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Description
Over the last fifty years, education funding has been litigated and debated in the United States. In an effort to uncover more into the effects of state dollars on education, I used the guiding research question: did differences in state-level education funding trends in the 1990s affect crime rates? With the help of literature on changing education-funding trends, I selected the timeframe of 1990-1995 because some states and jurisdictions increased their funding while others decreased it. For my research, I outlined the independent variable of per pupil expenditures in order to focus directly on the dollars that impact the individual student, and the dependent variables of burglary, robbery, and motor vehicle theft crime rates because juveniles typically commit these crimes. Unemployment rates and household income served as confounding variables, as these economic factors have been proven to affect crime rates. Using the difference-in-difference method, I was able to test the effect of the implementation of a treatment, increased education funding, on my control and treatment group over the 1990-1995-time period. After running a regression on each of my selected juvenile-specific crime rates, I found my results to be inconclusive; however, by factoring in more confounding variables, I believe this quasi-experimental approach can be repeated to find more solid results.
ContributorsWilson, Kelsey Marie (Author) / Dorn, Sherman (Thesis director) / Carter, Heather (Committee member) / Tatto, Maria (Committee member) / School of Public Affairs (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The emergence of machine intelligence, which is superior to the best human talent in some problem-solving tasks, has rendered conventional educational goals obsolete, especially in terms of enhancing human capacity in specific skills and knowledge domains. Hence, artificial intelligence (AI) has become a buzzword, espousing both crisis rhetoric and ambition to enact policy reforms in the educational policy arena. However, these policy measures are mostly based on an assumption of binary human-machine relations, focusing on exploitation, resistance, negation, or competition between humans and AI due to the limited knowledge and imagination about human-machine relationality. Setting new relations with AI and negotiating human agency with the advanced intelligent machines is a non-trivial issue; it is urgent and necessary for human survival and co-existence in the machine era. This is a new educational mandate. In this context, this research examined how the notion of human and machine intelligence has been defined in relation to one another in the intellectual history of educational psychology and AI studies, representing human and machine intelligence studies respectively. This study explored a common paradigmatic space, so-called ‘cyborg space,’ connecting the two disciplines through cross-referencing in the citation network and cross-modeling in the metaphorical semantic space. The citation network analysis confirmed the existence of cross-referencing between human and machine intelligence studies, and interdisciplinary journals conceiving human-machine interchangeability. The metaphor analysis found that the notion of human and machine intelligence has been seamlessly interwoven to be part of a theoretical continuum in the most commonly cited references. This research concluded that the educational research and policy paradigm needs to be reframed based on the fact that the underlying knowledge of human and machine intelligence is not strictly differentiated, and human intelligence is relatively provincialized within the human-machine integrated system.
ContributorsGong, Byoung-gyu (Author) / McGurty, Iveta (Thesis advisor) / Wylie, Ruth (Committee member) / Dorn, Sherman (Committee member) / Zheng, Yi (Committee member) / Arizona State University (Publisher)
Created2021