Sae Schatz, Ph.D., Director of the ADL Initiative, is an applied human–systems scientist, with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation. Frequently, her work seeks to enhance individuals’ higher-order cognitive skills (i.e., the mental, emotional, and relational skills associated with “cognitive readiness”). Dr. Schatz has applied her efforts to defense training and education for roughly a decade, and she holds a doctorate in Modeling and Simulation from the University of Central Florida.
Hanni Muukkonen is professor in Educational Psychology at the University of Oulu, Finland. She has completed her PhD in Psychology at the University of Helsinki. Her research interests include collaborative learning, knowledge creation, learning analytics and methodological development. She currently leads a large national learning analytics research and development project to support students' study paths, guidance and leadership in higher education.
Learning analytics can be used at various levels of granularity to examine and visualize learning paths of students and groups. Learning analytics refers to the measurement, collection, analysis and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which learning occurs. Data can be collected and analysis provided at the student, teacher or course, institution or governmental level. Typically, at the student level, various data from course-based learning environment activities is collected, which enables the reflection and analysis of progress or personal goals. At the institutional level, analytics may help to identify needed guidance or refinement of curricula or services to support fluent study paths. Further, artificial intelligence methods which combine register-based and activity-based data. in applications and advanced feedback designs can make the progress in studies visible to involved actors. What takes place between data being collected and presented back to the end-users is critical to maintain the transparency of analytical procedures and algorithm use, i.e., what is actually being represented by the visualizations. Ethical, legal and data protection issues play an important role in the definition of practices and standards for use of analytics in institutions.
Avron Barr started his career as a programmer at Stanford University; editor of the seminal Handbook of Artificial Intelligence; and founder of Teknowledge, an early AI startup in Silicon Valley. Since Teknowledge was sold in 1986, he has been an independent consultant, helping people understand, explain, and market cutting-edge software. Currently, he consults for the Institute for Defense Analyses and supports the US Advanced Distributed Learning Initiative’s Total Learning Architecture project. He volunteers as Chair of the IEEE Learning Technology Standards Committee and spends his free time hiking in the redwood forests around Santa Cruz, California.
AI-enhanced software can teach, and these smart computer programs will get much better at teaching in the years to come. We will review some examples of the use of artificial intelligence technologies in education and training today, as well as some cutting edge research projects that point to AI’s future in the schools. Turning to adoption and impact, we’ll discuss the technical infrastructure that will be needed to deploy these smart systems effectively, especially as regards learners’ data and data governance issues. Finally, we look at the impact on students, teachers, and schools. We propose a re-engineering approach to organizational change that might help educators get ahead of these inevitable developments.
NATO Civilian for 29 years with roles in command and control, education and training of C4ISR systems and online learning and training technology.
Since its inception and adoption, online learning has seen many trends and "fads". Immersive, game based, mobile, video, AI, social, and now micro. How have these been implemented, how successful have they been and where do we stand now? The presenter will review these trends and via an interactive session with the audience see how many have merged together. What has worked, what is working and where should we be aiming for to meet our present and future requirements.
Keynote speakers: 45 mins.
Speakers (Auditorium): 30 mins.
Parallel sessions: 40 mins.
Workshops: 2x40 mins. or
Workshop: 90 mins.
Exhibition in every break