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Raj Sandu; Ergun Gide; Mahmoud Elkhodr – Discover Education, 2024
Artificial intelligence (AI) tools, notably ChatGPT, are increasingly recognised for their transformative potential in higher education. This study employs a detailed case study approach complemented by a survey, delving into ChatGPT's impact on pedagogical practices, student engagement, and academic performance. It involved 74 undergraduate and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Foreign Countries
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Dorottya Demszky; Jing Liu; Heather C. Hill; Dan Jurafsky; Chris Piech – Educational Evaluation and Policy Analysis, 2024
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage…
Descriptors: Online Courses, Automation, Feedback (Response), Large Group Instruction
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Pedro Isaias, Editor; Demetrios G. Sampson, Editor; Dirk Ifenthaler, Editor – Cognition and Exploratory Learning in the Digital Age, 2024
The Cognition and Exploratory Learning in the Digital Age (CELDA) conference focuses on discussing and addressing the challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress of technological innovation, in the context of the digital age. In each edition, CELDA, gathers researchers and…
Descriptors: Artificial Intelligence, Cognitive Processes, Discovery Learning, Teaching Methods
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Marcel Mierwald – Journal of Educational Media, Memory and Society, 2024
Generative artificial intelligence (AI) offers new opportunities for history education, such as the ability to chat with historical figures. However, little is known about pupils' interaction with AI applications such as ChatGPT. A qualitative case study was conducted to explore how pupils (n = 21, year nine, fourteen years old) interacted with…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, History Instruction
Allard, Danièle; Mizoguchi, Riichiro – Research and Practice in Technology Enhanced Learning, 2021
This article introduces a novel, holistic framework--named Dr. Mosaik--that encompasses explanations of the entire tense-aspect system, while highlighting eight comprehensive rules that explain the main workings of the system. In turn, this provides a limited number of "anchor points" on which to time-efficiently address instruction and…
Descriptors: Intensive Language Courses, English, Morphemes, Form Classes (Languages)
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Albertson, Brendon – Research-publishing.net, 2021
A Computer-Assisted Language Learning (CALL) application, TextMix, was developed as a proof-of-concept for applying Natural Language Processing (NLP) sentence chunking techniques to creating 'sentence scramble' learning tasks. TextMix addresses limitations of existing applications for creating sentence scrambles by using NLP to parse and scramble…
Descriptors: Computer Assisted Instruction, Second Language Learning, Natural Language Processing, Sentences
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Lin, Jiayin; Sun, Geng; Beydoun, Ghassan; Li, Li – Educational Technology & Society, 2022
A newly emerged micro learning service offers a flexible formal, informal, or non-formal online learning opportunity to worldwide users with different backgrounds in real-time. With the assist of big data technology and cloud computing service, online learners can access tremendous fine-grained learning resources through micro learning service.…
Descriptors: Translation, Natural Language Processing, Informal Education, Online Courses
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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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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)
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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
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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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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
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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
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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
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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
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