Artificial intelligence is enabling dramatic improvements in education by providing learners with immersive personalized experiences, empowering teachers to be more effective, and giving administrators predictive analytics to achieve superior outcomes. AI also significantly increases access for learners and lowers costs, and helps overcome some of the most persistent skill gaps in the global workforce. When the education and training industry takes full advantage of this new technology the impact will be profound, as much as the adoption of compulsory education was in the 19th century.
To provide insight into the promise and potential of this new technology, Alelo offers a webinar series on the Future of AI in Education. We will look at the impact of AI on the experience of learners and teachers, the education and training industry, and the global economy. Seminar speakers will include Alelo experts as well as other thought leaders in the global community of artificial intelligence in education.
The following is the initial webinar schedule. Alelo plans to add further seminars by international leaders in artificial intelligence in education in the coming months.
How AI is Solving the #1 Skill Gap in the Global Economy
Dr. W. Lewis Johnson
Wednesday, May 23, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, May 24, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Click here to listen to the recording
A recent analysis by LinkedIn of job openings reveals that communication skills are the number 1 skill gap in the US today. Artificial intelligence is now starting to be applied effectively to develop communication skills and other soft skills, at a lower cost than was previously possible. AI can objectively measure soft skills and promote rapid learning. This will lead to great benefits for workers and employers alike, with implications for the global economy.
Will Teachers be Replaced by Algorithms?
Dr. W. Lewis Johnson and Karen Chiang
Wednesday, June 6, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, June 7, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Click here to listen to the recording
Futurists claim that intelligent machines will replace teachers within 10 years. Should teachers really be worried? On the contrary, AI is more likely to empower teachers, reduce drudgery and overwork, and make their jobs more rewarding. We will present examples from experiences integrating AI into blended learning programs.
How Will AI and Data-Driven Learning Transform the Global Education Industry?
Dr. W. Lewis Johnson
Wednesday, July 11, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT Click Here to Register
Co-Sponsored by SIIA
AI is enabling a new data-driven approach to the design and delivery of instruction. Cloud-based AI tools automatically collect and analyze data from learners, making them analytics tools as much as learning tools. Machine-learning algorithms applied to learner data accelerate improvements in system performance. Teachers and administrators can use the resulting analytics to detect learner problems and intervene quickly. This webinar will describe how AI and data-driven learning are accelerating innovation, will help drive the transition from school-based learning to ubiquitous lifelong learning, and will fundamentally transform the global education industry.
Rose Luckin, Ph.D.
Wednesday, August 1, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, August 2, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
How AI Research is Working to Support and Empower Teachers
H. Chad Lane, Ph.D.
Wednesday, August 8, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT Click Here to Register
Thursday, August 9, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT Click Here to Register
Dr. Kaśka Porayska-Pomsta
Wednesday, September 19, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, September 20, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Kurt Vanlehn, Ph.D.
Wednesday, October 3, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, October 4, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Beyond Academics: Intelligent Mentoring Systems for Career Success
Wednesday, October 17, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, October 18, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
One of the ultimate goals of education is to effectively prepare students for long-term success. Most existing intelligent systems in education focus on adaptive tutoring for specific academic subjects and deliver personalized learning on a relatively short-term scale. Delivering sustained personalization of learning/mentorship for long-term success and aligning education to a rapidly-changing workforce remain lesser explored issues in artificial intelligence. I will discuss some of the unique challenges presented by these goals. These challenges include (1) the ability to track and integrate data from many disparate sources, at multiple grain sizes, and over long periods of time, (2) the need to adapt personalized learning models to consider longitudinal, cross-discipline, whole-person context rather than based strictly on within-tutor or within-session data, (3) the need to adapt models of engagement and motivation to consider longer-term trajectories and broader categories of behavior (for example, school attendance and discipline trajectories in addition to momentary estimates of affect and engagement), and (4) the real-time alignment of educational goals to the skills and knowledge needed in a rapidly-changing workforce. I will discuss promising approaches that can help us solve each of these challenges and move us closer to building effective intelligent mentoring systems.
Prof. Gautam Biswas
Wednesday, October 31, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, November 1, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Dr. W. Lewis Johnson
Wednesday, November 14, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, November 15, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Beverly Park Woolf, Ph.D., Ed.D.
Wednesday, November 28, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, November 29, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
James Lester, Ph.D.
Wednesday, December 12, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
Thursday, December 13, 1:00 PM-2:00 PM EDT / 10:00 AM-11:00 AM PDT
|W. Lewis Johnson, Ph.D.
President and CEO, Alelo Inc.
Dr. Johnson is an internationally recognized expert in AI education. For his work on the first Alelo immersive game, Tactical Iraqi, he won DARPA’s Significant Technical Achievement Award. He has been a past President of the International AI in Education Society and was co-winner of the 2017 Autonomous Agents Influential Paper Award for his work in the field of pedagogical agents. He has been invited to speak at many international conferences such as the International Conference on Intelligent Tutoring Systems, and presented a Distinguished Lecture at the National Science Foundation.
Chief Revenue Officer, Alelo Inc.
Karen Chiang has been involved in language learning and testing in academic and workplace applications for over 30 years. Prior to working with Alelo she was VP of sales at Pearson and was responsible for talent solutions and commercialization of the Versant language assessment products which utilize automated scoring. Karen has experience in international and business development in emerging markets such as India.
|H. Chad Lane, Ph.D.
Associate Professor of Educational Psychology and Informatics, University of Illinois, Urbana-Champaign
Prof. Lane’s research focuses on the design, use, and impacts of intelligent technologies for learning, engagement, and interest. This work involves blending techniques from the entertainment industry (that foster engagement) with those from artificial intelligence and intelligent tutoring systems (that promote learning). He has over 70 publications, delivered invited talks around the U.S and Europe, and has hands-on experiences in informal and formal learning contexts. His current research focuses on designing advanced learning technologies for informal learning.
|Rose Luckin, Ph.D.
Professor of Learner Centred Design, Institute of Education, University College London
Rose Luckin is Professor of Learner Centred Design at UCL Knowledge Lab in London. Her research involves the design and evaluation of educational technology using theories from the learning sciences and techniques from Artificial Intelligence (AI). She has a particular interest in using AI to open up the ‘black box’ of learning to show teachers and students the detail of their progress intellectually, emotionally and socially.
|James Lester, Ph.D.
Director of the Center for Educational Informatics and Distinguished Professor, North Carolina State University
His research centers on adaptive learning technologies that utilize AI to create learning experiences that are designed to be both highly effective and highly engaging. Over the past decade, his work has focused on intelligent game-based learning environments, computational models of narrative, affective computing, and natural language tutorial dialogue. The adaptive learning environments he and his colleagues develop have been used by thousands of students in K-12 classrooms throughout the US. He is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI).
|Dr. Kaśka Porayska-Pomsta
Associate Professor of Adaptive Technologies for Learning and an RCUK Academic Fellow at the UCL Knowledge Lab
Kaska holds a Joint Honours Masters in Linguistics and Artificial Intelligence and a Ph.D. in Artificial Intelligence, both from the University of Edinburgh, UK. Her research is interdisciplinary in nature and focuses on developing adaptive interactive environments for learning and communication that are underpinned with real-time user and context modeling capabilities, especially in relation to users’ affective and motivational states. She is the Head of Research for the Department of Culture, Communication and Media at the UCL Institute of Education. She sits on the management committee for the Bloomsbury Centre for Educational Neuroscience, steering committee for the UCL Institute of Digital Health, and the executive board for the International Society for Artificial Intelligence in Education.
|Kurt VanLehn, Ph.D.
Diane and Gary Tooker Chair for Effective Education in Science, Technology, Engineering and Math in the Ira A. Fulton Schools of Engineering at Arizona State University
He received a Ph.D. from MIT in 1983 in Computer Science, was a post-doc at BBN and Xerox PARC, joined the faculty of Carnegie-Mellon University in 1985, moved to the University of Pittsburgh in 1990 and joined ASU in 2008. He founded and co-directed two large NSF research centers (Circle; the Pittsburgh Science of Learning Center). He has published over 175 peer-reviewed publications, is a fellow in the Cognitive Science Society, and is on the editorial boards of Cognition and Instruction and the International Journal of Artificial Intelligence in Education. Dr. VanLehn’s research focuses on intelligent tutoring systems, classroom orchestration systems, and other intelligent interactive instructional technology.
Chief Data Scientist at MARi
Ran Liu is a career- and whole-person-oriented intelligent mentoring and skill tracking platform. Prior to working at MARi, Ran completed her Ph.D. at Carnegie Mellon University, supported by a National Science Foundation fellowship. In her dissertation work, she developed video games to improve non-native language learning and measured their impact on transfer to real-world non-native language tasks. Ran also completed her post-doctoral training at Carnegie Mellon University working on educational data science research. Her post-doctoral research focused on advancing intelligent learner models as well as testing the effect of such modeling advancements on classroom learning outcomes.
|Beverly Park Woolf, Ph.D., Ed.D.
Research Professor in the College of Information and Computer Sciences, UMass-Amherst
Dr. Woolf develops intelligent tutors that model a student’s affective and cognitive characteristics and combine an analysis of learning with artificial intelligence, network technology, and multimedia. She published the book Building Intelligent Interactive Tutors along with over 250 articles. She is the lead author on the NSF report Roadmap to Education Technology in which forty experts and visionaries identified the next big computing ideas for education technology and developed a vision of how technology can incorporate deeper knowledge about human cognition.
Professor of Computer Science and Computer Engineering, Vanderbilt University
Gautam Biswas is a Cornelius Vanderbilt Endowed Professor of Engineering, a Professor of Computer Science and Computer Engineering in the EECS Department, and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI. Currently, Prof. Biswas is the lead on the VISOR (Vanderbilt Initiative for Smart cities Operations and Research) TIPS center at Vanderbilt University.