There is no doubt that Web 2.0 technologies have impacted almost every facet of our lives. Whether it be in the classroom, or the way to communicate with family and friends, Web 2.0 technology has allowed us to become global citizens. We are now able to tap into a larger, more diverse repository of information, and thus what we "know" is secondary to what we "can find out." One product of the integration of Web 2.0 technologies in our way of life, is the way in which we have now become prosumers in a digital world. Prosumption, a term that defines the process of both producing and consuming data, is applied in this dissertation to discuss the ways in which we remember major events in our national narrative, and how we become civically engaged. This dissertation first outlines the ways in which Web 2.0 technology has remediated collective memory frameworks. By rhetorically analyzing the vernacular literacies that emerge at two sites of memory, one pre-Web 2.0 and one post-Web 2.0 technology, I argue that collective memory frameworks have become sites of prosumption that provide fertile ground for more meaningful civic engagement models. This work also uses an ecology metaphor to help build the concept that collective memory frameworks are a part of our "ecosystem", whether physical or digital, they permeate our lives, particularly the lives of school-aged individuals. The second part of this dissertation attempts to connect the ideas of prosumption and remediation at sites of collective memory to suggest that the most effective way to facilitate civic engagement is for educators to transform their classrooms to become spaces that Thomas and Seely Brown call, a "New Culture of Learning." Through this model, students use Web 2.0 technologies to execute ideas of prosumption which can then be used to solve large-scale problems.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1362 |
Date | 01 January 2020 |
Creators | Hines, Jasara |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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