NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Po-Chun Huang; Ying-Hong Chan; Ching-Yu Yang; Hung-Yuan Chen; Yao-Chung Fan – IEEE Transactions on Learning Technologies, 2024
Question generation (QG) task plays a crucial role in adaptive learning. While significant QG performance advancements are reported, the existing QG studies are still far from practical usage. One point that needs strengthening is to consider the generation of question group, which remains untouched. For forming a question group, intrafactors…
Descriptors: Automation, Test Items, Computer Assisted Testing, Test Construction
Peer reviewed Peer reviewed
Direct linkDirect link
Semere Kiros Bitew; Amir Hadifar; Lucas Sterckx; Johannes Deleu; Chris Develder; Thomas Demeester – IEEE Transactions on Learning Technologies, 2024
Multiple-choice questions (MCQs) are widely used in digital learning systems, as they allow for automating the assessment process. However, owing to the increased digital literacy of students and the advent of social media platforms, MCQ tests are widely shared online, and teachers are continuously challenged to create new questions, which is an…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Test Construction, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Srikanth Allamsetty; M. V. S. S. Chandra; Neelima Madugula; Byamakesh Nayak – IEEE Transactions on Learning Technologies, 2024
The present study is related to the problem associated with student assessment with online examinations at higher educational institutes (HEIs). With the current COVID-19 outbreak, the majority of educational institutes are conducting online examinations to assess their students, where there would always be a chance that the students go for…
Descriptors: Computer Assisted Testing, Accountability, Higher Education, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Ka-Yan Fung; Kit-Yi Tang; Tze Leung Rick Lui; Kuen-Fung Sin; Lik-Hang Lee; Huamin Qu; Shenghui Song – IEEE Transactions on Learning Technologies, 2024
Prescreening children for specific learning disabilities, e.g., dyslexia, is essential for effective intervention. With a quick and reliable prescreening result, special education coordinators (SENCOs) can provide students with early intervention and relieve their learning pressure. Unfortunately, due to the limited resources, many students in…
Descriptors: Dyslexia, Children, Computer Software, Early Intervention
Peer reviewed Peer reviewed
Direct linkDirect link
Kangkang Li; Qian Yang; Xianmin Yang – IEEE Transactions on Learning Technologies, 2024
The student-generated question (SGQ) strategy is an effective instructional strategy for developing students' higher order cognitive and critical thinking. However, assessing the quality of SGQs is time consuming and domain experts intensive. Previous automatic evaluation work focused on surface-level features of questions. To overcome this…
Descriptors: Computer Simulation, Artificial Intelligence, Computer Assisted Testing, Automation
Peer reviewed Peer reviewed
Direct linkDirect link
Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software