Mike Tissenbaum: Next-Generation Learning Spaces: Investigating new forms of research at the intersection of learning sciences, HCI, and design @ Pless Hall, 7th Floor, ALT Conference Room 785

02/23/2018 11:00 am – 02/23/2018 12:00 pm Next-Generation Learning Spaces: Investigating new forms of research at the intersection of learning sciences, HCI, and design
Mike Tissenbaum, MIT
Friday, February 23, 11:00AM-12:00noon
Pless Hall, 7th Floor, ALT Conference Room 785
Technology is radically impacting the ways we work, live, and relate to the world around us. As a result, there is a growing need for students to develop STEM and computational literacies that will help them to actively design, shape, and engage in our digitally mediated future. Helping students to develop these literacies requires us to rethink education beyond the acquisition of domain knowledge to transformational experiences that encompass social, collaborative, and knowledge building skills that empower learners to tackle nascent problems. In turn, to effectively support these new forms of learning, we need to design learning spaces that foster the kinds of complex collaboration, idea sharing, and inquiry that characterize best practices in education.
Achieving this goal requires us to redesign learning environments as intertwined technological, informational, and pedagogical spaces, in which learners’ experiences, goals, and pedagogical needs can be opportunistically connected to those of their peers to facilitate new forms of collaborative learning – learning that is spontaneous, anchored in students’ own ideas, and facilitated by the teachers and technologies around them. Effective construction and evaluation of these environments requires us to approach them from an increasingly multi-disciplinary set of perspectives. The combination of learning sciences, human-computer interaction, and user- and learner-centered design offers a particularly rich set of complementary methods for designing and evaluating the learning and collaboration processes that take place in hybrid physical-digital learning spaces. Further, these instrumented learning spaces open the potential for collecting a rich array of telemetry data to complement traditional qualitative and quantitative approaches for understanding learning processes. These data offer exciting new opportunities not only for researchers to understand how students learn, but also to provide teachers and students alike with real-time insight into the state of their class at the individual, small group, and whole class levels.
Mike’s talk will encompass three main themes: 1) How technology-enhanced learning environments support new ways for participants to collaborate with peers, investigate rich and engaging phenomena, and develop critical STEM and computational literacies; 2) How employing multi-dimensional approaches from the learning sciences, HCI, and design provide important insights into how learning and collaboration are distributed across learners, technologies, and the physical space; and 3) What roles data-mining and analytics-driven software agents play in adding a layer of intelligence to these spaces by supporting real-time orchestration of activities, with timely and context-sensitive information for new insights into collaboration and learning. Using examples from his research in formal and informal learning environments, Mike will illustrate how these themes connect to his development of the theory of divergent collaboration, which is reshaping how we understand collaboration and learning processes and outcomes in open-ended and exploratory environments.
Mike Tissenbaum is a learning research scientist with the App Inventor team at MIT’s Center for Mobile Learning. Mike’s research focuses on collaborative learning and knowledge communities and aims to understand how children develop STEM and computational literacies when engaged in technology-enhanced learning.
More broadly, Mike’s research has pioneered a combination of tangible, embodied, and immersive technologies that support students’ engagement in science, engineering, and computational practices. Mike’s work has shown how technologies and data representations situated within the physical space can provide learners with unique opportunities to set their own learning goals and collaborate with peers. These findings have had important implications for understanding open-ended and exploratory collaboration, especially divergent collaboration. Using a blend of learning analytics approaches and interaction analysis, Mike is charting exciting new pathways for supporting student collaboration and teacher facilitation in complex, immersive, and exploratory learning.
Mike also investigates ways of supporting teachers’ real-time orchestration of learning. He has developed interventions that draw teachers more deeply into the learning process as active facilitators. Using data mining and intelligent software agents, Mike has designed scaffolds that help teachers understand the state of the class at the individual, small group, and whole class levels; to orchestrate the flow of activities; and to know where and when they are needed at critical moments in students’ learning.
Mike also currently serves on the International Society of the Learning Sciences’ (ISLS) and the Network of Academic Programs in the Learning Sciences’ (NAPLeS) technology committees; is the AERA co-chair of the Advanced Technologies for Learning Special Interest Group (SIG-ATL); and is a founding organizer of the New England Learning Scientists. Mike earned a PhD in Curriculum and Instruction (OISE) and a Master of Information Studies (iSchool) from the University of Toronto. Prior to joining MIT, Mike was a post-doctoral scholar at the Wisconsin Institute for Discovery and the Complex Play Lab at the University of Wisconsin–Madison.