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Becker, Kirk; Meng, Huijuan – Journal of Applied Testing Technology, 2022
The rise of online proctoring potentially provides more opportunities for item harvesting and consequent brain dumping and shared "study guides" based on stolen content. This has increased the need for rapid approaches for evaluating and acting on suspicious test responses in every delivery modality. Both hiring proxy test takers and…
Descriptors: Identification, Cheating, Computer Assisted Testing, Observation
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Langenfeld, Thomas – Journal of Applied Testing Technology, 2022
The turn to online learning and training programs as a response to challenging times (i.e., the COVID-19 crisis) necessitated the need for internet-based testing solutions. Researchers generally have found that Unproctored Internet Testing (UIT) for high-stakes cognitive ability assessments results in higher scores than proctored assessments. Live…
Descriptors: Internet, Computer Assisted Testing, COVID-19, Pandemics
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Shin, Jinnie; Gierl, Mark J. – Journal of Applied Testing Technology, 2022
Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…
Descriptors: Computer Assisted Testing, Scoring, Essays, Automation
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Firoozi, Tahereh; Bulut, Okan; Epp, Carrie Demmans; Naeimabadi, Ali; Barbosa, Denilson – Journal of Applied Testing Technology, 2022
Automated Essay Scoring (AES) using neural networks has helped increase the accuracy and efficiency of scoring students' written tasks. Generally, the improved accuracy of neural network approaches has been attributed to the use of modern word embedding techniques. However, which word embedding techniques produce higher accuracy in AES systems…
Descriptors: Computer Assisted Testing, Scoring, Essays, Artificial Intelligence
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Becker, Kirk A.; Kao, Shu-chuan – Journal of Applied Testing Technology, 2022
Natural Language Processing (NLP) offers methods for understanding and quantifying the similarity between written documents. Within the testing industry these methods have been used for automatic item generation, automated scoring of text and speech, modeling item characteristics, automatic question answering, machine translation, and automated…
Descriptors: Item Banks, Natural Language Processing, Computer Assisted Testing, Scoring
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Muckle, Timothy J.; Meng, Yu; Johnson, Samuel – Journal of Applied Testing Technology, 2022
The COVID-19 pandemic has witnessed a renewed interest in Live Remote Proctoring (LRP), not only as a test availability measure but as a necessity to maintain business continuity. Many certification organizations have correspondingly provided LRP as an option for candidates. This study describes a retrospective, observational pilot study…
Descriptors: Computer Assisted Testing, Observation, Program Evaluation, Pilot Projects
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Morin, Maxim; Alves, Cecilia; De Champlain, André – Journal of Applied Testing Technology, 2022
The COVID-19 pandemic severely disrupted assessment models that were commonplace in the testing industry for decades. As a response to this disturbance, remote proctoring has emerged as a promising and potentially sound alternative to offer examinations, while adhering to public health authority guidelines. However, validity evidence in support of…
Descriptors: Distance Education, Observation, High Stakes Tests, Medical Education
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Hurtz, Gregory M.; Weiner, John A. – Journal of Applied Testing Technology, 2022
Since the onset of the pandemic in 2020, many credentialing organizations have incorporated online remote administration of their examinations to enable continuity of their programs. This paper describes a research study examining several high stakes credentialing examination programs that utilized mixed delivery modes, including online remote…
Descriptors: Comparative Analysis, Integrity, Computer Assisted Testing, Supervision