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Brimzhanova, Saule; Atanov, Sabyrzhan; Moldamurat, Khuralay; Baymuhambetova, Botagoz; Brimzhanova, Karlygash; Seitmetova, Aitkul – Education and Information Technologies, 2022
Computer-based testing of humanities students has some inconveniences and difficulties, where the whole learning process is practically based on communicative methods. In this regard, one needs such a testing system, which would allow one to ask open-ended questions, and students would be able to enter detailed answers. Despite the popularity of…
Descriptors: Computer Assisted Testing, Humanities Instruction, Humanities, Mathematics
Joanna Williamson – Research Matters, 2025
Teachers, examiners and assessment experts know from experience that some candidates annotate exam questions. "Annotation" includes anything the candidate writes or draws outside of the designated response space, such as underlining, jotting, circling, sketching and calculating. Annotations are of interest because they may evidence…
Descriptors: Mathematics, Tests, Documentation, Secondary Education
Anela Hrnjicic; Adis Alihodžic – International Electronic Journal of Mathematics Education, 2024
Understanding the concepts related to real function is essential in learning mathematics. To determine how students understand these concepts, it is necessary to have an appropriate measurement tool. In this paper, we have created a web application using 32 items from conceptual understanding of real functions (CURF) item bank. We conducted a…
Descriptors: Mathematical Concepts, College Freshmen, Foreign Countries, Computer Assisted Testing
Falk, Carl F.; Feuerstahler, Leah M. – Educational and Psychological Measurement, 2022
Large-scale assessments often use a computer adaptive test (CAT) for selection of items and for scoring respondents. Such tests often assume a parametric form for the relationship between item responses and the underlying construct. Although semi- and nonparametric response functions could be used, there is scant research on their performance in a…
Descriptors: Item Response Theory, Adaptive Testing, Computer Assisted Testing, Nonparametric Statistics
Demir, Seda – Journal of Educational Technology and Online Learning, 2022
The purpose of this research was to evaluate the effect of item pool and selection algorithms on computerized classification testing (CCT) performance in terms of some classification evaluation metrics. For this purpose, 1000 examinees' response patterns using the R package were generated and eight item pools with 150, 300, 450, and 600 items…
Descriptors: Test Items, Item Banks, Mathematics, Computer Assisted Testing
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
Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Vachharajani, Vinay; Pareek, Jyoti – International Journal of Distance Education Technologies, 2020
The demand for higher education keeps on increasing. The invention of information technology and e-learning have, to a large extent, solved the problem of shortage of skilled and qualified teachers. But there is no guarantee that this will ensure the high quality of learning. In spite of large number of students, though the delivery of learning…
Descriptors: Higher Education, Educational Technology, Technology Uses in Education, Computer Assisted Testing
Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
Yu, Eliseeva Dina; Fedosov, A. Yu.; Mnatsakanyan, Olga L.; Grigoreva, Svetlana V.; Dmitrieva, Tatiana V. – NORDSCI, 2018
Building the process of education effectively and qualitatively taking into account educational needs and students' individual characteristics is possible by developing of the special technics of education, in terms of which a student not only will repeat the actions of a teacher but first of all will use different interactive and adaptive…
Descriptors: Foreign Countries, Adaptive Testing, Computer Assisted Testing, Mathematics
Ruiperez-Valiente, Jose A.; Munoz-Merino, Pedro J.; Alexandron, Giora; Pritchard, David E. – IEEE Transactions on Learning Technologies, 2019
One of the reported methods of cheating in online environments in the literature is CAMEO (Copying Answers using Multiple Existences Online), where harvesting accounts are used to obtain correct answers that are later submitted in the master account which gives the student credit to obtain a certificate. In previous research, we developed an…
Descriptors: Computer Assisted Testing, Tests, Online Courses, Identification
Steven L. Wise; Megan R. Kuhfeld; Marlit Annalena Lindner – Applied Measurement in Education, 2024
When student achievement is assessed, we seek to elicit a student's maximum performance -- a goal requiring the assumption that the student is fully engaged. Otherwise, to the extent that disengagement occurs, test performance is likely to suffer. Effectively managing test-taking disengagement requires an understanding of the testing conditions…
Descriptors: Testing, Attention Span, Learner Engagement, Time Factors (Learning)
Dixon-Román, Ezekiel; Nichols, T. Philip; Nyame-Mensah, Ama – Learning, Media and Technology, 2020
In this article, we examine the sociopolitical implications of AI technologies as they are integrated into writing instruction and assessment. Drawing from new materialist and Black feminist thought, we consider how learning analytics platforms for writing are animated by and through entanglements of algorithmic reasoning, state standards and…
Descriptors: Racial Bias, Artificial Intelligence, Educational Technology, Writing Instruction
Uzun, Kutay – Contemporary Educational Technology, 2018
Managing crowded classes in terms of classroom assessment is a difficult task due to the amount of time which needs to be devoted to providing feedback to student products. In this respect, the present study aimed to develop an automated essay scoring environment as a potential means to overcome this problem. Secondarily, the study aimed to test…
Descriptors: Computer Assisted Testing, Essays, Scoring, English Literature
Reddick, Rachel – International Educational Data Mining Society, 2019
One significant challenge in the field of measuring ability is measuring the current ability of a learner while they are learning. Many forms of inference become computationally complex in the presence of time-dependent learner ability, and are not feasible to implement in an online context. In this paper, we demonstrate an approach which can…
Descriptors: Measurement Techniques, Mathematics, Assignments, Learning

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