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Assim S. Alrajhi – Education and Information Technologies, 2025
Motivated by the proliferation of artificial intelligence that has the potential to promote self-access learning, this study utilizes a sequential explanatory quasi-experimental mixed methods design to investigate the efficacy of Google Assistant (GA) in facilitating second language (L2) vocabulary learning compared to online dictionaries. A…
Descriptors: English (Second Language), Second Language Learning, Artificial Intelligence, Vocabulary Development
Jing Shi; Na Wan; Roslina Ibrahim – International Journal of Web-Based Learning and Teaching Technologies, 2024
The application of computer technology has revolutionized and promoted the traditional mode of piano teaching. Nowadays, many companies and institutions have begun to apply computer technology to online piano teaching. This paper analyzes the difficulties faced by students in piano teaching and the development of piano assistant practice and…
Descriptors: Music Education, Musical Instruments, Teaching Methods, Algorithms
Yizhou Fan; Luzhen Tang; Huixiao Le; Kejie Shen; Shufang Tan; Yueying Zhao; Yuan Shen; Xinyu Li; Dragan Gaševic – British Journal of Educational Technology, 2025
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of supports from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. In particular, there has been a surge of academic interest in human-AI collaboration and…
Descriptors: College Students, Writing Achievement, Writing Exercises, Artificial Intelligence
Richey, J. Elizabeth; McEldoon, Katherine; Tan, Elaine – Pearson, 2023
Pearson's Learning Foundations describe the optimal conditions for learning and reflect the learner experience Pearson hopes their products will create. Pearson does this by incorporating the Learning Design Principles. Each of the Learning Design Principles goes into detail about a key principle, supporting product design and marketing by…
Descriptors: Theory Practice Relationship, Research and Development, Individualized Instruction, Intelligent Tutoring Systems
Boussaha, Karima; Boussouf, Raouf Amir – International Journal of Virtual and Personal Learning Environments, 2022
Several researchers studied the impact of collaboration between the learners, but few studies have been carried out on the impact of collaboration between teachers. In the previous work, the authors have studied the impact of the collaboration among the learners with a specific collaborative CEHL(K. Boussaha et al.,2015). In this work, the authors…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Coaching (Performance), Intelligent Tutoring Systems

Micah Watanabe; Megan Imundo; Katerina Christhilf; Tracy Arner; Danielle S. McNamara – Grantee Submission, 2024
Reading comprehension is essential for students' ability to build knowledge. Students' comprehension abilities can be enhanced by providing students with deliberate practice and formative feedback on reading comprehension strategies. iSTART is an Intelligent Tutoring System (ITS) that is designed to provide instruction in reading strategies with…
Descriptors: Reading Comprehension, Reading Strategies, Intelligent Tutoring Systems, Reading Instruction
Eglington, Luke G.; Pavlik, Philip I., Jr. – International Journal of Artificial Intelligence in Education, 2023
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Erika L. Thompson; Toufeeq Ahmed Syed; Zainab Latif; Katie Stinson; Damaris Javier; Gabrielle Saleh; Jamboor K. Vishwanatha – Journal for STEM Education Research, 2025
Given the differences in trajectory for under-represented minorities in biomedical careers, we sought to explore how a virtual mentoring program, the National Research Mentoring Network (NRMN), and its platform (MyNRMN), may facilitate transitions in the science, technology, engineering, mathematics, and medicine (STEMM) pipeline. The purpose of…
Descriptors: College Students, STEM Education, STEM Careers, Medical Education
Moore, Robert L.; Jiang, Shiyan; Abramowitz, Brian – Journal of Research on Technology in Education, 2023
This systematic review examines the empirical literature published between 2014 and 2021 that situates artificial intelligence within K-12 educational contexts. Our review synthesizes 12 articles and highlights artificial intelligence's instructional contexts and applications in K-12 learning environments. We focused our synthesis on the learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Secondary Education, Computer Assisted Instruction
Eglington, Luke G.; Pavlik, Philip I., Jr. – Grantee Submission, 2022
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Tyson, Matthew Mark; Sauers, Nicholas J. – Journal of Educational Administration, 2021
Purpose: The purpose of this study is to examine school leaders' experiences with adoption and implementation of artificial intelligence systems in their schools. It examined the factors that led educational administrators to adopt one artificial intelligence program (ALEKS) and their perceptions around the implementation process.…
Descriptors: Principals, Administrator Attitudes, Technology Integration, Artificial Intelligence
Suwicha Wittayakom; Chintana Kanjanavisutt; Methinee Wongwanich Rumpagaporn – Higher Education Studies, 2024
This systematic literature review explores the implementation and effectiveness of active learning approaches in online training environments. The rapid growth of online education necessitates strategies that enhance learner engagement and improve educational outcomes. The review identifies various active learning techniques, such as discussions,…
Descriptors: Online Courses, Training, Active Learning, Learning Strategies
Chen, Fei; Xia, Quansheng; Feng, Yan; Wang, Lan; Peng, Gang – Journal of Computer Assisted Learning, 2023
Background: Teaching Mandarin as a second language (L2) has become an important profession and an important research area. The acquisition of unaspirated and aspirated consonants in Mandarin has been reported to be rather challenging for L2 learners. Objectives: In the current study, a 3-D airflow model was integrated into the virtual talking head…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Mandarin Chinese, Models
Abbigail Kubiak; Sue Ann Sisto; Janice Tona – Journal of Occupational Therapy Education, 2025
We investigated the outcomes of a novel neuroscience and neuroanatomy support program (NSP) developed and implemented in the pre-professional phase of an accredited Bachelor of Science/ Master of Science occupational therapy (OT) program. This research demonstrates the potential of targeted small group tutoring as an effective means to promote…
Descriptors: Occupational Therapy, Neurosciences, Allied Health Occupations Education, College Students
Olney, Andrew M.; Gilbert, Stephen B.; Rivers, Kelly – Grantee Submission, 2021
Cyberlearning technologies increasingly seek to offer personalized learning experiences via adaptive systems that customize pedagogy, content, feedback, pace, and tone according to the just-in-time needs of a learner. However, it is historically difficult to: (1) create these smart learning environments; (2) continuously improve them based on…
Descriptors: Educational Technology, Computer Assisted Instruction, Learning Analytics, Intelligent Tutoring Systems