Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. / Cataloged from PDF version of thesis. Vita. / Includes bibliographical references (pages 179-201). / Today's educational systems are complex, political, sociotechnical ecosystems that struggle to meet the needs of most learners and societal demands-and most critically, struggle to change. Yet, learners globally need access to high quality learning environments and coherent learning pathways that support them to thrive in our complex world. Fundamental to every learning technology, environment, and system, is a learning data model and architecture that helps to organize the learner's experience. To date, in traditional educational systems, this has largely been dominated by public policy curriculum standards, which have tremendous limitations and shortcomings on classroom practice and their ability to support complex learning technologies. At the same time, over the past several decades significant advances have been made in the learning sciences, learning analytics, and learning technologies that have greatly expanded our ability to model learning and provide immersive and adaptive learning environments. Yet each of these communities rarely coordinates and aligns these data models. The disjointedness of these structures leaves their architecture in a messy, challenging state, unable to successfully carry us into an advanced future of learning technologies and effective learning ecosystems. This dissertation explores the use of Systems Engineering as a means to reengineering this critical infrastructure of the system, through the LearningGraph-a research initiative that used this methodology to create a unified data structure for modeling learning constructs in a coherent learning data architecture. The aim of the project is to ultimately inform a new infrastructure to support learning development across learning technologies and environments. In doing so, we create the foundation for closing significant gaps in the current system: between learning sciences research and practice; curriculum and assessment design; the design of learning technologies and all the aforementioned components; and between and across education systems globally. Moreover, it creates the potential for the foundation of a very different future for learning ecosystems. / by Jennifer Sterling Groff. / Ph. D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/120683 |
| Date | January 2018 |
| Creators | Groff, Jen |
| Contributors | Eric Klopfer., Program in Media Arts and Sciences (Massachusetts Institute of Technology), Program in Media Arts and Sciences (Massachusetts Institute of Technology) |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 273 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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