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Natalie Bleijlevens; Tanya Behne – Developmental Psychology, 2024
Upon hearing a novel label, listeners tend to assume that it refers to a novel, rather than a familiar object. While this disambiguation or mutual exclusivity (ME) effect has been robustly shown across development, it is unclear what it involves. Do listeners use their pragmatic and lexical knowledge to exclude the familiar object and thus select…
Descriptors: Ambiguity (Semantics), Toddlers, Adults, Cognitive Mapping
Kübra Karakaya Özyer – Journal of Social Studies Education Research, 2024
The study aims to assess online assessment practices in a public university, addressing questions about self-efficacy levels, tools used, challenges faced, and proposed solutions. The chosen methodology employs a cross-sectional survey design, collecting both quantitative and qualitative data from 50 instructors in Türkiye through a convenience…
Descriptors: Foreign Countries, Student Evaluation, Computer Assisted Testing, College Students
Cassandra Guarino; Anna Bargagliotti; Tom Smith; Hana Kang; Yiwang Li – Annenberg Institute for School Reform at Brown University, 2024
This study addresses the important yet underexplored question of whether the Common Core State Standards in Mathematics, which emphasize critical thinking and problem-solving, as well as the computer-based assessments aligned with the Common Core, have facilitated or hindered learning for students with disabilities. By analyzing administrative…
Descriptors: Common Core State Standards, Mathematics Achievement, Mathematics Instruction, Elementary School Students
Zhengyuan Liu – Education and Information Technologies, 2024
This study investigates the differential impacts of various online language assessment models--specifically, the Nonlinear Dynamic Individual-Centered Language Assessment (NDICLA), diagnostic assessment, and formative assessment--on the cognitive load and learning outcomes of English as a Foreign Language (EFL) learners within computer-assisted…
Descriptors: Computer Assisted Testing, Student Evaluation, Models, Second Language Learning
Gerd Kortemeyer; Julian Nöhl; Daria Onishchuk – Physical Review Physics Education Research, 2024
[This paper is part of the Focused Collection in Artificial Intelligence Tools in Physics Teaching and Physics Education Research.] Using a high-stakes thermodynamics exam as the sample (252 students, four multipart problems), we investigate the viability of four workflows for AI-assisted grading of handwritten student solutions. We find that the…
Descriptors: Grading, Physics, Science Instruction, Artificial Intelligence
Blaženka Divjak; Petra Žugec; Katarina Pažur Anicic – International Journal of Mathematical Education in Science and Technology, 2024
Assessment is among the inevitable components of a curriculum and directs students' learning. E-assessment, as prepared and administered with the use of ICT, provides opportunities to make the process easier in some aspects, but also brings certain challenges. This paper presents an e-assessment framework from a student perspective. Our study…
Descriptors: Student Evaluation, Computer Assisted Testing, Evaluation Methods, Student Attitudes
Clodagh Carroll – European Journal of Science and Mathematics Education, 2024
With the initial COVID-19 lockdown of March 2020 in Ireland, many modules in university programmes that were designed to be delivered face-to-face were suddenly switched to remote delivery. The difficulty for both lecturers and students in replicating face-to-face interaction and the frequent lack of lecturers' visibility of students' work in such…
Descriptors: Foreign Countries, College Freshmen, Mathematics Education, Mathematics Instruction
Yaru Meng; Hua Fu; Chuang Wang – Language Learning & Technology, 2024
There is growing literature on computerized dynamic assessment (C-DA) wherein individual items are accompanied by mediating prompts, but its effectiveness at fine-grained levels across time has not been explored sufficiently. This study constructed a computerized listening dynamic assessment (CLDA) system, where mediation was informed by an…
Descriptors: Computer Assisted Testing, Test Validity, Audio Equipment, Audiometric Tests
Ashish Gurung; Kirk Vanacore; Andrew A. McReynolds; Korinn S. Ostrow; Eamon S. Worden; Adam C. Sales; Neil T. Heffernan – Grantee Submission, 2024
Learning experience designers consistently balance the trade-off between open and close-ended activities. The growth and scalability of Computer Based Learning Platforms (CBLPs) have only magnified the importance of these design trade-offs. CBLPs often utilize close-ended activities (i.e. Multiple-Choice Questions [MCQs]) due to feasibility…
Descriptors: Multiple Choice Tests, Testing, Test Format, Computer Assisted Testing
Saha, Sujan Kumar; Gupta, Rushali – Education and Information Technologies, 2020
The use of computers in educational assessment is a widely explored territory. Several studies have been performed to show the effectiveness of computer-assisted assessment (CAA) and it has been accepted in various education sectors. However, due to the lack of sufficient infrastructure and other issues, the paper-based examination is still being…
Descriptors: Computer Assisted Testing, Student Evaluation, Foreign Countries, Handwriting
Salles, Franck; Dos Santos, Reinaldo; Keskpaik, Saskia – Large-scale Assessments in Education, 2020
During this digital era, France, like many other countries, is undergoing a transition from paper-based assessments to digital assessments in education. There is a rising interest in technology-enhanced items which offer innovative ways to assess traditional competencies, as well as addressing problem solving skills, specifically in mathematics.…
Descriptors: Foreign Countries, Didacticism, Mathematics Tests, Learning Analytics
Morris, Scott B.; Bass, Michael; Howard, Elizabeth; Neapolitan, Richard E. – International Journal of Testing, 2020
The standard error (SE) stopping rule, which terminates a computer adaptive test (CAT) when the "SE" is less than a threshold, is effective when there are informative questions for all trait levels. However, in domains such as patient-reported outcomes, the items in a bank might all target one end of the trait continuum (e.g., negative…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Banks, Item Response Theory
O'Neill, Rachel; Cameron, Audrey; Burns, Eileen; Quinn, Gary – Psychology in the Schools, 2020
Attitudes to sign languages or language policies are often not overtly discussed or recorded but they influence deaf young people's educational opportunities and outcomes. Two qualitative studies from Scotland investigate the provision of British Sign Language as accommodation in public examinations. The first explores the views of deaf pupils and…
Descriptors: Foreign Countries, Alternative Assessment, Sign Language, Deafness
Wan, Qian; Crossley, Scott; Allen, Laura; McNamara, Danielle – Grantee Submission, 2020
In this paper, we extracted content-based and structure-based features of text to predict human annotations for claims and nonclaims in argumentative essays. We compared Logistic Regression, Bernoulli Naive Bayes, Gaussian Naive Bayes, Linear Support Vector Classification, Random Forest, and Neural Networks to train classification models. Random…
Descriptors: Persuasive Discourse, Essays, Writing Evaluation, Natural Language Processing
Zhang, Haoran; Litman, Diane – Grantee Submission, 2020
While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE and neural AES, by extracting…
Descriptors: Computer Assisted Testing, Scoring, Essay Tests, Writing Evaluation

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