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Jill E. Stefaniak; Stephanie L. Moore – Online Learning, 2024
Generative AI presents significant opportunities for instructional designers to create content and personalize online learning environments. Alongside its benefits, generative AI also poses ethical considerations and potential risks, such as perpetuating biases or disrupting the learning process. Navigating these complexities requires an approach…
Descriptors: Artificial Intelligence, Inclusion, Electronic Learning, Technology Uses in Education
A. N. Varnavsky – IEEE Transactions on Learning Technologies, 2024
The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The…
Descriptors: Hierarchical Linear Modeling, Intelligent Tutoring Systems, Individualized Instruction, Electronic Learning
Marras, Mirko; Boratto, Ludovico; Ramos, Guilherme; Fenu, Gianni – International Journal of Artificial Intelligence in Education, 2022
Online education platforms play an increasingly important role in mediating the success of individuals' careers. Therefore, while building overlying content recommendation services, it becomes essential to guarantee that learners are provided with equal recommended learning opportunities, according to the platform principles, context, and…
Descriptors: Electronic Learning, Educational Technology, Educational Opportunities, Equal Education
Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
Janine Arantes – Policy Futures in Education, 2024
There has been a policy push in K-12 educational settings towards personalized learning in the last decade. Commercial platforms and learning designers have responded, offering learning tools to support teaching and learning through data-driven insights and recommendations. Trending towards the augmentation or replacing human teachers with…
Descriptors: Educational Policy, Individualized Instruction, Elementary Secondary Education, Electronic Learning
Yan, Hongxin; Lin, Fuhua; Kinshuk – Canadian Journal of Learning and Technology, 2022
Self-paced online learning provides great flexibility for learning, yet it brings some inherent learning barriers because of the nature of this educational paradigm. This review paper suggests some corresponding strategies to address these barriers in order to create a more supportive self-paced online learning environment. These strategies…
Descriptors: Electronic Learning, Individualized Instruction, Educational Strategies, Barriers
Xu, Xiaoshu; Zhu, Xiaoshen; Chan, Fai Man – Interactive Learning Environments, 2023
Personal Learning Environment (PLE) represents a shift of learning paradigm towards learner-centered pedagogy, where users become masters of their own learning. PLEs are best used by learners with Self-Regulated Learning (SRL) abilities. Previous research showed that learners felt lost or socially isolated in PLEs due to their limited SRL…
Descriptors: Educational Environment, Individualized Instruction, Pilot Projects, College Students
OECD Publishing, 2021
How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems. The book…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Learning Analytics
Greenhow, Christine; Graham, Charles R.; Koehler, Matthew J. – Educational Psychologist, 2022
"Online learning"--learning that involves interactions that are mediated through using digital, typically internet-based, technology--is pervasive, multi-faceted, and evolving, creating opportunities and challenges for educational research in the wake of the COVID-19 pandemic. In this special issue, we advance an interdisciplinary agenda…
Descriptors: Electronic Learning, Educational Research, Interdisciplinary Approach, Educational Technology
Boninger, Faith; Molnar, Alex; Saldaña, Christopher – Commercialism in Education Research Unit, 2020
Virtual learning and personalized learning have been at the forefront of education reform discussions for over a decade. Backed by almost $200 million philanthropic dollars from the Chan-Zuckerberg Initiative, the Gates Foundation, and others, Summit Public Schools has aggressively marketed its Summit Learning Platform to schools across the United…
Descriptors: Individualized Instruction, Electronic Learning, Charter Schools, Instructional Effectiveness
OECD Publishing, 2021
For the first time, the OECD Future of Education and Skills 2030 project conducted comprehensive curriculum analyses through the co-creation of new knowledge with a wide range of stakeholders including policy makers, academic experts, school leaders, teachers, NGOs, other social partners and, most importantly, students. This report is one of six…
Descriptors: Curriculum Evaluation, Curriculum Development, Educational Innovation, Comparative Education
Fairman, Janet C.; Smith, David J.; Pullen, Paige C.; Lebel, Steve J. – Professional Development in Education, 2023
This article describes the challenge of engaging educators in professional development (PD) that is timely and relevant to their work, and effective in stimulating instructional changes to improve student learning. The authors highlight the competing needs and goals for PD that create tensions among the external accountability demands, school…
Descriptors: Faculty Development, Evidence Based Practice, Educational Needs, Learner Engagement
Boyle, Michael; Donahue, Gail; Donoghue, Mary Pat; Faber, David A.; Jones, Frankie; Ray-Timoney, Jeannie; Tesche, Brooke; Uhl, Timothy D. – Journal of Catholic Education, 2020
The twin uncertainties of the pandemic and the economic downturn have taken a toll on our Catholic schools. Yet reports across the country are that Catholic schools have been very successful in remote learning. Although there are well-documented efforts to define the values of Catholic schools, these values are not fully known and there is still…
Descriptors: COVID-19, Pandemics, Catholic Schools, School Closing
Staker, Heather; Arnett, Thomas; Powell, Allison – Clayton Christensen Institute for Disruptive Innovation, 2020
The idea of student-centered learning is not new; teachers have long sought to design personalized, competency-based environments that are tailored to individuals and that empower students to drive their own learning. What is new is the emergence of an online learning ecosystem and, with it, the technical possibility of equipping all students with…
Descriptors: Student Centered Learning, Labor Force Development, Credentials, Competency Based Education
Taneri, Grace Ufuk – Center for Studies in Higher Education, 2020
We are living in an era of artificial intelligence (AI). There is wide discussion about and experimentation with the impact of AI on education/higher education. In this paper, we give a discussion of how AI is evolving, explore the ways AI is changing education/higher education, give a concise account of the skills universities need to teach their…
Descriptors: Artificial Intelligence, Higher Education, Electronic Learning, Blended Learning