Badrul H. Khan, Ph.D. is a world-renowned speaker, author, educator and consultant in the field of e-learning and educational technology. Professor Khan has the credit of first coining the phrase Web based instruction and popularizing the concept through his 1997 best-selling Web-Based Instruction book which paved the way for the new field of e-learning. Known as the founder of modern e-learning, Dr. Khan has been honored with many awards and worldwide acclamation throughout his career. In recognition of his unique contribution to the field of e-learning coupled with his services to worldwide e-learning communities, Egyptian E-Learning University Council on August 13, 2012 appointed Dr. Badrul Khan as an honorary distinguished professor of e-learning. Professor Khan is a United States Distance Learning Association (USDLA) 2015 Hall of Fame Inductee. He is recognized as one of the Leaders in Open and Distance Education in North America. He is Founder of GyanBahan (GyanBahan.com), the Knowledge Carrier - a practical application of competency-based lifelong e-learning. He authored 12 books in e-learning and his Managing E-learning book has been translated into 20 languages.
He served as the founding Director of the Educational Technology Leadership (ETL) graduate cohort program at The George Washington University. He also served as the founding Director of the Educational Technology (ET) graduate program at the University of Texas, Brownsville. His personal Website: BadrulKhan.com/
Microlearning can be viewed as a single objective focused, outcome based, stand alone, meaningful, and interactive learning unit delivered in bite-sized snippets (i.e., a short modular format) either digitally (i.e., via computer, tablet, or mobile phone) or non-digitally (i.e., as via a flashcard or booklet). Designing and delivering microlearning requires thoughtful analysis and investigation of how to use the learning media’s potential in concert with instructional design principles and issues critical to various dimensions of the learning environment. In this keynote presentation, microlearning will be discussed from the perspective of a comprehensive framework encompassing the eight critical learning issues of learning including: pedagogical, technological, interface design, evaluation, management, resource support, ethical considerations and institutional. Attributes and Characteristics of microlearning will be discussed. Examples of microlearning in practice will also be demonstrated.
Sae Schatz, Ph.D., serves as the Director of the Advanced Distributed Learning (ADL) Initiative, a science, technology, and policy program under the Office of the Secretary of Defense in the U.S. Department of Defense. Before joining the government in 2015, Sae worked as an applied human–systems scientist, with an emphasis on human cognition and learning, adaptive systems, learning technologies, performance assessment, and modeling and simulation. Sae has authored numerous peer-reviewed scholarly publications, and she led development of 3 military textbooks. More recently, she co-edited the book, Modernizing Learning: Building the Future Learning Ecosystem, which defines a blueprint for revolutionizing training and education through technology, data, next-generation learning science, and innovation. Sae has worked in defense training and education for over a decade, and she holds a doctorate in Modeling and Simulation from UCF.
Dr. Sae Schatz, Director of the Advanced Distributed Learning (ADL) Initiative at the US Department of Defense, will describe the foundational technologies, policies, and partnerships that are accelerating the development of a globally connected future learning ecosystem. With her focus on modernizing learning, Dr. Schatz aims to tear down barriers to interoperability by creating a common currency (data) that facilitates lifelong learning. ADL Initiative projects are advancing the development and broad adoption of a Total Learning Architecture (TLA), which features a framework of international standards to harmonize the structure, meaning, and treatment of learning data, so they can be used across domains to improve the efficiency of education and training systems.