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Showing 1 to 15 of 19 results Save | Export
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Yu-Ju Lan; Scott Grant; Hui-Chin Yeh – Educational Technology & Society, 2025
This study investigated the use of virtual chatbots in a 3D multi-user virtual environment (3D MUVE) to enhance the communication skills of Chinese as a foreign language (CFL) learners. Several virtual chat agents, developed using pattern matching techniques and embedded in Second Life, created a blended learning environment in which CFL learners…
Descriptors: Artificial Intelligence, Communication Skills, Educational Technology, Technology Uses in Education
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Geoffrey Currie; Josie Currie; Sam Anderson; Johnathan Hewis – Health Education Journal, 2024
Introduction: In Australia, 54.3% of medical students are women yet they remain under-represented in stereotypical perspectives of medicine. While potentially transformative, generative artificial intelligence (genAI) has the potential for errors, misrepresentations and bias. GenAI text-to-image production could reinforce gender biases making it…
Descriptors: Gender Bias, Artificial Intelligence, Computer Software, Medical Education
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Norbert Noster; Sebastian Gerber; Hans-Stefan Siller – Digital Experiences in Mathematics Education, 2024
The use of large language models like ChatGPT is widely discussed for educational purposes. Using this technology requires teachers to have appropriate competences that incorporate knowledge of how to make use of this technology. In this study, we investigate pre-service teachers' knowledge through the lens of the KTMT model ("Knowledge for…
Descriptors: Preservice Teachers, Mathematics Skills, Problem Solving, Technology Uses in Education
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Mai Abdullah Alqaed – Advanced Education, 2024
Artificial intelligence (AI) is gaining wide attention in second language learning as a beneficial tool. The current research investigates EFL learners' perceptions and usage of AI applications among 68 undergraduate English language major students. The aim is to enhance students' awareness of valuable AI applications and involve them with AI…
Descriptors: Artificial Intelligence, Student Attitudes, English (Second Language), Second Language Instruction
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Zachary W. Taylor; Brett McCartt; Tahagod Babekir – Texas Education Review, 2024
Across many language backgrounds, a consistent hurdle to accessing United States higher education is understanding the basic information necessary to apply for admission and financial aid and complete the many enrollment management processes necessary to begin one's college career (apply for housing, receive and submit vaccinations, register for…
Descriptors: Arabic, Native Speakers, Access to Education, Higher Education
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Alexander, Katarzyna; Savvidou, Christine; Alexander, Chris – Teaching English with Technology, 2023
Recent developments in AI technologies and the increasing accessibility of AI tools, such as ChatGPT, have raised concerns about academic integrity in higher education. Thus, this research aims to shed light on the challenges faced by English as a Second Language (ESL) lecturers in identifying AI-generated texts, and highlighting the skills and…
Descriptors: Identification, Artificial Intelligence, Writing Assignments, Second Language Learning
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Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
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Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
Misato Hiraga – ProQuest LLC, 2024
This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…
Descriptors: Japanese, Computational Linguistics, Form Classes (Languages), Error Analysis (Language)
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Young, Nicholas T.; Caballero, Marcos D. – Journal of Educational Data Mining, 2021
We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…
Descriptors: Prediction, Models, Learning Analytics, Mathematics
Olney, Andrew M. – Grantee Submission, 2021
In contrast to simple feedback, which provides students with the correct answer, elaborated feedback provides an explanation of the correct answer with respect to the student's error. Elaborated feedback is thus a challenge for AI in education systems because it requires dynamic explanations, which traditionally require logical reasoning and…
Descriptors: Feedback (Response), Error Patterns, Artificial Intelligence, Test Format
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Christopher Saarna – International Journal of Technology in Education, 2024
This study seeks to clarify whether teachers are able to distinguish between essays written by English L2 students or generated by ChatGPT. 47 instructors who hold experience teaching English to native speakers of Japanese in universities or other higher education institutions were tested on whether they could identify between human written essays…
Descriptors: Identification, Artificial Intelligence, Computer Software, Grammar
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Kortemeyer, Gerd – Physical Review Physics Education Research, 2023
Massive pretrained language models have garnered attention and controversy due to their ability to generate humanlike responses: Attention due to their frequent indistinguishability from human-generated phraseology and narratives and controversy due to the fact that their convincingly presented arguments and facts are frequently simply false. Just…
Descriptors: Artificial Intelligence, Physics, Science Instruction, Introductory Courses
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Liu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
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Yoke Lian Lau – International Society for Technology, Education, and Science, 2023
Three categories of audio recordings, a web service platform, and commercial software were involved in this analysis process. The three categories of audio recordings included eight filtered student recordings, an audio recording provided by a Mandarin instructor from University Malaysia Sabah, and an audio recording generated by Text-to-Speech…
Descriptors: Speech Communication, Acoustics, Mandarin Chinese, Second Language Learning
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