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Hannah Bryant – ProQuest LLC, 2023
This qualitative case study addresses the rise in popularity of the use of predictive text programs within the K-12 educational environment. A problem exists in the discrepancy between the widespread availability of Google Smart Compose within Google Docs, an AI predictive text tool, within the school environment, and a distinct lack of research…
Descriptors: Process Approach (Writing), Technology Uses in Education, Web 2.0 Technologies, Influence of Technology
Hsiao-Ling Hsu; Howard Hao-Jan Chen; Andrew G. Todd – Interactive Learning Environments, 2023
With advances in technology, intelligent personal assistants (IPAs) have become available to assist users with a variety of tasks using voice commands. Because IPAs may induce dialogic interactions, researchers speculated that they may benefit second language learning, especially regarding pronunciation, listening and speaking skills. So far, very…
Descriptors: Foreign Countries, College Students, English (Second Language), Artificial Intelligence
Kahraman, Deniz; Koc, Mustafa – International Society for Technology, Education, and Science, 2022
It is considered important for school principals to have technology leadership competencies in digital age conditions in order to carry out education and training efficiently and effectively. Since teachers see school principals as role models, how teachers perceive the technology use skills of school principals is an important factor for the…
Descriptors: Instructional Leadership, Educational Technology, Information Technology, Technology Integration
Ritonga, Mahyudin; Zulmuqim, Zulmuqim; Bambang, Bambang; Kurniawan, Rahadian; Pahri, Pahri – World Journal on Educational Technology: Current Issues, 2022
Information technology provides a lot of convenience for humans in completing their tasks and getting results according to targets. In line with that, language teachers have a duty to find out the level of language skills and forms of language errors in students. Machine Learning as part of technology can be maximized to detect forms of Arabic…
Descriptors: Arabic, Error Correction, Video Technology, Speech Communication
Mohammed Abdulmalik Ali – Eurasian Journal of Applied Linguistics, 2022
Machine Translation (MT) is an engine that accelerates language learning, design creation, and contemporary comprehension of many areas of language and communication based on our qualitative understanding of secondary resources. Arab students regard Arabic as a source language that is afterwards translated into English texts and words in order to…
Descriptors: Translation, Arabs, Arabic, Cultural Influences
Paquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
Bennett, Amy; Inglis, Matthew; Gilmore, Camilla – Journal of Educational Psychology, 2019
Parents are frequently advised to use number books to help their children learn the meaning of number words and symbols. How should these resources be designed to best support learning? Previous research has shown that number books typically include multiple concrete representations of number. However, a large body of mathematics education…
Descriptors: Numbers, Symbols (Mathematics), Mathematical Concepts, Learning Strategies
Yeung, Chun-Kit; Yeung, Dit-Yan – International Journal of Artificial Intelligence in Education, 2019
The 2017 ASSISTments Data Mining competition aims to use data from a longitudinal study for predicting a brand-new outcome of students which had never been studied before by the educational data mining research community. Specifically, it facilitates research in developing predictive models that predict whether the first job of a student out of…
Descriptors: Data Analysis, Careers, Prediction, Employment
Sennott, Samuel C.; Akagi, Linda; Lee, Mary; Rhodes, Anthony – Topics in Language Disorders, 2019
Artificially intelligent tools have given us the capability to use technology to address ever more complex challenges. What are the capabilities, challenges, and hazards of incorporating and developing this technology for augmentative and alternative communication (AAC)? "Artificial intelligence" (AI) can be defined as the capability of…
Descriptors: Augmentative and Alternative Communication, Artificial Intelligence, Knowledge Representation, Thinking Skills
Mason, Blake; Rau, Martina A.; Nowak, Robert – Cognitive Science, 2019
Visual representations are prevalent in STEM instruction. To benefit from visuals, students need representational competencies that enable them to see meaningful information. Most research has focused on explicit conceptual representational competencies, but implicit perceptual competencies might also allow students to efficiently see meaningful…
Descriptors: Visual Aids, STEM Education, Task Analysis, Competence
Luckin, Rosemary; Cukurova, Mutlu – British Journal of Educational Technology, 2019
Interdisciplinary research from the learning sciences has helped us understand a great deal about the way that humans learn, and as a result we now have an improved understanding about how best to teach and train people. This same body of research must now be used to better inform the development of Artificial Intelligence (AI) technologies for…
Descriptors: Instructional Design, Educational Technology, Artificial Intelligence, Mathematics
Rosé, Carolyn P.; McLaughlin, Elizabeth A.; Liu, Ran; Koedinger, Kenneth R. – British Journal of Educational Technology, 2019
Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…
Descriptors: Discovery Learning, Man Machine Systems, Artificial Intelligence, Models
Pigeau, Antoine; Aubert, Olivier; Prié, Yannick – International Educational Data Mining Society, 2019
Success prediction in Massive Open Online Courses (MOOCs) is now tackled in numerous works, but still needs new case studies to compare the solutions proposed. We study here a specific dataset from a French MOOC provided by the OpenClassrooms company, featuring 12 courses. We exploit various features present in the literature and test several…
Descriptors: Success, Large Group Instruction, Online Courses, Prediction
Reading Matrix: An International Online Journal, 2025
This systematic review examines 22 studies (2024-2025) on the use of generative AI, primarily ChatGPT, for providing feedback in English writing instruction for language learners. It identifies the types of feedback AI offers, its effectiveness relative to teacher and peer feedback, and perceptions from students and teachers. Findings show AI…
Descriptors: Writing Instruction, Teaching Methods, English (Second Language), Second Language Learning
Qiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests

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