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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
Hii, Puong Koh; Goh, Chin Fei; Rasli, Amran; Tan, Owee Kowang – Knowledge Management & E-Learning, 2022
Multicriteria decision-making (MCDM) techniques have been widely adopted to evaluate the effectiveness of e-learning. However, the literature review has not kept pace with the rapid accumulation of knowledge in this field. This study systematically reviews the MCDM techniques applied in e-learning issues. In total, we reviewed 77 published studies…
Descriptors: Electronic Learning, Instructional Effectiveness, Decision Making, Evaluation
Constance Tucker; Sarah Jacobs; Kirstin Moreno – Intersection: A Journal at the Intersection of Assessment and Learning, 2024
Learning outcomes and assessment frameworks guide educators in curricular decisionmaking, impact assessment, gap identification, and equity evaluation, aligning with anticipated learning objectives. Common frameworks include Bloom's taxonomy, Kirkpatrick's model, Fink's taxonomy, and Moore's Outcomes model. The authors identified a lack of focus…
Descriptors: Student Evaluation, Outcomes of Education, Taxonomy, Decision Making
Dizon, Arnie G. – History of Education, 2023
CIPP, which stands for Context, Input, Process and Product, an evaluation model, is one of the most widely applied curriculum evaluation models in education. This document-based study sought to determine the historical development of CIPP as a curriculum evaluation model. Here, the reasons why the CIPP evaluation model was conceptualised are…
Descriptors: Educational History, Curriculum Evaluation, Models, Curriculum Development
Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
Markus T. Jansen; Ralf Schulze – Educational and Psychological Measurement, 2024
Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…
Descriptors: Factor Analysis, Models, Item Analysis, Evaluation Methods
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
Schweizer, Karl; Wang, Tengfei; Ren, Xuezhu – Journal of Experimental Education, 2022
The essay reports two studies on confirmatory factor analysis of speeded data with an effect of selective responding. This response strategy leads test takers to choose their own working order instead of completing the items along with the given order. Methods for detecting speededness despite such a deviation from the given order are proposed and…
Descriptors: Factor Analysis, Response Style (Tests), Decision Making, Test Items
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
Çelikbilek, Yakup; Adigüzel Tüylü, Ayse Nur – Interactive Learning Environments, 2022
Institutions and universities have started using e-learning systems to reach the potential students from all over the world by decreasing costs of investments. The speed of technological developments increases the importance of e-learning systems and their technology-based components. E-learning systems also decrease the costs of both institutions…
Descriptors: Electronic Learning, Technology Uses in Education, Distance Education, Artificial Intelligence
Firestone, William A.; Donaldson, Morgaen L. – Educational Assessment, Evaluation and Accountability, 2019
Most recent research on teacher evaluation examines evaluation's measurement properties and accountability uses. Less research studies how evaluation data can improve teaching and student learning. In other contexts, researchers have examined how teachers use data to improve their practice. From general research on teachers' data use, we apply the…
Descriptors: Teacher Evaluation, Data Use, Evaluation Methods, Decision Making
Elizabeth Talbott; Andres De Los Reyes; Devin M. Kearns; Jeannette Mancilla-Martinez; Mo Wang – Exceptional Children, 2023
Evidence-based assessment (EBA) requires that investigators employ scientific theories and research findings to guide decisions about what domains to measure, how and when to measure them, and how to make decisions and interpret results. To implement EBA, investigators need high-quality assessment tools along with evidence-based processes. We…
Descriptors: Evidence Based Practice, Evaluation Methods, Special Education, Educational Research
Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making
Umair Ali Khan; Janne Kauttonen; Lili Aunimo; Ari Alamäki – Journal of Information Technology Education: Research, 2024
Aim/Purpose: The purpose of this paper is to address the challenges posed by disinformation in an educational context. The paper aims to review existing information assessment techniques, highlight their limitations, and propose a conceptual design for a multimodal, explainable information assessment system for higher education. The ultimate goal…
Descriptors: Artificial Intelligence, Higher Education, Trust (Psychology), Barriers
Hung, Su-Pin; Huang, Hung-Yu – Journal of Educational and Behavioral Statistics, 2022
To address response style or bias in rating scales, forced-choice items are often used to request that respondents rank their attitudes or preferences among a limited set of options. The rating scales used by raters to render judgments on ratees' performance also contribute to rater bias or errors; consequently, forced-choice items have recently…
Descriptors: Evaluation Methods, Rating Scales, Item Analysis, Preferences