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Monteiro, Kátia; Crossley, Scott; Botarleanu, Robert-Mihai; Dascalu, Mihai – Language Testing, 2023
Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…
Descriptors: Second Language Learning, Second Languages, Native Language, Semantics
Unger, Layla; Yim, Hyungwook; Savic, Olivera; Dennis, Simon; Sloutsky, Vladimir M. – Developmental Science, 2023
Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…
Descriptors: Natural Language Processing, Language Usage, Vocabulary Development, Linguistic Input
Micheal M. van Wyk; Michael Agyemang Adarkwah; Samuel Amponsah – Open Praxis, 2023
The launch of ChatGPT has been revolutionary. This AI chatbot can produce conversations which are indistinguishable from that of humans. This exploratory qualitative study is foregrounded in a constructivist-interpretative perspective. The principal objective of this paper is to explore the views of academics on ChatGPT as an AI-based learning…
Descriptors: Artificial Intelligence, Natural Language Processing, Higher Education, Learning Strategies
Chau, Hung; Labutov, Igor; Thaker, Khushboo; He, Daqing; Brusilovsky, Peter – International Journal of Artificial Intelligence in Education, 2021
The increasing popularity of digital textbooks as a new learning media has resulted in a growing interest in developing a new generation of "adaptive textbooks" that can help readers to learn better through adapting to the readers' learning goals and the current state of knowledge. These adaptive textbooks are most frequently powered by…
Descriptors: Automation, Textbooks, Computer Uses in Education, Artificial Intelligence
Li, Chenglu; Xing, Wanli – International Journal of Artificial Intelligence in Education, 2021
Among all the learning resources within MOOCs such as video lectures and homework, the discussion forum stood out as a valuable platform for students' learning through knowledge exchange. However, peer interactions on MOOC discussion forums are scarce. The lack of interactions among MOOC learners can yield negative effects on students' learning,…
Descriptors: Natural Language Processing, Online Courses, Computer Mediated Communication, Artificial Intelligence
Usta, Arif; Altingovde, Ismail Sengor; Ozcan, Rifat; Ulusoy, Ozgur – IEEE Transactions on Learning Technologies, 2021
In this digital age, there is an abundance of online educational materials in public and proprietary platforms. To allow effective retrieval of educational resources, it is a necessity to build keyword-based search engines over these collections. In modern Web search engines, high-quality rankings are obtained by applying machine learning…
Descriptors: Search Engines, Online Searching, Information Retrieval, Educational Research
Condor, Aubrey; Litster, Max; Pardos, Zachary – International Educational Data Mining Society, 2021
We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…
Descriptors: Automation, Grading, Test Items, Generalization
Sabnis, Varun; Abhinav, Kumar; Subramanian, Venkatesh; Dubey, Alpana; Bhat, Padmaraj – International Educational Data Mining Society, 2021
Today, there is a vast amount of online material for learners. However, due to the lack of prerequisite information needed to master them, a lot of time is spent in identifying the right learning content for mastering these concepts. A system that captures underlying prerequisites needed for learning different concepts can help improve the quality…
Descriptors: Prerequisites, Fundamental Concepts, Automation, Natural Language Processing
Funda Nayir; Tamer Sari; Aras Bozkurt – Journal of Educational Technology and Online Learning, 2024
From personalized advertising to economic forecasting, artificial intelligence (AI) is becoming an increasingly important element of our daily lives. These advancements raise concerns regarding the transhumanist perspective and associated discussions in the context of technology-human interaction, as well as the influence of artificial…
Descriptors: Artificial Intelligence, Technology Uses in Education, Humanism, Capacity Building
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Leanne Bowler; Irene Lopatovska; Mark S. Rosin – Information and Learning Sciences, 2024
Purpose: The purpose of this study is to explore teen-adult dialogic interactions during the co-design of data literacy activities in order to determine the nature of teen thinking, their emotions, level of engagement, and the power of relationships between teens and adults in the context of data literacy. This study conceives of co-design as a…
Descriptors: Librarians, Adolescents, Language Patterns, Public Libraries
Using GPT and Authentic Contextual Recognition to Generate Math Word Problems with Difficulty Levels
Wu-Yuin Hwang; Ika Qutsiati Utami – Education and Information Technologies, 2024
Automatic generation of math word problems (MWPs) is a challenging task in Natural Language Processing (NLP), particularly connecting it to real-life problems because it can benefit students in developing a higher level of mathematical thinking. However, most of the MWPs are presented within a scholastic setting in a decontextualized way. This…
Descriptors: Artificial Intelligence, Technology Uses in Education, Mathematics Education, Word Problems (Mathematics)
Ananta Ardyansyah; Agung Budhi Yuwono; Sri Rahayu; Naif Mastoor Alsulami; Oktavia Sulistina – Journal of Chemical Education, 2024
The rapid development of artificial intelligence (AI) has transformed chatbots into generative pre-trained transformers (GPTs) capable of performing various tasks. The use of GPTs is expanding to learning, including natural sciences like chemistry. GPTs can assist students in understanding and solving chemistry problems. However, there are…
Descriptors: Foreign Countries, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Exploration of ChatGPT in Basic Education: Advantages, Disadvantages, and Its Impact on School Tasks
Raúl Alberto Garcia Castro; Nikole Alexandra Mayta Cachicatari; Willian Máximo Bartesaghi Aste; Martín Pedro Llapa Medina – Contemporary Educational Technology, 2024
The introduction of ChatGPT into basic education is progressing rapidly, generating impacts that, in many cases, are unknown. Its impressive capability profiles it as a tool that will revolutionize teaching and learning processes, creating gaps that need to be understood and evaluated. The research aims to explore the advantages, disadvantages,…
Descriptors: Artificial Intelligence, Natural Language Processing, Foreign Countries, Technology Uses in Education
Jie Zhang – International Journal of Information and Communication Technology Education, 2024
This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing the…
Descriptors: Oral Language, Translation, Computational Linguistics, Computer Software

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