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Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Brenna Griffen; Elizabeth R. Lorah; Nicolette Caldwell; Donald A. Hantula; John Nosek; Matt Tincani; Shea Lemley – Journal of Developmental and Physical Disabilities, 2024
Handwashing is a vital skill for maintaining health and hygiene. For individuals with intellectual and developmental disabilities (IDD), such as autism spectrum disorder, evidence-based strategies, such as prompting and task analysis, may be effective in teaching these skills. Due to the shortage of experts who teach individuals with IDD skills…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Health Behavior, Hygiene
Tsung-Ying Chen – Journal of Psycholinguistic Research, 2024
Artificial grammar learning (AGL) is an experimental paradigm frequently adopted to investigate the unconscious and conscious learning and application of linguistic knowledge. This paper will introduce ENIGMA (https://enigma-lang.org) as a free, flexible, and lightweight Web-based tool for running online AGL experiments. The application is…
Descriptors: Artificial Intelligence, Grammar, Computer Software, Handheld Devices
Linda Castañeda; Victoria I. Marín; Daniel Villar-Onrubia – Educational Technology Research and Development, 2024
Technology-mediated interactions and datafication are increasingly central in contemporary social dynamics and institutions, including teaching and learning processes. In order to fully understand the complex entanglements of human and non-human actants that emerge in postdigital education, it is essential to imagine new methodological approaches…
Descriptors: Learning Activities, Topology, Learning Processes, Technology Uses in Education
Saadeh Z. Sweidan; Shyam K. Almawajdeh; Ayah M. Khawaldeh; Khalid A. Darabkh – Education and Information Technologies, 2024
The teaching of children with Autism spectrum disorder (ASD) in Arabic-speaking countries depends mainly on the traditional techniques which are limited and outdated. On the other hand, smartphone applications (apps) have become an essential part of the current life style. They are literally used to accomplish thousands of different tasks related…
Descriptors: Autism Spectrum Disorders, Children, Computer Oriented Programs, Visual Aids
Saman Ebadi; Asieh Amini – Interactive Learning Environments, 2024
Artificial Intelligence (AI) technology in the educational context, particularly chatbotics, has made significant changes in learning English. This mixed-methods study is intended to explore university students' attitudes toward the potential role of artificial intelligence (AI)-assisted mobile applications. Meanwhile, the role of social presence…
Descriptors: Artificial Intelligence, Educational Technology, English (Second Language), Second Language Learning
Luis Alberto Laurens-Arredondo – Education and Information Technologies, 2024
The use of technologies in the classroom has become one of the main allies for university teachers in pedagogical innovation, especially during, and after the pandemic. Therefore, the main objective of this article is to investigate how different types of innovative technologies are most effective in increasing motivation among university…
Descriptors: Educational Technology, Student Motivation, Technology Uses in Education, College Students
Victor K. Y. Chan – International Association for Development of the Information Society, 2024
This article seeks to explore the convergent validity of (and thus the consistency between) a few popular generative artificial intelligence (AI) robots in evaluating popular mobile learning apps' usability. The three robots adopted in the study were Microsoft Copilot, Google PaLM, and Meta Llama, which were individually instructed to accord…
Descriptors: Computer Oriented Programs, Handheld Devices, Telecommunications, Usability
Tiffany Tseng; Matt J. Davidson; Luis Morales-Navarro; Jennifer King Chen; Victoria Delaney; Mark Leibowitz; Jazbo Beason; R. Benjamin Shapiro – ACM Transactions on Computing Education, 2024
Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect…
Descriptors: Artificial Intelligence, Models, Data Processing, Design
Moser, Luca – International Association for Development of the Information Society, 2021
Despite the positive effects of mobile augmented reality (MAR)-tools for learning, MAR-tools are not commonly used in classrooms. The scientific discourse identified a lack of concepts that guide the practical application of mobile augmented reality (MAR)-tools in education. Teachers often feel insecure when designing and applying digital learning…
Descriptors: Telecommunications, Handheld Devices, Educational Technology, Technology Uses in Education
Fichten, Catherine; Jorgensen, Mary; Havel, Alice; Vo, Christine; Libman, Eva – Online Submission, 2022
We present eight studies dealing with artificial intelligence and mobile apps that assist post-secondary students with attention deficit hyperactivity disorder (ADHD) and other disabilities with their academic work. Study 1, based on an advisory board and on a Google search, provided glowing testimonials about AI tools. However, Study 2, a scoping…
Descriptors: Artificial Intelligence, College Students, Telecommunications, Computer Oriented Programs
Subigya K. Nepal – ProQuest LLC, 2024
The integration of behavioral sensing and Artificial Intelligence (AI) has increasingly proven invaluable across various domains, offering profound insights into human behavior, enhancing mental health monitoring, and optimizing workplace productivity. This thesis presents five pivotal studies that employ smartphone, wearable, and laptop-based…
Descriptors: Artificial Intelligence, Handheld Devices, Influence of Technology, Technological Advancement
Baskas, Richard S. – Online Submission, 2022
When teaching an online class, there are many forms of technology that are available for teachers to use to work with students. Online classes allow students the opportunity to use a variety of mobile devices to make it easier for students to participate in online classes. A literature review was conducted through Google and GoogleScholar to…
Descriptors: Educational Technology, Technology Uses in Education, Online Courses, Telecommunications
Shi, Zhixing; Ma, Junjie – Online Submission, 2021
The development and popularization of online classroom is an inevitable trend given the tremendous progress of science and technology and the advent of 5G information era. In this special period, if possible, most of the offline classes are converted to online classes, using tablets or computers for online classes. Online classes are divided into…
Descriptors: Educational Technology, Educational Innovation, Online Courses, Technology Uses in Education
Cho, Eunsoon; Cho, Young Hoan; Grant, Michael M.; Song, Donggil; Huh, Yeol – TechTrends: Linking Research and Practice to Improve Learning, 2020
The Korean Society for Educational Technology (KSET) hosted its second panel discussion partnering with the Association for Educational Communications and Technology (AECT) at the 2019 AECT Convention in Las Vegas, Nevada. A total of four panelists, two from Korea and two from the U.S., participated in the discussion on the trends of educational…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Telecommunications