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Bryan Abendschein; Xialing Lin; Chad Edwards; Autumn Edwards; Varun Rijhwani – Journal of Computer Assisted Learning, 2024
Background: Education is often the primary arena for exploring and integrating new technologies. AI and human-machine communication (HMC) are prevalent in the classroom, yet we are still learning how student perceptions of these tools will impact education. Objectives: We sought to understand student perceptions of credibility related to written…
Descriptors: Students, Student Attitudes, Feedback (Response), Writing (Composition)
Cherner, Todd; Fegely, Alex; Hou, Chenyu; Halpin, Peter – Journal of Interactive Learning Research, 2023
Skilled orators and their public speaking skills have been held in high esteem since antiquity. Artificial intelligence-powered presentation platforms (AI-PPPs) are an emerging educational technology that provides a virtual venue and AI audience for users to practice a presentation or pitch and receive feedback to improve their public speaking…
Descriptors: Artificial Intelligence, Teaching Methods, Public Speaking, Educational Technology
Khalid Bashir Hajam; Sanjib Gahir – Journal of Educational Technology Systems, 2024
The research seeks to delve into and comprehend the attitudes of university students regarding artificial intelligence (AI) and to identify potential factors influencing these attitudes. The research employs a descriptive research design with a quantitative approach. A sample of 240 university students, including both males and females, was…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Gender Differences
Anna Koufakou – Education and Information Technologies, 2024
Student opinions for a course are important to educators and administrators, regardless of the type of the course or the institution. Reading and manually analyzing open-ended feedback becomes infeasible for massive volumes of comments at institution level or online forums. In this paper, we collected and pre-processed a large number of course…
Descriptors: Learning, Opinions, Student Attitudes, Natural Language Processing
Amanda E. Graf – ProQuest LLC, 2024
The purpose of this qualitative study was to learn how digital-native college students perceive of cheating and plagiarism. Today's students grew up with high-speed internet, smartphones, and instant access to information. Their learning environment was greatly altered during the COVID-19 pandemic, shifting many from in-person to online learning.…
Descriptors: College Students, Private Colleges, Religious Colleges, Cheating
Ching Sing Chai; Ding Yu; Ronnel B. King; Ying Zhou – SAGE Open, 2024
As artificial intelligence (AI) permeates almost all aspects of our lives, university students need to acquire relevant knowledge, skills, and attitudes to adapt to the challenges it poses. This study reports the development and validation of a scale called the Artificial Intelligence Learning Intention Scale (AILIS). AILIS was designed to measure…
Descriptors: Artificial Intelligence, Intention, Measures (Individuals), Development
Keunjae Kim; Kyungbin Kwon – Education and Information Technologies, 2024
The popularity of artificial intelligence (AI) has highlighted the necessity of K-12 AI education, particularly at the elementary level. However, the lack of a comprehensive and age-appropriate AI curriculum integrated into school subjects, along with the abstract and complex nature of AI concepts, exacerbates student inequalities. Researchers…
Descriptors: Artificial Intelligence, Curriculum Development, Program Effectiveness, Elementary School Students
Adil Baqach; Amal Battou – Education and Information Technologies, 2024
Nowadays, e-learning is a significant learning option, especially in light of the COVID-19 pandemic. However, it is a very challenging task because, in online courses, tutors have no direct interaction with students, which causes most of them to lose interest and ultimately drop out of their studies. In regular classes, teachers can see how each…
Descriptors: MOOCs, Student Attitudes, Student Reaction, Tutors
Tian Song; Hang Zhang; Yijia Xiao – IEEE Transactions on Learning Technologies, 2024
High-quality programming projects for education are critically required in teaching. However, it is hard to develop those projects efficiently and artificially constrained by the lecturers' experience and background. The recent popularity of large language models (LLMs) has led to a great number of applications in the field of education, but…
Descriptors: Artificial Intelligence, Education, Intellectual Disciplines, Undergraduate Students
Ghadah Al Murshidi; Galina Shulgina; Anastasiia Kapuza; Jamie Costley – Smart Learning Environments, 2024
Generative Artificial Intelligence (GAI) holds promise for enhancing the educational experience by providing personalized feedback and interactive simulations. While its integration into classrooms would improve education, concerns about how students may use AI in the class has prompted research on the perceptions related to the intention to…
Descriptors: Artificial Intelligence, Educational Experience, Feedback (Response), Interaction
Sahari, Yousef; Al-Kadi, Abdu M. Talib; Ali, Jamal Kaid Mohammed – Journal of Psycholinguistic Research, 2023
This preliminary cross-sectional study, focusing on Artificial Intelligence (AI), aimed to assess the impact of ChatGPT on translation within an Arab context. It primarily explored the attitudes of a sample of translation teachers and students through semi-structured interviews and projective techniques. Data collection included gathering…
Descriptors: Artificial Intelligence, Translation, Incidence, Student Attitudes
Jiahong Su; Weipeng Yang – Journal of Computer Assisted Learning, 2024
Background: The number of artificial intelligence (AI) literacy studies in K-12 education has recently increased, with most research focusing on primary and secondary education contexts. Little research focuses on AI literacy programs in early childhood education. Objectives: The aim of this mixed-methods study is to examine the feasibility of an…
Descriptors: Foreign Countries, Artificial Intelligence, Kindergarten, Young Children
Namin Shin; Eunyoung Choi; Sejin Chang – Education and Information Technologies, 2024
This research endeavors to introduce a comprehensive scale tailored to gauge high school students' attitudes toward AI-based interviews for university admissions. Moreover, the study delves into the impact of information provisioning on students' attitudes toward AI-based interviews. The participant cohort comprised 604 high school students, who…
Descriptors: High School Students, Student Attitudes, Artificial Intelligence, College Admission
Rustam Shadiev; Xun Wang; Xuan Chen; Elena Gayevskaya; Nikolay Borisov – Education and Information Technologies, 2024
Recent evidence suggests that not many studies on technology-supported cross-cultural learning considered creating authentic, immersive learning environments and addressing the language barrier in communication among representatives of different cultures which are very critical matters in the field. The present study attempted to address this gap.…
Descriptors: Learning Activities, Technology Uses in Education, Translation, Student Attitudes
Lifang Bai; Yijia Wei – IEEE Transactions on Learning Technologies, 2024
ChatGPT can promptly reformulate a text and improve its quality in content and form while preserving the original meaning. Yet, little is known about how learners respond to such reformulations. Here, we employed a three-stage writing task (composing-comparison-rewriting) to investigate how learners notice, integrate, and perceive ChatGPT's…
Descriptors: English (Second Language), Second Language Learning, Writing Evaluation, Artificial Intelligence