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Eran Hadas; Arnon Hershkovitz – Journal of Learning Analytics, 2025
Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…
Descriptors: Creativity, Evaluation Methods, Computer Assisted Testing, Artificial Intelligence
Yang Jiang; Mo Zhang; Jiangang Hao; Paul Deane; Chen Li – Journal of Educational Measurement, 2024
The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Ethics
Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
Gal Kaldes; Elizabeth L. Tighe; Qiwei He – Grantee Submission, 2024
Introduction: Despite the necessity for adults with lower literacy skills to undergo and succeed in high-stakes computer-administered assessments (e.g., GED, HiSET), there remains a gap in understanding their engagement with digital literacy assessments. Methods: This study analyzed process data, specifically time allocation data, from the Program…
Descriptors: Time Management, Adults, Literacy, Computer Assisted Testing
Jeff Ford; Rachel Erickson; Ha Le; Kaylee Vick; Jillian Downey – PRIMUS, 2024
In this study, we analyzed student participation and success in a college-level Calculus I course that utilized standards-based grading. By measuring the level to which students participate in this class structure, we were able to use a clustering algorithm that revealed multiple groupings of students that were distinct based on activity…
Descriptors: Calculus, Mathematics Instruction, Mathematics Achievement, Grades (Scholastic)
Han, Areum; Krieger, Florian; Borgonovi, Francesca; Greiff, Samuel – Large-scale Assessments in Education, 2023
Process data are becoming more and more popular in education research. In the field of computer-based assessments of collaborative problem solving (ColPS), process data have been used to identify students' test-taking strategies while working on the assessment, and such data can be used to complement data collected on accuracy and overall…
Descriptors: Behavior Patterns, Cooperative Learning, Problem Solving, Reaction Time
Kuang, Huan; Sahin, Fusun – Large-scale Assessments in Education, 2023
Background: Examinees may not make enough effort when responding to test items if the assessment has no consequence for them. These disengaged responses can be problematic in low-stakes, large-scale assessments because they can bias item parameter estimates. However, the amount of bias, and whether this bias is similar across administrations, is…
Descriptors: Test Items, Comparative Analysis, Mathematics Tests, Reaction Time
Susu Zhang; Xueying Tang; Qiwei He; Jingchen Liu; Zhiliang Ying – Grantee Submission, 2024
Computerized assessments and interactive simulation tasks are increasingly popular and afford the collection of process data, i.e., an examinee's sequence of actions (e.g., clickstreams, keystrokes) that arises from interactions with each task. Action sequence data contain rich information on the problem-solving process but are in a nonstandard,…
Descriptors: Correlation, Problem Solving, Computer Assisted Testing, Prediction
Lee, Ji-Eun; Chan, Jenny Yun-Chen; Botelho, Anthony; Ottmar, Erin – Educational Technology Research and Development, 2022
Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods (k-means clustering, data visualization) to…
Descriptors: Computer Games, Educational Games, Mathematics Instruction, Learning Processes
Lee, Ji-Eun; Chan, Jenny Yun-Chen; Botelho, Anthony; Ottmar, Erin – Grantee Submission, 2022
Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods ("k"-means clustering, data…
Descriptors: Computer Games, Educational Games, Mathematics Instruction, Learning Processes
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
Roark, Casey L.; Lehet, Matthew I.; Dick, Frederic; Holt, Lori L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Category learning is fundamental to cognition, but little is known about how it proceeds in real-world environments when learners do not have instructions to search for category-relevant information, do not make overt category decisions, and do not experience direct feedback. Prior research demonstrates that listeners can acquire task-irrelevant…
Descriptors: Classification, Learning Processes, Schemata (Cognition), Decision Making
Scoular, Claire; Care, Esther – Educational Assessment, 2019
Recent educational and psychological research has highlighted shifting workplace requirements and change required to equip the emerging workforce with skills for the 21st century. The emergence of these highlights the issues, and drives the importance, of new methods of assessment. This study addresses some of the issues by describing a scoring…
Descriptors: Cooperation, Problem Solving, Scoring, 21st Century Skills
Hedlefs-Aguilar, Maria Isolde; Morales-Martinez, Guadalupe Elizabeth; Villarreal-Lozano, Ricardo Jesus; Moreno-Rodriguez, Claudia; Gonzalez-Rodriguez, Erick Alejandro – European Journal of Educational Research, 2021
This study explored the cognitive mechanism behind information integration in the test anxiety judgments in 140 engineering students. An experiment was designed to test four factors combined (test goal orientation, test cognitive functioning level, test difficulty and test mode). The experimental task required participants to read 36 scenarios,…
Descriptors: Test Anxiety, Engineering Education, Algebra, College Students
Aryadoust, Vahid; Foo, Stacy; Ng, Li Ying – Language Testing, 2022
The aim of this study was to investigate how test methods affect listening test takers' performance and cognitive load. Test methods were defined and operationalized as while-listening performance (WLP) and post-listening performance (PLP) formats. To achieve the goal of the study, we examined test takers' (N = 80) brain activity patterns…
Descriptors: Listening Comprehension Tests, Language Tests, Eye Movements, Brain Hemisphere Functions
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