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Terry A. Ackerman; Deborah L. Bandalos; Derek C. Briggs; Howard T. Everson; Andrew D. Ho; Susan M. Lottridge; Matthew J. Madison; Sandip Sinharay; Michael C. Rodriguez; Michael Russell; Alina A. Davier; Stefanie A. Wind – Educational Measurement: Issues and Practice, 2024
This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational…
Descriptors: Educational Assessment, Competence, Skill Development, Communication Skills
Tianci Liu; Chun Wang; Gongjun Xu – Grantee Submission, 2022
Multidimensional Item Response Theory (MIRT) is widely used in educational and psychological assessment and evaluation. With the increasing size of modern assessment data, many existing estimation methods become computationally demanding and hence they are not scalable to big data, especially for the multidimensional three-parameter and…
Descriptors: Item Response Theory, Computation, Monte Carlo Methods, Algorithms
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Orit Hazzan; Yael Erez – ACM Transactions on Computing Education, 2025
In this opinion piece, we explore the idea that GenAI has the potential to fundamentally disrupt computer science education (CSE) by drawing insights from 10 pedagogical and cognitive theories and models. We highlight how GenAI improves CSE by making educational practices more effective and requires less effort and time, and all at a lower cost,…
Descriptors: Computer Science Education, Artificial Intelligence, Technology Uses in Education, Educational Change
Peter Organisciak; Michele Newman; David Eby; Selcuk Acar; Denis Dumas – Grantee Submission, 2023
Purpose: Most educational assessments tend to be constructed in a close-ended format, which is easier to score consistently and more affordable. However, recent work has leveraged computation text methods from the information sciences to make open-ended measurement more effective and reliable for older students. This study asks whether such text…
Descriptors: Learning Analytics, Child Language, Semantics, Age Differences

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