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Spino, LeAnne L.; Echevarría, Megan M.; Wu, Yu – Foreign Language Annals, 2022
The ACTFL Oral Proficiency Interview--computer (OPIc) employs a self-assessment instrument to determine the nature of the speaking prompts to which the test taker will respond and, thus the difficulty of the test. Grounded in research demonstrating varying levels of accuracy in self-assessment among language learners, this study examines the…
Descriptors: Computer Assisted Testing, Oral Language, Language Proficiency, Self Evaluation (Individuals)
Parte, Laura; Mellado, Lucía – Online Learning, 2022
This study sheds light on the relation between assessment modalities and student behavior through linguistics styles, and academic performance. First, we examine the effect of assessment modalities (self-evaluation quizzes and summative quizzes) on academic performance. Using two modalities of online quizzes, we mainly focus on the student…
Descriptors: Academic Achievement, Distance Education, Tests, Student Attitudes
Emerson, David J.; Smith, Kenneth J. – Accounting Education, 2022
The recent pandemic necessitated a migration to online instruction leading to concerns regarding the integrity of online assessments as a result of the presence of fee-based websites that disseminate answers to students. We validated this concern by evaluating student performance on an online quiz where some of the questions had easily searchable…
Descriptors: Homework, Web Sites, Educational Technology, Cheating
Erdem-Kara, Basak; Dogan, Nuri – International Journal of Assessment Tools in Education, 2022
Recently, adaptive test approaches have become a viable alternative to traditional fixed-item tests. The main advantage of adaptive tests is that they reach desired measurement precision with fewer items. However, fewer items mean that each item has a more significant effect on ability estimation and therefore those tests are open to more…
Descriptors: Item Analysis, Computer Assisted Testing, Test Items, Test Construction
Sahin Kursad, Merve; Cokluk Bokeoglu, Omay; Cikrikci, Rahime Nukhet – International Journal of Assessment Tools in Education, 2022
Item parameter drift (IPD) is the systematic differentiation of parameter values of items over time due to various reasons. If it occurs in computer adaptive tests (CAT), it causes errors in the estimation of item and ability parameters. Identification of the underlying conditions of this situation in CAT is important for estimating item and…
Descriptors: Item Analysis, Computer Assisted Testing, Test Items, Error of Measurement
A. Corinne Huggins-Manley; Brandon M. Booth; Sidney K. D'Mello – Grantee Submission, 2022
The field of educational measurement places validity and fairness as central concepts of assessment quality (AERA, APA, NCME, 2014). Prior research has proposed embedding fairness arguments within argument-based validity processes, particularly when fairness is conceived as comparability in assessment properties across groups (Chapelle, 2021; Xi,…
Descriptors: Educational Assessment, Persuasive Discourse, Validity, Artificial Intelligence
Ben Seipel; Patrick C. Kennedy; Sarah E. Carlson; Virginia Clinton-Lisell; Mark L. Davison – Grantee Submission, 2022
As access to higher education increases, it is important to monitor students with special needs to facilitate the provision of appropriate resources and support. Although metrics such as ACT's (formerly American College Testing) "reading readiness" provide insight into how many students may need such resources, they do not specify…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Reading Tests, Reading Comprehension
A. Corinne Huggins-Manley; Brandon M. Booth; Sidney K. D'Mello – Journal of Educational Measurement, 2022
The field of educational measurement places validity and fairness as central concepts of assessment quality. Prior research has proposed embedding fairness arguments within argument-based validity processes, particularly when fairness is conceived as comparability in assessment properties across groups. However, we argue that a more flexible…
Descriptors: Educational Assessment, Persuasive Discourse, Validity, Artificial Intelligence
Carol Eckerly; Yue Jia; Paul Jewsbury – ETS Research Report Series, 2022
Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Scoring
Leiah J. Groom-Thomas; Monica G. Lee; Cate Smith Todd; Kathleen Lynch; Susanna Loeb; Scott R. McConnell; Lydia J. Carlis – Annenberg Institute for School Reform at Brown University, 2022
Many preschool agencies nationwide continue to experience closures and/or conversions to virtual or hybrid instruction due to the ongoing COVID-19 pandemic. Despite the importance of understanding young children's learning and development during the COVID emergency, limited knowledge exists on adaptable practices of assessing young children during…
Descriptors: COVID-19, Pandemics, Federal Programs, Low Income Students
Maria Fahlgren; Mats Brunström – International Journal of Mathematical Education in Science and Technology, 2025
This paper provides some insights into the use of example-generating tasks in the design of a technology-rich learning environment to enhance students' mathematical thinking. The paper reports on an early stage of a design-based research project concerning the design of tasks and associated feedback utilising the affordances provided by a combined…
Descriptors: Mathematics Instruction, Educational Technology, Technology Uses in Education, Computer Software
Andrea Fernández-Sánchez; Juan José Lorenzo-Castiñeiras; Ana Sánchez-Bello – European Journal of Education, 2025
The advent of artificial intelligence (AI) technologies heralds a transformative era in education. This study investigates the integration of AI tools in developing educational assessment rubrics within the 'Curriculum Design Development and Evaluation' course at the University of A Coruña during the 2023-2024 academic year. Employing an…
Descriptors: Foreign Countries, Higher Education, Artificial Intelligence, Technology Integration
Shujun Liu; Azzeddine Boudouaia; Xinya Chen; Yan Li – Asia-Pacific Education Researcher, 2025
The application of Automated Writing Evaluation (AWE) has recently gained researchers' attention worldwide. However, the impact of AWE feedback on student writing, particularly in languages other than English, remains controversial. This study aimed to compare the impacts of Chinese AWE feedback and teacher feedback on Chinese writing revision,…
Descriptors: Foreign Countries, Middle School Students, Grade 7, Writing Evaluation
Hai Li; Wanli Xing; Chenglu Li; Wangda Zhu; Simon Woodhead – Journal of Learning Analytics, 2025
Knowledge tracing (KT) is a method to evaluate a student's knowledge state (KS) based on their historical problem-solving records by predicting the next answer's binary correctness. Although widely applied to closed-ended questions, it lacks a detailed option tracing (OT) method for assessing multiple-choice questions (MCQs). This paper introduces…
Descriptors: Mathematics Tests, Multiple Choice Tests, Computer Assisted Testing, Problem Solving
Haoxin Xu; Tianrun Deng; Xianlong Xu; Xiaoqing Gu; Lingyun Huang; Haoran Xie; Minhong Wang – Education and Information Technologies, 2025
In the 21st century, the urgent educational demand for cultivating complex skills in vocational training and learning is met with the effectiveness of the four-component instructional design model. Despite its success, research has identified a notable gap in the address of formative assessment, particularly within computer-supported frameworks.…
Descriptors: Models, Instructional Design, Computer Assisted Testing, Formative Evaluation

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