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Sedigheh Karimpour; Ehsan Namaziandost; Hossein Kargar Behbahani – Journal of Educational Computing Research, 2025
As an integral part of dynamic assessment, computerized dynamic assessment (CDA) offers learners computer-assisted automated mediation. Accordingly, the possible efficacy of corrective feedback seems to be enhanced with new technologies, such as artificial intelligence tools, that offer automatic corrective feedback. Using technology-enhanced…
Descriptors: Computer Assisted Testing, Feedback (Response), Language Acquisition, Electronic Learning
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Guozhu Ding; Mailin Li; Shan Li; Hao Wu – Asia Pacific Education Review, 2025
This study investigated the optimal feedback intervals for tasks of varying difficulty levels in online testing and whether task difficulty moderates the effect of feedback intervals on student performance. A pre-experimental study with 36 students was conducted to determine the delayed time for providing feedback based on student behavioral data.…
Descriptors: Feedback (Response), Academic Achievement, Computer Assisted Testing, Intervals
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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
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Arif Cem Topuz; Kinshuk – Educational Technology Research and Development, 2024
Online assessments of learning, or online exams, have become increasingly widespread with the rise of distance learning. Online exams are preferred by many students and are perceived as a quick and easy tool to measure knowledge. On the contrary, some students are concerned about the possibility of cheating and technological difficulties in online…
Descriptors: Computer Assisted Testing, Student Evaluation, Evaluation Methods, Student Attitudes
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Xuefan Li; Marco Zappatore; Tingsong Li; Weiwei Zhang; Sining Tao; Xiaoqing Wei; Xiaoxu Zhou; Naiqing Guan; Anny Chan – IEEE Transactions on Learning Technologies, 2025
The integration of generative artificial intelligence (GAI) into educational settings offers unprecedented opportunities to enhance the efficiency of teaching and the effectiveness of learning, particularly within online platforms. This study evaluates the development and application of a customized GAI-powered teaching assistant, trained…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation, Academic Achievement
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Daniel Lupiya Mpolomoka – Pedagogical Research, 2025
Overview: This systematic review explores the utilization of artificial intelligence (AI) for assessment, grading, and feedback in higher education. The review aims to establish how AI technologies enhance efficiency, scalability, and personalized learning experiences in educational settings, while addressing associated challenges that arise due…
Descriptors: Artificial Intelligence, Higher Education, Evaluation Methods, Literature Reviews
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Jessie S. Barrot – Education and Information Technologies, 2024
This bibliometric analysis attempts to map out the scientific literature on automated writing evaluation (AWE) systems for teaching, learning, and assessment. A total of 170 documents published between 2002 and 2021 in Social Sciences Citation Index journals were reviewed from four dimensions, namely size (productivity and citations), time…
Descriptors: Educational Trends, Automation, Computer Assisted Testing, Writing Tests
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Alireza Maleki – International Journal of Lifelong Education, 2025
Online learning and assessment have become a major concern for educators in the field of education due to the many challenges they present. The coronavirus lockdown has profoundly affected the instruction and evaluation processes for English as a Foreign Language (EFL) learners. Therefore, this study aims to investigate the perspectives of EFL…
Descriptors: English (Second Language), Language Teachers, Computer Assisted Testing, Barriers
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Qiao, Chen; Hu, Xiao – IEEE Transactions on Learning Technologies, 2023
Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…
Descriptors: Computer Assisted Testing, Automation, Test Items, Semantics
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Barrett, Michelle D.; Jiang, Bingnan; Feagler, Bridget E. – International Journal of Artificial Intelligence in Education, 2022
The appeal of a shorter testing time makes a computer adaptive testing approach highly desirable for use in multiple assessment and learning contexts. However, for those who have been tasked with designing, configuring, and deploying adaptive tests for operational use at scale, preparing an adaptive test is anything but simple. The process often…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Construction, Design Requirements
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Paige E. Cervantes; Robert D. Gibbons; Lawrence A. Palinkas; Greta R. Conlon; Sarah M. Horwitz – Journal of Developmental and Physical Disabilities, 2025
Because autistic youth experience increased suicide risk and there are no suicide risk screening tools for this population, existing measures need to be evaluated and then modified with input from the autism community. This pilot study obtained feedback from autistic youth, caregivers, and autism specialist clinicians (N = 14) on the applicability…
Descriptors: Autism Spectrum Disorders, Suicide, Risk, Computer Assisted Testing
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Barczak, Andre L. C.; Mathrani, Anuradha; Han, Binglan; Reyes, Napoleon H. – Educational Technology Research and Development, 2023
An important course in the computer science discipline is 'Data Structures and Algorithms' (DSA). "The coursework" lays emphasis on experiential learning for building students' programming and algorithmic reasoning abilities. Teachers set up a repertoire of formative programming exercises to engage students with different programmatic…
Descriptors: Computer Assisted Testing, Automation, Computer Science Education, Programming
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
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Daocheng Hong – Interactive Learning Environments, 2024
The digital transformation of education is greatly accelerating in various computer-supported applications. As a particularly prominent application of the human-machine interactive system, intelligent learning systems aim to capture users' current intentions and provide recommendations through real-time feedback. However, we have a limited…
Descriptors: Feedback (Response), Users (Information), Learner Engagement, Tests
Samuel S. Davidson – ProQuest LLC, 2024
Automated corrective feedback (ACF), in which a computer system helps language learners identify and correct errors in their writing or speech, is considered an important tool for language instruction by many researchers. Such systems allow learners to correct their own mistakes, thereby reducing teacher workload and potentially preventing issues…
Descriptors: Computer Assisted Testing, Automation, Student Evaluation, Feedback (Response)
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