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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
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Putnikovic, Marko; Jovanovic, Jelena – IEEE Transactions on Learning Technologies, 2023
Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…
Descriptors: Automation, Computer Assisted Testing, Grading, Natural Language Processing
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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
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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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Hsu, Hao-Hsuan; Huang, Nen-Fu – IEEE Transactions on Learning Technologies, 2022
This article introduces Xiao-Shih, the first intelligent question answering bot on Chinese-based massive open online courses (MOOCs). Question answering is critical for solving individual problems. However, instructors on MOOCs must respond to many questions, and learners must wait a long time for answers. To address this issue, Xiao-Shih…
Descriptors: Foreign Countries, Artificial Intelligence, Online Courses, Natural Language Processing
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Larranaga, Mikel; Aldabe, Itziar; Arruarte, Ana; Elorriaga, Jon A.; Maritxalar, Montse – IEEE Transactions on Learning Technologies, 2022
In a concept learning scenario, any technology-supported learning system must provide students with mechanisms that help them with the acquisition of the concepts to be learned. For the technology-supported learning systems to be successful in this task, the development of didactic material is crucial--a hard task that could be alleviated by means…
Descriptors: Computer Assisted Testing, Science Tests, Multiple Choice Tests, Textbooks
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C. H., Dhawaleswar Rao; Saha, Sujan Kumar – IEEE Transactions on Learning Technologies, 2023
Multiple-choice question (MCQ) plays a significant role in educational assessment. Automatic MCQ generation has been an active research area for years, and many systems have been developed for MCQ generation. Still, we could not find any system that generates accurate MCQs from school-level textbook contents that are useful in real examinations.…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Automation, Test Items
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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
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Aldabe, Itziar; Maritxalar, Montse – IEEE Transactions on Learning Technologies, 2014
The work we present in this paper aims to help teachers create multiple-choice science tests. We focus on a scientific vocabulary-learning scenario taking place in a Basque-language educational environment. In this particular scenario, we explore the option of automatically generating Multiple-Choice Questions (MCQ) by means of Natural Language…
Descriptors: Science Tests, Test Construction, Computer Assisted Testing, Multiple Choice Tests