Publication Date
In 2025 | 10 |
Since 2024 | 33 |
Since 2021 (last 5 years) | 135 |
Since 2016 (last 10 years) | 251 |
Since 2006 (last 20 years) | 451 |
Descriptor
Computer Assisted Testing | 460 |
Feedback (Response) | 460 |
Foreign Countries | 212 |
Formative Evaluation | 122 |
Student Evaluation | 122 |
Student Attitudes | 113 |
Educational Technology | 111 |
Evaluation Methods | 98 |
College Students | 78 |
Computer Software | 76 |
Teaching Methods | 75 |
More ▼ |
Source
Author
Cutumisu, Maria | 5 |
Jordan, Sally | 4 |
Laakso, Mikko-Jussi | 4 |
Lee, Hee-Sun | 4 |
Liu, Ou Lydia | 4 |
Pallant, Amy | 4 |
Economides, Anastasios A. | 3 |
Heffernan, Neil T. | 3 |
Hwang, Gwo-Jen | 3 |
McNamara, Danielle S. | 3 |
Mulholland, Matthew | 3 |
More ▼ |
Publication Type
Education Level
Location
Australia | 27 |
United Kingdom | 26 |
China | 18 |
Spain | 18 |
Taiwan | 17 |
Iran | 10 |
Canada | 9 |
Turkey | 9 |
California | 8 |
Finland | 6 |
Germany | 6 |
More ▼ |
Laws, Policies, & Programs
Individuals with Disabilities… | 1 |
No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Does not meet standards | 1 |
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
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
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
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
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
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
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
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
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)
Tadd Farmer; Michael C. Johnson; Jorin D. Larsen; Lance E. Davidson – Advances in Physiology Education, 2025
Team-based learning (TBL) is an active learning instructional strategy shown to improve student learning in large-enrollment courses. Although early implementations of TBL proved generally effective in an undergraduate exercise physiology course that delivered an online individual readiness assurance test (iRAT) before class, the instructor…
Descriptors: Cooperative Learning, Active Learning, Undergraduate Students, Exercise Physiology
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Plasencia, Javier – Biochemistry and Molecular Biology Education, 2023
Multiple studies have shown that testing contributes to learning at all educational levels. In this observational classroom study, we report the use of a learning tool developed for a Genetics and Molecular Biology course at the college level. An interactive set of practice exams that included 136 multiple choice questions (MCQ) or matching…
Descriptors: Molecular Biology, Genetics, Science Tests, College Science
Richard Say; Denis Visentin; Annette Saunders; Iain Atherton; Andrea Carr; Carolyn King – Journal of Computer Assisted Learning, 2024
Background: Formative online multiple-choice tests are ubiquitous in higher education and potentially powerful learning tools. However, commonly used feedback approaches in online multiple-choice tests can discourage meaningful engagement and enable strategies, such as trial-and-error, that circumvent intended learning outcomes. These strategies…
Descriptors: Feedback (Response), Self Management, Formative Evaluation, Multiple Choice Tests