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W. Jake Thompson; Amy K. Clark – Educational Measurement: Issues and Practice, 2024
In recent years, educators, administrators, policymakers, and measurement experts have called for assessments that support educators in making better instructional decisions. One promising approach to measurement to support instructional decision-making is diagnostic classification models (DCMs). DCMs are flexible psychometric models that…
Descriptors: Decision Making, Instructional Improvement, Evaluation Methods, Models
A. M. Sadek; Fahad Al-Muhlaki – Measurement: Interdisciplinary Research and Perspectives, 2024
In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…
Descriptors: Monte Carlo Methods, Accuracy, Artificial Intelligence, Guidelines
Bephyer Parey; Elisabeth Kutscher – Journal of Mixed Methods Research, 2024
Rigor evaluation in mixed methods research is a growing need. Linking rigor to Hong and Pluye's (2019) concepts of methodological and reporting quality, the purpose of this article is to operationalize and expand Harrison et al.'s (2020) Rigorous Mixed Methods Framework. Drawing from a systematic methodological review of 66 inclusive education…
Descriptors: Mixed Methods Research, Difficulty Level, Evaluation Methods, Research Design
Grant, S. G.; Swan, Kathy; Lee, John – Social Education, 2023
Assessment is usually considered as an afterthought in the instructional design process. Given the many challenges of assessment design--and the lack of ready solutions--teachers may fall back on familiar forms of assessments and hope for the best. As a result, the problem is not a lack of will on the part of teachers. Instead, it is the lack of…
Descriptors: Evaluation Methods, Inquiry, Design, Models
Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
Daniel A. Mak; Sebastian Dunn; David Coombes; Carlo R. Carere; Jane R. Allison; Volker Nock; André O. Hudson; Renwick C. J. Dobson – Biochemistry and Molecular Biology Education, 2024
Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and…
Descriptors: Biochemistry, Kinetics, Science Instruction, Teaching Methods
Arabi, Elham; Garza, Tiberio – International Journal of Training and Development, 2023
This research investigates the linkage between training evaluation, learning design and training transfer. A new training evaluation model, (i.e., learning-transfer evaluation model [LTEM]), was used to examine its ability to provide evaluative evidence through robust assessments in pre-, post- and delayed assessments. The model was used to…
Descriptors: Evaluation Methods, Instructional Design, Training, Program Evaluation
Daniel McNeish – Grantee Submission, 2023
Factor analysis is often used to model scales created to measure latent constructs, and internal structure validity evidence is commonly assessed with indices like SRMR, RMSEA, and CFI. These indices are essentially effect size measures and definitive benchmarks regarding which values connote reasonable fit have been elusive. Simulations from the…
Descriptors: Models, Testing, Indexes, Factor 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
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Zheng Liu; Jiahui Wen; Yikang Liu; Chuan-Peng Hu – British Journal of Educational Psychology, 2024
Background: Self-related information is difficult to ignore and forget, which brings valuable implications for educational practice. Self-referential encoding techniques involve integrating self-referencing cues during the processing of learning material. However, the evidence base and effective implementation boundaries for these techniques in…
Descriptors: Self Concept, Meta Analysis, Student Attitudes, Models
Katherine Connolly; Jessica B. Koslouski; Sandra M. Chafouleas; Marlene B. Schwartz; Bonnie Edmondson; Amy M. Briesch – Journal of School Health, 2024
Background: Adoption of the Whole School, Whole Community, Whole Child (WSCC) model has been slowed by a lack of available tools to support implementation. The Wellness School Assessment Tool (WellSAT) WSCC is an online assessment tool that allows schools to evaluate the alignment of their policies with the WSCC model. This study assesses the…
Descriptors: Usability, Wellness, Program Evaluation, Evaluation Methods
Holman, Alea R.; D'Costa, Stephanie; Janowitch, Laura – School Psychology Review, 2023
Psychoeducational assessment has been used as a tool to sort children into academic tracks based on children's presumed capabilities. Historically, such tracking was based on measures that sought to legitimize racist assumptions about the capabilities of children of color. Despite legal mandates and changes to practice intended to correct these…
Descriptors: Power Structure, Evaluation Methods, Cooperation, Models
Jeff Irvine – Journal of Instructional Pedagogies, 2023
The Pirie-Kieren Model (PKM) was a paradigm shift in theories of learning by presenting a coherent, consistent theory compatible with complexity theory. PKM recognized that learning is non-linear, recursive, iterative, and emergent. PKM was one of the first theories to depart from the linear models of learning that dominated theories of learning…
Descriptors: Models, Mathematics Education, Educational Theories, Taxonomy
Safa Ridha Albo Abdullah; Ahmed Al-Azawei – International Review of Research in Open and Distributed Learning, 2025
This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…
Descriptors: Electronic Learning, Academic Achievement, Grade Prediction, Data Analysis