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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
Almotairi, Maram; Fkih, Fethi – Journal of Education and e-Learning Research, 2022
The Question answering (QA) system plays a basic role in the acquisition of information and the e-learning environment is considered to be the field that is most in need of the question-answering system to help learners ask questions in natural language and get answers in short periods of time. The main problem in this context is how to understand…
Descriptors: Semantics, Natural Language Processing, Intelligent Tutoring Systems, Ambiguity (Semantics)
Mead, Alan D.; Zhou, Chenxuan – Journal of Applied Testing Technology, 2022
This study fit a Naïve Bayesian classifier to the words of exam items to predict the Bloom's taxonomy level of the items. We addressed five research questions, showing that reasonably good prediction of Bloom's level was possible, but accuracy varies across levels. In our study, performance for Level 2 was poor (Level 2 items were misclassified…
Descriptors: Artificial Intelligence, Prediction, Taxonomy, Natural Language Processing
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
Andrew Potter; Mitchell Shortt; Maria Goldshtein; Rod D. Roscoe – Grantee Submission, 2025
Broadly defined, academic language (AL) is a set of lexical-grammatical norms and registers commonly used in educational and academic discourse. Mastery of academic language in writing is an important aspect of writing instruction and assessment. The purpose of this study was to use Natural Language Processing (NLP) tools to examine the extent to…
Descriptors: Academic Language, Natural Language Processing, Grammar, Vocabulary Skills
Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests
Hui-Chun Chu; Yi-Chun Lu; Yun-Fang Tu – Educational Technology & Society, 2025
This study guided 97 undergraduates using generative artificial intelligence (GenAI) to conduct multimodal digital storytelling (M-DST) learning activities. Furthermore, the study examined the differences in M-DST ability and critical thinking awareness among undergraduates with different levels of learning motivation and their perceptions of this…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
Florian Hesse; Gerrit Helm – Journal of Digital Learning in Teacher Education, 2025
AI is changing the way writing is learnt at university and taught in schools. Different institutions hence call for integrating programs on writing with AI in teacher education. These must be based on the needs of the participants, which are, however, still unexplored. This article fills this gap with findings from a February 2024 questionnaire…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing (Composition), Preservice Teacher Education
Emerson, Andrew; Min, Wookhee; Azevedo, Roger; Lester, James – British Journal of Educational Technology, 2023
Game-based learning environments hold significant promise for facilitating learning experiences that are both effective and engaging. To support individualised learning and support proactive scaffolding when students are struggling, game-based learning environments should be able to accurately predict student knowledge at early points in students'…
Descriptors: Game Based Learning, Natural Language Processing, Prediction, Student Evaluation
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
Li, Xu; Ouyang, Fan; Liu, Jianwen; Wei, Chengkun; Chen, Wenzhi – Journal of Educational Computing Research, 2023
The computer-supported writing assessment (CSWA) has been widely used to reduce instructor workload and provide real-time feedback. Interpretability of CSWA draws extensive attention because it can benefit the validity, transparency, and knowledge-aware feedback of academic writing assessments. This study proposes a novel assessment tool,…
Descriptors: Computer Assisted Testing, Writing Evaluation, Feedback (Response), Natural Language Processing
Murat Demirkol; Nedim Malkoc – Educational Process: International Journal, 2023
Background/purpose: The unprecedented developments in AI-based technologies and large language models such as ChatGPT have exhibited a brand-new territory to be explored. Since its first release in November 2022, the potential utility of ChatGPT has garnered incremental attention in the scientific world, and has already accumulated a great number…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Educational Research
Michael Cowling; Joseph Crawford; Kelly-Ann Allen; Michael Wehmeyer – Australasian Journal of Educational Technology, 2023
ChatGPT and other artificial intelligence (AI) and large language models (LLMs) have hit higher education by storm. Much of the research focuses on how this -- and similar -- tools can be leveraged for effective education of undergraduate coursework students. In this study, we explore the emerging benefits and limitations of ChatGPT and LLMs in…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
Binh Nguyen Thanh; Diem Thi Hong Vo; Minh Nguyen Nhat; Thi Thu Tra Pham; Hieu Thai Trung; Son Ha Xuan – Australasian Journal of Educational Technology, 2023
In this study, we introduce a framework designed to help educators assess the effectiveness of popular generative artificial intelligence (AI) tools in solving authentic assessments. We employed Bloom's taxonomy as a guiding principle to create authentic assessments that evaluate the capabilities of generative AI tools. We applied this framework…
Descriptors: Artificial Intelligence, Models, Performance Based Assessment, Economics Education
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy