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Zixi Li; Chen Feng – International Journal of Designs for Learning, 2024
This design case focused on the design of an intervention set aimed at capturing and sharing tacit knowledge in the workplace. The design case demonstrated the design process of expanding a single chatbot intervention into a comprehensive hybrid intervention set to cooperate with learners of different technology competencies and learning needs.…
Descriptors: Knowledge Level, Technological Literacy, Intervention, Knowledge Management
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
Haruo Kodama; Motofumi T. Suzuki; Yoshitomo Yaginuma – Asian Association of Open Universities Journal, 2024
Purpose: The purpose of this paper is to propose the need for an integrated system for the production, authoring, addition and revision of webcast content and a multi-device apps mechanism with rights management for Internet transmission in the perspective of the OUJ course reuse. Design/methodology/approach: This paper designs systems that reuse…
Descriptors: Open Universities, Computer Oriented Programs, Multimedia Materials, Video Technology
Yeo, Marie Alina – TESOL Journal, 2023
What does it mean to write, learn to write, and teach writing in an age when students can use the latest artificial intelligence (AI) co-authoring tools to produce entire essays without even adding an original idea or composing a single sentence? This article addresses questions of authorship and academic integrity concerning the use of AI writing…
Descriptors: Integrity, Ethics, Artificial Intelligence, Writing (Composition)
Ujjwal Biswas; Samit Bhattacharya – Education and Information Technologies, 2024
The application of machine learning (ML) has grown and is now used to enhance learning outcomes. In blended classroom settings, ML, emerging smartphones and wearable technologies are commonly used to improve teaching and learning. The combination of these advanced technologies and ML plays a crucial role in enhancing real-time feedback quality.…
Descriptors: Artificial Intelligence, Blended Learning, Flipped Classroom, 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
DiCarlo, Cynthia F.; Deris, Aaron R.; Deris, Thomas P. – Journal of Behavioral Education, 2023
The purpose of this study was to investigate the impact of mLearning or mobile device practice on the attention and accuracy of student's use of math concepts, specifically, telling time. A single subject, alternating treatment design was used to compare mLearning to paper and pencil practice in four 3rd grade male students. Results were mixed;…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Handheld Devices, Attention
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
Pauldy Cornelia Johanna Otermans; Stephanie Baines; Monica Pereira; Chelsea Livingstone; Dev Aditya – International Journal of Technology in Education, 2024
Revolutionary technological advancements have introduced the integration of Conversational AI into a multitude of different settings. This widespread implementation has raised questions about the impact of AI on learning, its benefits are and its potential costs. This study aims to explore the perspectives of parents, investigating their…
Descriptors: Artificial Intelligence, Parent Attitudes, Technology Uses in Education, Computer Mediated Communication
Connie Levina Yuen; Nadja Schlote – Journal of Educational Technology Systems, 2024
This study examines learners' experiences and the use of language learning applications ("apps") as a primary source of "second or additional language learning" ("L2") instruction and assessment in higher education. It purviews the integration of artificial intelligence (AI)-powered features that support…
Descriptors: Handheld Devices, Learning Experience, Computer Oriented Programs, Artificial Intelligence
Stojanovic, Danijela; Bogdanovic, Zorica; Petrovic, Luka; Mitrovic, Svetlana; Labus, Aleksandra – Interactive Learning Environments, 2023
In this paper we present an approach to employing pervasive technologies, such as IoT and mobile technologies, in secondary education. The goal is to develop a comprehensive methodology, IoT infrastructure and a mobile application that would enable secondary students to test their knowledge in interaction with a smart environment. We have…
Descriptors: Learning Processes, Secondary School Students, Technology Uses in Education, Handheld Devices
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
Berkay Ceylan; Melek Altiparmak Karakus – International Journal of Technology in Education and Science, 2024
This research aims to investigate the use of an artificial intelligence-based mobile application with plants and plant identification techniques (AImPLANT) with prospective science teachers in outdoor activities. The goals of the study are: (i) to develop an AI-based mobile application from scratch based customized for education (ii) to enhance…
Descriptors: Artificial Intelligence, Handheld Devices, Telecommunications, Computer Oriented Programs
Qianru Li; Kan Kan Chan – Education and Information Technologies, 2024
Mobile-assisted Language Learning (MALL) has been widely adopted in teaching and learning, yet there has been scant research concerning speaking test adaptation. An emerging type of mobile application is designed to facilitate test takers' performance in a high-stakes speaking test (e.g., the International English Language Testing System (IELTS)).…
Descriptors: Student Attitudes, Test Wiseness, Computer Assisted Testing, Handheld Devices
Odicar Joice Chavez; Thelma Palaoag – Journal of Research in Innovative Teaching & Learning, 2024
Purpose: This study investigates user preferences for motivational features aligned with self-determination theory (SDT), emphasizing autonomy, relatedness, and competency. The study seeks to identify the most appealing and effective motivational features in AI-driven mobile apps for fostering autonomy, promoting relatedness, and enhancing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Handheld Devices, Telecommunications
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