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Chen, Chia-Wen; Wang, Wen-Chung; Chiu, Ming Ming; Ro, Sage – Journal of Educational Measurement, 2020
The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
Pugh, Debra; De Champlain, André; Gierl, Mark; Lai, Hollis; Touchie, Claire – Research and Practice in Technology Enhanced Learning, 2020
The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants…
Descriptors: Computer Assisted Testing, Test Construction, Multiple Choice Tests, Test Items
Erdemir, Mustafa; Akyuz, Halil Ibrahim – Journal on School Educational Technology, 2020
The purpose of this study is to reduce ethics violations such as tricking and cheating that may occur in the offline assessment of undergraduate level Physics-II (Electricity) course subjects. The study is significant for the reliable and ethical evaluation of the Internet and computer-based educational process. Thirty-eight pre-service teachers…
Descriptors: Test Reliability, Ethics, Cheating, Undergraduate Students
Agnew, Stephen; Kerr, Jane; Watt, Richard – Australasian Journal of Educational Technology, 2021
This research explored the effect of incentives to complete online quizzes during a course. When a 1% weighting incentive per quiz was removed, student engagement dropped dramatically. There is also evidence that students who continued to complete quizzes did so with less vigour, spending less time on each quiz, starting them later in the week and…
Descriptors: Student Behavior, Academic Achievement, Incentives, Behavior Modification
Somers, Rick; Cunningham-Nelson, Samuel; Boles, Wageeh – Australasian Journal of Educational Technology, 2021
In this study, we applied natural language processing (NLP) techniques, within an educational environment, to evaluate their usefulness for automated assessment of students' conceptual understanding from their short answer responses. Assessing understanding provides insight into and feedback on students' conceptual understanding, which is often…
Descriptors: Natural Language Processing, Student Evaluation, Automation, Feedback (Response)
Oncul, Bilal – International Technology and Education Journal, 2021
With the effect of the pandemic, higher education is maintained all over the world with the help of online education methods. How to make online exams, which are an important part of distance education processes, in a way to prevent cheating and illegal behavior is an important issue that brings with it discussions. This research, in which the…
Descriptors: Cheating, Computer Assisted Testing, Literature Reviews, Supervision
Tan, Choon Yong Alex; Swe, Kye Mon Min; Poulsaeman, Veronica – Quality Assurance in Education: An International Perspective, 2021
Purpose: The purpose of this case study is to share the authors' involvement and observation in adopting online exam as an evaluation tool, in the hope that others may too be able to adapt and circumvent this lockdown period while bringing a more reliable methodological approach in an online exam. Design/methodology/approach: This is a case study…
Descriptors: Computer Assisted Testing, COVID-19, Pandemics, School Closing
Dadashzadeh, Mohammad – Journal of Instructional Pedagogies, 2021
The COVID-19 shutdown of in-person university classrooms in Spring 2020 brought the question of how to conduct online examinations into urgent focus. Although, online education has been around since 1984 and online exams have been routinely built into online course syllabi, the mid-semester transition to online teaching confronted many instructors…
Descriptors: Computer Assisted Testing, Supervision, Cheating, Examiners
Zhai, Xiaoming; Shi, Lehong; Nehm, Ross H. – Journal of Science Education and Technology, 2021
Machine learning (ML) has been increasingly employed in science assessment to facilitate automatic scoring efforts, although with varying degrees of success (i.e., magnitudes of machine-human score agreements [MHAs]). Little work has empirically examined the factors that impact MHA disparities in this growing field, thus constraining the…
Descriptors: Meta Analysis, Man Machine Systems, Artificial Intelligence, Computer Assisted Testing
Wyse, Adam E. – Educational and Psychological Measurement, 2021
An essential question when computing test--retest and alternate forms reliability coefficients is how many days there should be between tests. This article uses data from reading and math computerized adaptive tests to explore how the number of days between tests impacts alternate forms reliability coefficients. Results suggest that the highest…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Reliability, Reading Tests
Uto, Masaki; Okano, Masashi – IEEE Transactions on Learning Technologies, 2021
In automated essay scoring (AES), scores are automatically assigned to essays as an alternative to grading by humans. Traditional AES typically relies on handcrafted features, whereas recent studies have proposed AES models based on deep neural networks to obviate the need for feature engineering. Those AES models generally require training on a…
Descriptors: Essays, Scoring, Writing Evaluation, Item Response Theory
Ludwig, Jeffrey – International Journal of Educational Methodology, 2021
In modern times, the importance of education cannot be overstated. Beyond the acquisition of knowledge, perhaps the most important aim of education may be the development of character in individuals, including vitality, courage, sensitiveness, and intelligence, from which our society may experience increased prosperity, peace, and freedom. In this…
Descriptors: Active Learning, Cooperative Learning, Computer Assisted Testing, Mathematics Instruction
Huang, Enmou; Jiang, Lianjiang; Yang, Manzhen – Educational Technology Research and Development, 2021
In recent years, growing interest is shown in Technology-aided formative assessment (TAFA) and language learning. Research has shed light on the experimentation and effectiveness of various TAFA tools, focusing on their pedagogical advantages in assisting the teaching of particular linguistic skills (reading, writing, spelling, etc.). Taking an…
Descriptors: Affordances, Computer Assisted Testing, Formative Evaluation, Second Language Instruction
Saxon, D. Patrick; Morante, Edward A. – Journal of Developmental Education, 2021
Recent research on entering college student assessment instruments and placement practices has been critical. Critics suggest that commonly used assessment instruments are inaccurate, misused, and lack predictive validity. This article describes valid criticisms and appropriate uses of assessment instruments. It also lists challenges and provides…
Descriptors: Student Evaluation, Student Placement, College Students, Evaluation Methods
Ockey, Gary J.; Neiriz, Reza – Assessment in Education: Principles, Policy & Practice, 2021
As our understanding of the construct of oral communication (OC) has evolved, so have the possibilities of computer technology undertaking the delivery of tests that measure this ability. It is paramount to understand to what extent such developments lead to accurate, comprehensive, and useful assessment of OC. In this paper, we discuss five…
Descriptors: Speech Communication, Computer Assisted Testing, Speech Tests, English (Second Language)