{"653068":{"#nid":"653068","#data":{"type":"event","title":"PhD Proposal by Sungeun An","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: A Computational Model of Self-Directed Learning for Systems Thinking\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESungeun An\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPh.D. Candidate in Human-Centered Computing\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Interactive Computing\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate\u003C\/strong\u003E: Wednesday, December 1, 2021\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime\u003C\/strong\u003E: 2:00 PM - 4:00 PM EST\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation(Remote via BlueJeans)\u003C\/strong\u003E: \u003Ca href=\u0022https:\/\/gatech.bluejeans.com\/3291125456\u0022\u003Ehttps:\/\/gatech.bluejeans.com\/3291125456\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Ashok Goel (Advisor), School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Jennifer Hammock, National Museum of Natural History, Smithsonian Institution\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Robert J. Moore, IBM Research-Almaden\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Spencer Rugaber, School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Sashank Varma, School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Emily Weigel, School of Biological Sciences, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESystems thinking is a useful skill for addressing ill-defined problems in complex domains. Yet, robust computational models of how adult learners engage in systems thinking or how to help them learn about systems thinking in a self-directed manner are not available. In this interdisciplinary work, I use theories and techniques from cognitive science, learning science, artificial intelligence, and data mining to develop a computational model of self-directed adult learning about systems thinking in the domain of ecology.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETo achieve this goal, I present the Virtual Experimentation Research Assistant (VERA; vera.cc.gatech.edu)-- an interactive learning environment that enables learners to access large-scale biological knowledge from Encyclopedia of Life (EOL), construct conceptual mechanistic models of ecological systems, run agent-based simulations of these models, and revise the models and simulations as needed. I have used VERA to complete two preliminary field studies. The first study explored the effects of modeling in acquiring domain knowledge. I found that engaging in ecological modeling using VERA helped college-level students acquire biological knowledge, and access to large-scale domain knowledge helped them construct more complex models and develop a larger number of hypotheses for a given problem. The second study investigated novice learners\u0026rsquo; behaviors in estimating the parameters for agent-based simulations. I discovered that students showed multiple cognitive strategies for parameter estimation such as systematic search, problem reduction\/decomposition, global\/local search.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nVERA is now accessible through Smithsonian Institution\u0026rsquo;s EOL website (eol.org) and it is used by thousands of self-directed learners around the world. To complete my dissertation, I plan to conduct two additional studies. The first will use data mining techniques to understand patterns in how self-directed adult learners use VERA to construct models to address ill-defined problems. The second study will explore the effects of using VERA in self-directed learning by comparing the students\u0026rsquo; modeling behaviors and learning outcomes in guided and self-directed learning. Together these four studies will lead to a computational model of how adult learners learn about systems thinking in a self-directed manner and how to design interactive learning environments to support self-directed systems thinking in open and ill-defined problems.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":": A Computational Model of Self-Directed Learning for Systems Thinking"}],"uid":"27707","created_gmt":"2021-11-22 15:14:58","changed_gmt":"2021-11-22 15:14:58","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-12-01T14:00:00-05:00","event_time_end":"2021-12-01T16:00:00-05:00","event_time_end_last":"2021-12-01T16:00:00-05:00","gmt_time_start":"2021-12-01 19:00:00","gmt_time_end":"2021-12-01 21:00:00","gmt_time_end_last":"2021-12-01 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}