Title: Accelerating Self-regulated Learning in Game-based Virtual Learning Environments with Multimodal Data
Speaker: Professor Roger Azevedo
Abstract: Game-based virtual learning environments can be used to detect, foster, and accelerate self-regulated learning (SRL) by using multimodal data. SRL is an essential predictor of students’ learning, problem-solving, and reasoning across tasks, domains, and contexts. More specifically, cognitive, affective, metacognitive, motivational, and social processes play a crucial role in students’ ability to accurately and dynamically monitor and regulate while learning with game-based virtual learning environments. Despite the potential of these environments to detect, foster, and accelerate SRL, there remain many conceptual, theoretical, methodological, analytical, and pedagogical challenges and opportunities. For example, how can multimodal data be used to accelerate SRL, how is metacognition enacted and detected in game-based virtual learning environments, how do we conceptually and methodologically separate motivation from emotions during learning with such environments, what role do intelligent virtual humans play in sustaining social processes during learning with these environments, do we assess the quality of cognitive strategies that are embodied during learning with game-based learning environments? This talk focuses on these questions as well as: (1) describing game-based virtual learning environments and their affordances for detecting, fostering, and accelerating SRL; (2) presenting the conceptual, theoretical, methodological, and analytical challenges currently impacting the field; and (3) discussing implications for using multimodal data for researchers, learners, and educators to detect, foster, and accelerate SRL.
Biography: Dr. Azevedo is a Professor in the School of Modeling Simulation and Training at the University of Central Florida. He is also an affiliated faculty in the Departments of Computer Science and Internal Medicine at the University of Central Florida and the lead scientist for the Learning Sciences Faculty Cluster Initiative. He received his Ph.D. in Educational Psychology from McGill University and completed his postdoctoral training in Cognitive Psychology at Carnegie Mellon University. His main research area includes examining the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies (e.g., intelligent tutoring systems, hypermedia, multimedia, simulations, serious games, immersive virtual learning environments). More specifically, his overarching research goal is to understand the complex interactions between humans and intelligent learning systems by using interdisciplinary methods to measure cognitive, metacognitive, emotional, motivational, and social processes and their impact on learning, performance, and transfer. To accomplish this goal, he conducts laboratory, classroom, and in-situ (e.g., medical simulator) studies and collects multi-channel data to develop models of human-computer interaction; examines the nature of temporally unfolding self- and other-regulatory processes (e.g., human-human and human-artificial agents); and designs intelligent learning and training systems to detect, track, model, and foster learners, teachers, and trainers’ self-regulatory processes. He has published over 300 peer-reviewed papers, chapters, and refereed conference proceedings in the areas of educational, learning, cognitive, educational, and computational sciences. He was the former editor of the Metacognition and Learning journal and serves on the editorial board of several top-tiered learning and cognitive sciences journals (e.g., Applied Cognitive Psychology, International Journal of AI in Education, Educational Psychology Review, European Journal of Psychological Assessment). His research is funded by the National Science Foundation (NSF), Department of Education, Institute of Education Sciences (IES), National Institutes of Health (NIH), and the Social Sciences and the Humanities Research Council of Canada (SSHRC), Natural and Sciences and Engineering Council of Canada (NSERC), Canada Research Chairs (CRC), Canadian Foundation for Innovation (CFI), European Association for Research on Learning and Instruction (EARLI) and the Jacobs Foundation. He is a fellow of the American Psychological Association and the recipient of the prestigious Early Faculty Career Award from the National Science Foundation.
Title: On GraphoLearn – the digital evidence-based method for supporting the development of reading skills in all learners
Speaker: Professor Ulla Richardson
Abstract: The evidence-based GraphoLearn app is used for supporting the development of early reading skills, especially in struggling learners. I will provide a brief description on the theoretical and methodological backgrounds of the GraphoLearn method together with findings applying the method into the scientifically designed learning environment GraphoLearn (grapholearn.com) in different orthographies but also for different types of learners. The focus of my talk will be on the design and development of the game in order for it to become a learning/training tool for all learners. In addition, I will present some of the challenges and possibilities GraphoLearn game log data provide for assessing and learning about individual learners’ performance (accuracy, time, and specific learning content) and changes of performance related to gaming sessions.
Biography: Richardson is a professor of technology-enhanced language learning in the Center for Applied Language Studies and adjunct Professor of Experimental Psycholinguistics and Research on Speech Sciences, Department of Languages at the University of Jyväskylä. She is head of the Secretariat of GraphoWORLD Network of Excellence (http://info.grapholearn.com/partners/), and UNESCO Chair on Inclusive Literacy Learning for All. Her research falls into reading and writing skills and development in different languages and orthographies, dyslexia research, interventions and skill assessments, phonology and speech processing as well as evidence-based technology in language learning. She leads the multidisciplinary GraphoLearn (GL) team which has developed the evidence based GraphoLearn learning environment (info.GraphoLearn.com) for more than 25 languages to support learners in developing their reading skills. Currently, she leads an international research project “AllRead” (funded by Fondation Botnar) and she has led several international and national research projects centered around GraphoGame/GraphoLearn including “Technology-enhanced environment for supporting reading development in all learners” (Academy of Finland), “Early identification and prevention of reading problems in alphabetic and semanto-phonetic writing (EU FP 7 Marie Curie IRSES funding), “Fluent-project” (Lifelong Learning- Comenius funding), and “GraphoGame-project” (EC FP6 Marie Curie Excellence -funding).