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