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Direct linkGerhard Tutz; Pascal Jordan – Journal of Educational and Behavioral Statistics, 2024
A general framework of latent trait item response models for continuous responses is given. In contrast to classical test theory (CTT) models, which traditionally distinguish between true scores and error scores, the responses are clearly linked to latent traits. It is shown that CTT models can be derived as special cases, but the model class is…
Descriptors: Item Response Theory, Responses, Scores, Models
Robson Gonçalves Fechine Feitosa; Gustavo Augusto Lima de Campos; Ismayle de Sousa Santos; Carlos Hairon Ribeiro Gonçalves; Antônio de Barros Serra; Alisson Romão de Oliveira; Pedro Lucas Pereira Feitosa; Yuri David Santos; Esdras Lins Bispo Jr.; Guilherme Álvaro Rodrigues Maia Esmeraldo – International Journal of Artificial Intelligence in Education, 2025
Many existing solutions for the automatic assessment of open-ended questions predominantly rely on machine learning models, primarily focusing on aspects such as writing style and assigning a final score. However, these solutions often overlook the crucial factor of feedback content relevance, specifically, how well the response aligns with the…
Descriptors: Competency Based Education, Skill Development, Artificial Intelligence, Feedback (Response)
Séverin Lions; María Paz Blanco; Pablo Dartnell; Carlos Monsalve; Gabriel Ortega; Julie Lemarié – Applied Measurement in Education, 2024
Multiple-choice items are universally used in formal education. Since they should assess learning, not test-wiseness or guesswork, they must be constructed following the highest possible standards. Hundreds of item-writing guides have provided guidelines to help test developers adopt appropriate strategies to define the distribution and sequence…
Descriptors: Test Construction, Multiple Choice Tests, Guidelines, Test Items
Huang, Hung-Yu – Educational and Psychological Measurement, 2023
The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs)…
Descriptors: Test Items, Classification, Bayesian Statistics, Decision Making
Elvis Ortega-Ochoa; Marta Arguedas; Thanasis Daradoumis – British Journal of Educational Technology, 2024
Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline…
Descriptors: Empathy, Artificial Intelligence, Databases, Dialogs (Language)
Choe, Edison M.; Han, Kyung T. – Journal of Educational Measurement, 2022
In operational testing, item response theory (IRT) models for dichotomous responses are popular for measuring a single latent construct [theta], such as cognitive ability in a content domain. Estimates of [theta], also called IRT scores or [theta hat], can be computed using estimators based on the likelihood function, such as maximum likelihood…
Descriptors: Scores, Item Response Theory, Test Items, Test Format
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
Download full textNianbo Dong; Benjamin Kelcey; Jessaca Spybrook; Yanli Xie; Dung Pham; Peilin Qiu; Ning Sui – Grantee Submission, 2024
Multisite trials that randomize individuals (e.g., students) within sites (e.g., schools) or clusters (e.g., teachers/classrooms) within sites (e.g., schools) are commonly used for program evaluation because they provide opportunities to learn about treatment effects as well as their heterogeneity across sites and subgroups (defined by moderating…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Educational Research, Effect Size
Pattison, Ellen; Ure, Alexandra; Mittiga, Sharon R.; Williams, Katrina; Freeman, Nerelie C. – Journal of Autism and Developmental Disorders, 2022
This review aimed to assess the quality and content of recommendations for delivering an autism diagnosis, published internationally within clinical practice guidelines. Seventeen relevant guidelines were identified. When methodological information was provided, recommendations for feedback were predominantly formed through consensus.…
Descriptors: Feedback (Response), Clinical Diagnosis, Autism, Guidelines
Weese, James D.; Turner, Ronna C.; Liang, Xinya; Ames, Allison; Crawford, Brandon – Educational and Psychological Measurement, 2023
A study was conducted to implement the use of a standardized effect size and corresponding classification guidelines for polytomous data with the POLYSIBTEST procedure and compare those guidelines with prior recommendations. Two simulation studies were included. The first identifies new unstandardized test heuristics for classifying moderate and…
Descriptors: Effect Size, Classification, Guidelines, Statistical Analysis
Han, Suhwa; Kang, Hyeon-Ah – Journal of Educational Measurement, 2023
The study presents multivariate sequential monitoring procedures for examining test-taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test-taking behavior. The study in particular proposes three schemes to track different…
Descriptors: Test Wiseness, Student Behavior, Item Response Theory, Computer Assisted Testing
Matthew John Davidson – ProQuest LLC, 2022
Digitally-based assessments create opportunities for collecting moment to moment information about how students are responding to assessment items. This information, called log or process data, has long been regarded as a vast and valuable source of data about student performance. Despite repeated assurances of its vastness and value, process data…
Descriptors: Data Use, Psychometrics, Item Response Theory, Test Items
Meijuan Li; Hongyun Liu; Mengfei Cai; Jianlin Yuan – Education and Information Technologies, 2024
In the human-to-human Collaborative Problem Solving (CPS) test, students' problem-solving process reflects the interdependency among partners. The high interdependency in CPS makes it very sensitive to group composition. For example, the group outcome might be driven by a highly competent group member, so it does not reflect all the individual…
Descriptors: Problem Solving, Computer Assisted Testing, Cooperative Learning, Task Analysis
Orsola Torrisi; Jethro Banda; Georges Reniers; Stéphane Helleringer – Field Methods, 2024
Guidelines for conducting surveys by mobile phone calls in low- and middle-income countries suggest keeping interviews short (<20 minutes). The evidence supporting this recommendation is scant, even though limiting interview duration might reduce the amount of data generated by such surveys. We recruited nearly 2,500 mobile phone users in…
Descriptors: Foreign Countries, Developing Nations, Interviews, Telephone Surveys
Yi Zhang; Christian D. Schunn; Yong Wu – International Journal of Educational Technology in Higher Education, 2024
Peer feedback literacy is becoming increasingly important in higher education as peer feedback has substantially grown as a pedagogical approach. However, quality of produced feedback, a key behavioral aspect of peer feedback literacy, lacks a systematic and evidence-based conceptualization to guide research, instruction, and system design. We…
Descriptors: Peer Evaluation, Feedback (Response), Literacy, Guidelines
