Publication Date
In 2025 | 21 |
Since 2024 | 52 |
Since 2021 (last 5 years) | 80 |
Since 2016 (last 10 years) | 86 |
Since 2006 (last 20 years) | 87 |
Descriptor
Computational Linguistics | 88 |
Teaching Methods | 88 |
Artificial Intelligence | 86 |
Computer Software | 64 |
Second Language Learning | 32 |
Technology Uses in Education | 30 |
Second Language Instruction | 29 |
Foreign Countries | 28 |
English (Second Language) | 20 |
Learning Processes | 20 |
Comparative Analysis | 17 |
More ▼ |
Source
Author
Godwin-Jones, Robert | 2 |
Jionghao Lin | 2 |
Lehr, Caroline | 2 |
Abdelaziz Boumahdi | 1 |
Abdelghani Es-Sarghini | 1 |
Abdu Al-Kadi | 1 |
Adam Tauman Kalai | 1 |
Ades, Tal | 1 |
Adrian Kirwan | 1 |
Agnieszka Kaluzna | 1 |
Ahmet Can Uyar | 1 |
More ▼ |
Publication Type
Education Level
Location
China | 5 |
Germany | 2 |
India | 2 |
Japan | 2 |
Taiwan | 2 |
Thailand | 2 |
United Kingdom | 2 |
Australia | 1 |
Germany (Berlin) | 1 |
Greece | 1 |
Indonesia | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
Flesch Reading Ease Formula | 2 |
Force Concept Inventory | 2 |
Flesch Kincaid Grade Level… | 1 |
International English… | 1 |
Peabody Picture Vocabulary… | 1 |
What Works Clearinghouse Rating
Adrian Kirwan – Irish Educational Studies, 2024
Since its arrival in late 2022, ChatGPT has occupied the minds of academics, administrators and students. Reactions to the emergence of Large Language Models (LLMs) have varied but significant anxieties about their impact on assessment have arisen. To address these concerns, this article serves three purposes; firstly, it seeks to gauge the…
Descriptors: Integrity, Computational Linguistics, Artificial Intelligence, Technology Uses in Education
Gustavo Simas da Silva; Vânia Ribas Ulbricht – International Association for Development of the Information Society, 2023
ChatGPT and Bard, two chatbots powered by Large Language Models (LLMs), are propelling the educational sector towards a new era of instructional innovation. Within this educational paradigm, the present investigation conducts a comparative analysis of these groundbreaking chatbots, scrutinizing their distinct operational characteristics and…
Descriptors: Comparative Analysis, Teaching Methods, Computer Software, Artificial Intelligence
Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
Bryan R. Drost; Char Shryock – Phi Delta Kappan, 2025
Creating assessment questions aligned to standards is a time-consuming task for teachers, but large language models such as ChatGPT can help. Bryan Drost & Char Shryock describe a three-step process for using ChatGPT to create assessments: 1) Ask ChatGPT to break standards into measurable targets. 2) Determine how much time to spend on each…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Teaching Methods
Bitzenbauer, Philipp – Contemporary Educational Technology, 2023
Large language models, such as ChatGPT, have great potential to enhance learning and support teachers, but they must be used with care to tackle limitations and biases. This paper presents two easy-to-implement examples of how ChatGPT can be used in physics classrooms to foster critical thinking skills at the secondary school level. A pilot study…
Descriptors: Physics, Science Instruction, Teaching Methods, Computer Software
Alberto Giretti; Dilan Durmus; Massimo Vaccarini; Matteo Zambelli; Andrea Guidi; Franco Ripa di Meana – International Association for Development of the Information Society, 2023
This paper provides a possible strategy for integrating large language artificial intelligence models (LLMs) in supporting students' education in artistic or design activities. We outline the methodological foundations concerning the integration of CHATGPT LLM in the educational approach aimed at enhancing artistic conception and design ideation.…
Descriptors: Art Education, Design, Artificial Intelligence, Computer Software
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
Chih-Hung Wu; Ting-Sheng Weng; Chih-Hsing Liu – Educational Technology & Society, 2025
With the growing attention directed towards ChatGPT and its applications in education, this study explored its impact on various variables pertaining to student learning. Specifically, an integrated theoretical framework was used to investigate the factors that influence student problem-solving and critical thinking abilities when using ChatGPT…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Learning Motivation
Pardo-Ballester, Cristina – Foreign Language Annals, 2022
This case study examines an online introductory Spanish-English translation course focused on learning Spanish through machine translation. Fifty-three Spanish learners were guided by their teacher to rethink, reflect, and interpret what Google Translate offered. Quantitative and qualitative analyses of learners' reports and teacher feedback…
Descriptors: Translation, Teaching Methods, Online Courses, Introductory Courses
Jian-Hong Ye; Mengmeng Zhang; Weiguaju Nong; Li Wang; Xiantong Yang – Education and Information Technologies, 2025
ChatGPT, as an example of generative artificial intelligence, possesses high-level conversational and problem-solving capabilities supported by powerful computational models and big data. However, the powerful performance of ChatGPT might enhance learner dependency. Although it has not yet been confirmed, many teachers and scholars are also…
Descriptors: Artificial Intelligence, College Students, Problem Solving, Student Attitudes

Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Peng Wang; Kexin Yin; Mingzhu Zhang; Yuanxin Zheng; Tong Zhang; Yanjun Kang; Xun Feng – Education and Information Technologies, 2025
In the era of educational informatization, nurturing critical thinking skills has become a central focus. However, the current state of Chinese students' critical thinking development is concerning, prompting researchers to explore effective enhancement strategies. Based on constructivist learning theory, this study leveraged the advancements in…
Descriptors: Critical Thinking, Skill Development, Artificial Intelligence, Computer Software
Li, Yuheng; Rakovic, Mladen; Poh, Boon Xin; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2022
Learning objectives, especially those well defined by applying Bloom's taxonomy for Cognitive Objectives, have been widely recognized as important in various teaching and learning practices. However, many educators have difficulties developing learning objectives appropriate to the levels in Bloom's taxonomy, as they need to consider the…
Descriptors: Educational Objectives, Taxonomy, Universities, Cognitive Ability
Gautham Arun; Vivek Perumal; Francis Paul John Bato Urias; Yan En Ler; Bryan Wen Tao Tan; Ranganath Vallabhajosyula; Emmanuel Tan; Olivia Ng; Kian Bee Ng; Sreenivasulu Reddy Mogali – Anatomical Sciences Education, 2024
Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and…
Descriptors: Artificial Intelligence, Teaching Methods, Computational Linguistics, Anatomy

Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence