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Ö. Emre C. Alagöz; Thorsten Meiser – Educational and Psychological Measurement, 2024
To improve the validity of self-report measures, researchers should control for response style (RS) effects, which can be achieved with IRTree models. A traditional IRTree model considers a response as a combination of distinct decision-making processes, where the substantive trait affects the decision on response direction, while decisions about…
Descriptors: Item Response Theory, Validity, Self Evaluation (Individuals), Decision Making
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Cheng, Yiling – Measurement: Interdisciplinary Research and Perspectives, 2023
Computerized adaptive testing (CAT) offers an efficient and highly accurate method for estimating examinees' abilities. In this article, the free version of Concerto Software for CAT was reviewed, dividing our evaluation into three sections: software implementation, the Item Response Theory (IRT) features of CAT, and user experience. Overall,…
Descriptors: Computer Software, Computer Assisted Testing, Adaptive Testing, Item Response Theory
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Austin M. Shin; Ayaan M. Kazerouni – ACM Transactions on Computing Education, 2024
Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…
Descriptors: Feedback (Response), Programming, Student Projects, Computer Software
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Fernandez-Gauna, Borja; Rojo, Naiara; Graña, Manuel – International Journal of Educational Technology in Higher Education, 2023
We describe an automated assessment process for team-coding assignments based on DevOps best practices. This system and methodology includes the definition of Team Performance Metrics measuring properties of the software developed by each team, and their correct use of DevOps techniques. It tracks the progress on each of metric by each group. The…
Descriptors: Computer Software, Programming, Coding, Teamwork
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Kuan-Yu Jin; Wai-Lok Siu – Journal of Educational Measurement, 2025
Educational tests often have a cluster of items linked by a common stimulus ("testlet"). In such a design, the dependencies caused between items are called "testlet effects." In particular, the directional testlet effect (DTE) refers to a recursive influence whereby responses to earlier items can positively or negatively affect…
Descriptors: Models, Test Items, Educational Assessment, Scores
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Nauryz Kuldanov; Svetlana Balagazova; Kamarsulu Ibrayeva; Aliya Mombek; Zhanbolat Kosherbayev; Nazymgul Bolatkhan – Journal of Educational Computing Research, 2025
The primary aim of this study was to evaluate whether the use of the EmoMusic dataset could enhance first-year students' emotional and musical creativity. A randomized controlled trial was conducted with 128 students. Participants were randomly assigned either to a control group that continued traditional vocal training or to an experimental group…
Descriptors: College Freshmen, Music Education, Creativity, Emotional Response
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Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages
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Paganin, Sally; Paciorek, Christopher J.; Wehrhahn, Claudia; Rodríguez, Abel; Rabe-Hesketh, Sophia; de Valpine, Perry – Journal of Educational and Behavioral Statistics, 2023
Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures (DPMs) offer a more flexible representation of the unknown distribution of the latent trait. However, the use of such models in the IRT…
Descriptors: Bayesian Statistics, Item Response Theory, Guidance, Evaluation Methods
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Ernesto Panadero; Alazne Fernández Ortube; Rebecca Krebs; Julian Roelle – Assessment & Evaluation in Higher Education, 2025
Rubrics play a crucial role in shaping educational assessment, providing clear criteria for both teaching and learning. The advent of online rubric platforms has the potential to significantly enhance the effectiveness of rubrics in educational contexts, offering innovative features for assessment and feedback through the creation of erubrics.…
Descriptors: Scoring Rubrics, Teaching Methods, Learning Processes, Feedback (Response)
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Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
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Dmytro Babik; Edward Gehringer; Jennifer Kidd; Kristine Sunday; David Tinapple; Steven Gilbert – Educational Technology Research and Development, 2024
Over the past two decades, there has been an explosion of innovation in software tools that encapsulate and expand the capabilities of the widely used student peer assessment. While the affordances and pedagogical impacts of traditional in-person, "paper-and-pencil" peer assessment have been studied extensively and are relatively well…
Descriptors: Peer Evaluation, Computer Software, Internet, Electronic Learning
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Marin, Julie; Brichler, Ségolène; Lecuyer, Hervé; Carbonnelle, Etienne; Lescat, Mathilde – Journal of Educational Technology Systems, 2021
The coronavirus disease 2019 epidemic has prompted all universities to completely change their teaching in a very rapid way around the world. In France, most of the university courses for the year 2020 had to be delivered at distance. This can be an opportunity for some to rethink the place and the form of distance learning (DL). We present here…
Descriptors: Feedback (Response), Student Attitudes, Medical Students, Microbiology
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Carmen C. Pârvu; Dan Alexandru Szabo; Razvan Tudor Ros?culet; George Danut Mocanu – Journal of Information Technology Education: Research, 2025
Aim/Purpose: This study aims to evaluate the effectiveness of a novel Computerized System for Learning, Correction, and Evaluation in Volleyball (S.C.I.C.E.V) in enhancing the technical performance of beginner volleyball players through immediate audio and visual feedback. The purpose is to determine whether real-time, detailed feedback improves…
Descriptors: Feedback (Response), Psychomotor Skills, Motor Development, Team Sports
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Jeromie Whalen; William Grube; Chenyang Xu; Torrey Trust – TechTrends: Linking Research and Practice to Improve Learning, 2025
Launched in November of 2022, the generative artificial intelligence tool ChatGPT garnered immediate societal interest and adoption as its advanced large language modeling proved capable of producing sophisticated, human-like responses to user-generated prompts. In this preliminary study, K-12 teachers in the United States were surveyed on their…
Descriptors: Elementary School Teachers, Secondary School Teachers, Teacher Attitudes, Teacher Response
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Mehmet Dönmez – International Journal of Assessment Tools in Education, 2024
This bibliometric analysis offers a comprehensive examination of AIbased feedback tools in education, utilizing data retrieved from the Web of Science (WoS) database. Encompassing a total of 239 articles from an expansive timeframe, spanning from inception to February 2024, this study provides a thorough overview of the evolution and current state…
Descriptors: Artificial Intelligence, Feedback (Response), Technology Uses in Education, Individualized Instruction
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