Matching Items (5)
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- All Subjects: Science history
- Creators: Brian, Jennifer
- Creators: Wylie, Ruth
Description
This research aimed to analyze and ultimately understand the relationship between the four dimensions of the Technology Readiness Index (TRI) 2.0 (optimism, innovation, discomfort, and insecurity) when compared to self-efficacy and learning. The experiment design was a one-group pretest-posttest where a participant’s TRI 2.0 acted as a subject variable. This information was then correlated to changes in self-efficacy and content mastery (learning) from pre-/post-test scores pertaining to Google Sheets functions for introductory statistics. In-between the pre- and post-tests, a learning activity was presented which asked participants to analyze quantitative statistics using Google Sheets. Findings of this research demonstrated a statistically insignificant relationship between technology readiness and self-efficacy or learning. Alternatively, significance was observed in changes from pre- to post-test scores for both learning and self-efficacy where a relationship was found between the degree to which participants’ content mastery and self-efficacy change before and after a computer-supported learning activity is assigned. These findings directly contribute to current understanding of how and why individuals can effectively learn and perform in computer-supported learning environments.
ContributorsCervantes Villa, Sabrina Marie (Author) / Craig, Scotty D. (Thesis advisor) / Donner, Jodie (Committee member) / Roscoe, Rod (Committee member) / Wylie, Ruth (Committee member) / Arizona State University (Publisher)
Created2022
Description
Writing speculative fiction is a valuable method for exploring the potential societal transformations elicited by advances in science and technology. The aim of this project is to use speculative fiction to explore the potential consequences of precision medicine for individuals’ daily lives. Precision medicine is a vision of the future in which medicine is about predicting, and ultimately preventing disease before symptoms arise. The idea is that identification of all the factors that influence health and contribute to disease development will translate to better and less expensive healthcare and empower individuals to take responsibility for maintaining their own health and wellness. That future, as envisioned by the leaders of the Human Genome Project, the Institute for Systems Biology, and the Obama administration’s Precision Medicine Initiative, is assumed to be a shared future, one that everyone desires and that is self-evidently “better” than the present. The aim of writing speculative fiction about a “precision medicine” future is to challenge that assumption, to make clear the values underpinning that vision of precision medicine, and to leave open the question of what other possible futures could be imagined instead.
ContributorsVenkatraman, Richa (Author) / Brian, Jennifer (Thesis advisor) / Maienschein, Jane (Thesis advisor) / Hurlbut, James (Committee member) / Arizona State University (Publisher)
Created2022
Description
This is a project about medicine and the history of a condition called premenstrual syndrome (PMS), its “discovery” and conceptual development at both scientific and socio-cultural levels. Since it was first mentioned in medical literature, PMS has been explored empirically as a medical condition and conceptually as non-somatic cultural phenomenon. Many attempts have been made to produce scientific, empirical evidence to bolster the theory of PMS as a biological disease. Some non-medical perspectives argue that invoking biology as the cause of PMS medicalizes a natural function of the female reproductive system and shallowly interrogates what is actually a complex bio-psycho-social phenomenon. This thesis questions both sides of this debate in order to reveal how criteria for PMS were categorized despite disagreement surrounding its etiology.
This thesis illustrates how the concept of PMS developed and was informed by the discovery of hormones and the resulting field of endocrinology that provided a framework for conceptualizing PMS. It displays how the development of the medical diagnostic category of PMS developed in tandem with the emergence of the field of endocrinology and was legitimized and effectively medicalized through this connection. The diagnosis of PMS became established though the diagnostic techniques like questionnaires in spite of persistent disagreement over its definition. The thesis shows how these medical concepts and practices legitimated the category of PMS, and how it has become ubiquitous in contemporary culture.
This thesis illustrates how the concept of PMS developed and was informed by the discovery of hormones and the resulting field of endocrinology that provided a framework for conceptualizing PMS. It displays how the development of the medical diagnostic category of PMS developed in tandem with the emergence of the field of endocrinology and was legitimized and effectively medicalized through this connection. The diagnosis of PMS became established though the diagnostic techniques like questionnaires in spite of persistent disagreement over its definition. The thesis shows how these medical concepts and practices legitimated the category of PMS, and how it has become ubiquitous in contemporary culture.
ContributorsZietal, Bianca (Author) / Hurlbut, James (Thesis advisor) / Robert, Jason (Committee member) / Brian, Jennifer (Committee member) / Arizona State University (Publisher)
Created2016
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
Description
Today in the U.S. the narrative of the “bad drug” has become quite a familiar account. There is an ever-growing collection of pharmaceutical products whose safety and efficacy has been debunked through the scandalous exposure of violations of integrity on the part of researchers, lapses in procedure and judgment on the part of the FDA, and reckless profiteering on the part of big pharma. However, a closer look reveals that the oversights and loopholes depicted in the bad drug narrative are not incidental failures of an otherwise intact, effective system. Rather, bad drugs, like good drugs, are a product of normal operations of the system; the same processes, actors, and influences manifest in both. The aim of this project is to shed light on these processes, actors, and influences at work in drug normalization by interrogating the peculiar case of the drug Lupron. Lupron exhibits all of the controversial features of the “bad drug” narrative but has remained an endorsed and embraced staple of the infertility industry. This contradiction situates Lupron to expose a number of the contingencies on which drug normalization rests more generally. In order to put forth an explanatory model for drug normalization, three such contingencies are described in detail for the case at hand: the nature of drug regulation, the structures and value that underpin the medical categorization of diseases, and the inextricability of post-medicine from the forces of industry. These contingencies provide some explanatory power for understanding not only the retention of Lupron but the ways in which all drugs are produced, validated, and perpetuated in a society.
ContributorsStevenson, Christine, M.S (Author) / Brian, Jennifer (Thesis advisor) / Hurlbut, Benjamin (Thesis advisor) / Maienschein, Jane (Committee member) / Arizona State University (Publisher)
Created2015