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Showing 1 to 15 of 45 results Save | Export
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Roger Young; Emily Courtney; Alexander Kah; Mariah Wilkerson; Yi-Hsin Chen – Teaching of Psychology, 2025
Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…
Descriptors: Item Response Theory, Multiple Choice Tests, Psychology, Textbooks
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Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
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Emery-Wetherell, Meaghan; Wang, Ruoyao – Assessment & Evaluation in Higher Education, 2023
Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Cheating, Identification
Gregory J. Crowther; Usha Sankar; Leena S. Knight; Deborah L. Myers; Kevin T. Patton; Lekelia D. Jenkins; Thomas A. Knight – Journal of Microbiology & Biology Education, 2023
The biology education literature includes compelling assertions that unfamiliar problems are especially useful for revealing students' true understanding of biology. However, there is only limited evidence that such novel problems have different cognitive requirements than more familiar problems. Here, we sought additional evidence by using…
Descriptors: Science Instruction, Artificial Intelligence, Scoring, Molecular Structure
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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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Jenny Yun-Chen Chan; Avery H. Closser; Vy Ngo; Hannah Smith; Allison S. Liu; Erin Ottmar – Journal of Computer Assisted Learning, 2023
Background: Prior work has shown that middle school students struggle with algebra and that game-based educational technologies, such as DragonBox and From Here to There!, are effective at improving students' algebraic performance. However, it remains unclear which aspects of algebraic knowledge shift as a result of playing these games and what…
Descriptors: Teaching Methods, Game Based Learning, Middle School Students, Algebra
Mingying Zheng – ProQuest LLC, 2024
The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…
Descriptors: Artificial Intelligence, Computational Linguistics, Language Tests, English (Second Language)
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Zhang, Lishan; VanLehn, Kurt – Interactive Learning Environments, 2021
Despite their drawback, multiple-choice questions are an enduring feature in instruction because they can be answered more rapidly than open response questions and they are easily scored. However, it can be difficult to generate good incorrect choices (called "distractors"). We designed an algorithm to generate distractors from a…
Descriptors: Semantics, Networks, Multiple Choice Tests, Teaching Methods
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Moro, Sérgio; Martins, António; Ramos, Pedro; Esmerado, Joaquim; Costa, Joana Martinho; Almeida, Daniela – Computers in the Schools, 2020
Many university programs include Microsoft Excel courses given their value as a scientific and technical tool. However, evaluating what is effectively learned by students is a challenging task. Considering multiple-choice written exams are a standard evaluation format, this study aimed to uncover the features influencing students' success in…
Descriptors: Multiple Choice Tests, Test Items, Spreadsheets, Computer Software
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Alammary, Ali – IEEE Transactions on Learning Technologies, 2021
Developing effective assessments is a critical component of quality instruction. Assessments are effective when they are well-aligned with the learning outcomes, can confirm that all intended learning outcomes are attained, and their obtained grades are accurately reflecting the level of student achievement. Developing effective assessments is not…
Descriptors: Outcomes of Education, Alignment (Education), Student Evaluation, Data Analysis
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Pelánek, Radek; Effenberger, Tomáš; Kukucka, Adam – Journal of Educational Data Mining, 2022
We study the automatic identification of educational items worthy of content authors' attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and…
Descriptors: Item Analysis, Identification, Difficulty Level, Case Studies
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Liao, Linyu – English Language Teaching, 2020
As a high-stakes standardized test, IELTS is expected to have comparable forms of test papers so that test takers from different test administration on different dates receive comparable test scores. Therefore, this study examined the text difficulty and task characteristics of four parallel academic IELTS reading tests to reveal to what extent…
Descriptors: Second Language Learning, English (Second Language), Language Tests, High Stakes Tests
Beauchamp, David; Constantinou, Filio – Research Matters, 2020
Assessment is a useful process as it provides various stakeholders (e.g., teachers, parents, government, employers) with information about students' competence in a particular subject area. However, for the information generated by assessment to be useful, it needs to support valid inferences. One factor that can undermine the validity of…
Descriptors: Computational Linguistics, Inferences, Validity, Language Usage
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Chen, Binglin; West, Matthew; Ziles, Craig – International Educational Data Mining Society, 2018
This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…
Descriptors: Accuracy, Probability, Student Behavior, Test Items
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Karlin, Omar; Karlin, Sayaka – InSight: A Journal of Scholarly Teaching, 2018
This study had two aims. The first was to explain the process of using the Rasch measurement model to validate tests in an easy-to-understand way for those unfamiliar with the Rasch measurement model. The second was to validate two final exams with several shared items. The exams were given to two groups of students with slightly differing English…
Descriptors: Item Response Theory, Test Validity, Test Items, Accuracy
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