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Michelle Cheong – Journal of Computer Assisted Learning, 2025
Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…
Descriptors: Artificial Intelligence, Performance Based Assessment, Spreadsheets, Models
Zachary K. Collier; Minji Kong; Olushola Soyoye; Kamal Chawla; Ann M. Aviles; Yasser Payne – Journal of Educational and Behavioral Statistics, 2024
Asymmetric Likert-type items in research studies can present several challenges in data analysis, particularly concerning missing data. These items are often characterized by a skewed scaling, where either there is no neutral response option or an unequal number of possible positive and negative responses. The use of conventional techniques, such…
Descriptors: Likert Scales, Test Items, Item Analysis, Evaluation Methods
Andrew D. Ho – Journal of Educational and Behavioral Statistics, 2024
I review opportunities and threats that widely accessible Artificial Intelligence (AI)-powered services present for educational statistics and measurement. Algorithmic and computational advances continue to improve approaches to item generation, scale maintenance, test security, test scoring, and score reporting. Predictable misuses of AI for…
Descriptors: Artificial Intelligence, Measurement, Educational Assessment, Technology Uses in Education
Semere Kiros Bitew; Amir Hadifar; Lucas Sterckx; Johannes Deleu; Chris Develder; Thomas Demeester – IEEE Transactions on Learning Technologies, 2024
Multiple-choice questions (MCQs) are widely used in digital learning systems, as they allow for automating the assessment process. However, owing to the increased digital literacy of students and the advent of social media platforms, MCQ tests are widely shared online, and teachers are continuously challenged to create new questions, which is an…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Test Construction, Test Items
Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
Eray Selçuk; Ergül Demir – International Journal of Assessment Tools in Education, 2024
This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions. For this purpose, depending on the changes in the priori distribution type, sample size, test length, and logistics model, the ability and item…
Descriptors: Item Response Theory, Item Analysis, Test Items, Simulation
Federica Ferretti; Alessandro Gambini; Camilla Spagnolo – European Journal of Science and Mathematics Education, 2024
As highlighted in the literature, one of the main difficulties in mathematics is the management of different semiotic representations. This difficulty occurs in verticals throughout schooling and is often an obstacle to the proper learning process of mathematics. The present study aims to investigate the different facets of these difficulties with…
Descriptors: Semiotics, Mathematics Education, Mathematics Tests, Test Items
Jila Niknejad; Margaret Bayer – International Journal of Mathematical Education in Science and Technology, 2025
In Spring 2020, the need for redesigning online assessments to preserve integrity became a priority to many educators. Many of us found methods to proctor examinations using Zoom and proctoring software. Such examinations pose their own issues. To reduce the technical difficulties and cost, many Zoom proctored examination sessions were shortened;…
Descriptors: Mathematics Instruction, Mathematics Tests, Computer Assisted Testing, Computer Software
Emma Walland – Research Matters, 2024
GCSE examinations (taken by students aged 16 years in England) are not intended to be speeded (i.e. to be partly a test of how quickly students can answer questions). However, there has been little research exploring this. The aim of this research was to explore the speededness of past GCSE written examinations, using only the data from scored…
Descriptors: Educational Change, Test Items, Item Analysis, Scoring
B. Goecke; S. Weiss; B. Barbot – Journal of Creative Behavior, 2025
The present paper questions the content validity of the eight creativity-related self-report scales available in PISA 2022's context questionnaire and provides a set of considerations for researchers interested in using these indexes. Specifically, we point out some threats to the content validity of these scales (e.g., "creative thinking…
Descriptors: Creativity, Creativity Tests, Questionnaires, Content Validity
Goran Trajkovski; Heather Hayes – Digital Education and Learning, 2025
This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis techniques,…
Descriptors: Artificial Intelligence, Educational Assessment, Computer Uses in Education, Test Format
Selcuk Acar; Yuyang Shen – Journal of Creative Behavior, 2025
Creativity tests, like creativity itself, vary widely in their structure and use. These differences include instructions, test duration, environments, prompt and response modalities, and the structure of test items. A key factor is task structure, referring to the specificity of the number of responses requested for a given prompt. Classic…
Descriptors: Creativity, Creative Thinking, Creativity Tests, Task Analysis
Lawrence T. DeCarlo – Educational and Psychological Measurement, 2024
A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization…
Descriptors: Test Format, Multiple Choice Tests, Item Response Theory, Models

Sami Baral; Li Lucy; Ryan Knight; Alice Ng; Luca Soldaini; Neil T. Heffernan; Kyle Lo – Grantee Submission, 2024
In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…
Descriptors: Visual Learning, Visual Perception, Natural Language Processing, Freehand Drawing
Dave Kush; Anne Dahl; Filippa Lindahl – Second Language Research, 2024
Embedded questions (EQs) are islands for filler--gap dependency formation in English, but not in Norwegian. Kush and Dahl (2022) found that first language (L1) Norwegian participants often accepted filler-gap dependencies into EQs in second language (L2) English, and proposed that this reflected persistent transfer from Norwegian of the functional…
Descriptors: Transfer of Training, Norwegian, Native Language, Grammar