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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
Yu-Min Wang; Chung-Lun Wei; Hsin-Hui Lin; Sheng-Ching Wang; Yi-Shun Wang – Interactive Learning Environments, 2024
As artificial intelligence (AI) technology rapidly develops and is deployed, students increasingly need to understand and learn AI-related skills for future employment. This study investigates how students' AI learning anxiety and AI job replacement anxiety affect intrinsic/extrinsic learning motivations and subsequent AI learning intention. The…
Descriptors: Learning Processes, Artificial Intelligence, Anxiety, Employment Opportunities
George Kalmpourtzis; Margarida Romero – Interactive Learning Environments, 2024
Taking into account the profound impact of technology on modern education, especially during the COVID-19 pandemic, increasing academic interest has focused towards the design and application of such tools on different learning contexts. A specific area of Human-Computer Interaction, called affordance theory, focuses on the perception, design and…
Descriptors: Robotics, Artificial Intelligence, Computer Software, Teaching Methods
Yun-Fang Tu; Gwo-Jen Hwang – Interactive Learning Environments, 2024
The present study employed the draw-a-picture technique and epistemic network analysis (ENA) to reveal university students' viewpoints on ChatGPT-supported learning, as well as the conceptions, roles, and educational objectives of ChatGPT-supported learning among university students with different learning attitudes. The results showed that…
Descriptors: College Students, Student Attitudes, Knowledge Level, Artificial Intelligence
Gang Lei – Interactive Learning Environments, 2024
With the emergence of the Industrial Revolution 4.0, modern technologies such as cloud computing, artificial intelligence, and big data are profoundly transforming the education ecosystem. The development of education is not only faced with huge challenges but also contains rare opportunities. New concepts such as deep learning, adaptive learning,…
Descriptors: Educational Technology, Artificial Intelligence, Blended Learning, Data
Hasan Zuhtu Okulu; Nilay Muslu – Interactive Learning Environments, 2024
ChatGPT holds significant potential for enhancing learning through integration into education as an advanced chatbot. With the goal of harnessing this potential, our research focused on exploring the utilization of ChatGPT in designing a course plan for pre-service science teachers. We adopted a qualitative research approach and employed ChatGPT…
Descriptors: Preservice Teachers, Science Teachers, Science Instruction, Instructional Design
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
Danhua Zhou – Interactive Learning Environments, 2024
Online scientific argumentation activities have significant value for students' cognitive ability. The purpose of this study was to solve the issues of online scientific argumentation. Firstly, the influences of online scientific argumentation were classified into "Learn to Argue" and "Argue to Learn" abilities. And then the…
Descriptors: Meta Analysis, Instructional Design, Instructional Effectiveness, Electronic Learning
Thomas K. F. Chiu – Interactive Learning Environments, 2024
Generative artificial intelligence (GenAI) tools have become increasingly accessible and have impacted school education in numerous ways. However, most of the discussions occur in higher education. In schools, teachers' perspectives are crucial for making sense of innovative technologies. Accordingly, this qualitative study aims to investigate how…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Standards
Yi-Fan Liu; Wu-Yuin Hwang; Chia-Hsuan Su – Interactive Learning Environments, 2024
Drama learning is helpful for English speaking, however, few studies provided students with opportunities to practice drama conversations individually. This study proposed a Context-Awareness Smart Learning Mechanism (CASLM) and integrated into SmartVpen that consisted of context-aware learning content, context-aware input assistance, oral…
Descriptors: Context Effect, Artificial Intelligence, Second Language Learning, English (Second Language)
Ting-Chia Hsu; Ching Chang; Tien-Hsiu Jen – Interactive Learning Environments, 2024
Young learners' vocabulary learning needs interaction with language input when they are engaged in an activity. Given that AI-supported image recognition technologies offer hands-on learning in authentic contexts, and that self-regulated learning (SRL) enables learners to monitor and evaluate their learning when interacting with multi-sensory…
Descriptors: Metacognition, Multisensory Learning, Vocabulary Development, Learning Strategies
Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
Lu, Jijian; Zhang, Xiaojie; Stephens, Max – Interactive Learning Environments, 2019
This study aims to visualize the commognitive processes in computer-supported one-to-one teaching and learning. By commognitive processes we mean cognitive processes and interpersonal communication. A 6-years mathematics teacher and a 15-year-old boy in China, who have done computer-supported one-to-one tutoring, were chosen to be the samples. We…
Descriptors: Communication (Thought Transfer), Learning Processes, Computer Assisted Instruction, Tutoring
Michael, Joel; Rovick, Allen; Glass, Michael; Zhou, Yujian; Evens, Martha – Interactive Learning Environments, 2003
CIRCSIM-Tutor is a computer tutor designed to carry out a natural language dialogue with a medical student. Its domain is the baroreceptor reflex, the part of the cardiovascular system that is responsible for maintaining a constant blood pressure. CIRCSIM-Tutor's interaction with students is modeled after the tutoring behavior of two experienced…
Descriptors: Natural Language Processing, Medical Students, Computer Mediated Communication, Artificial Intelligence

Shute, Valerie J.; Glaser, Robert – Interactive Learning Environments, 1990
Presents an evaluation of "Smithtown," an intelligent tutoring system designed to teach inductive inquiry skills and principles of basic microeconomics. Two studies of individual differences in learning are described, including a comparison of knowledge acquisition with traditional instruction; hypotheses tested are discussed; and the…
Descriptors: Artificial Intelligence, Cluster Analysis, Comparative Analysis, Computer Assisted Instruction