ASSESSING THE LEVEL OF TECHNOLOGY INTEGRATION OF TITLE I TEACHERS IN A LARGE URBAN SCHOOL DISTRICT

By law, Title I schools employ teachers who are both competent in their subject knowledge and State certified. In addition, Title I teachers receive ongoing professional development in technology integration and are equipped with the latest innovative resources to integrate technology in the classroom. The aim is higher academic achievement and the effective use of technology in the classroom. The investment to implement technology in this large urban school district to improve student achievement has continued to increase. In order to infuse current and emerging technology throughout the curriculum, this school district needs to know where teachers have, and have not, integrated technology. Yet the level of how technology is integrated in Title I schools is unknown. This study used the Digital-Age Survey Levels of Teaching Innovation (LoTi) to assess 508 Title I teachers’ technology integration levels using three major initiatives purchased by Title I— the iPads program, the Chromebook initiative, and the interactive whiteboards program. The study used a quantitative approach. Descriptive statistics, regression analysis, and statistical correlations were used to examine the relationship between the level of technology integration and the following dependent variables: personal computer use (PCU), current instructional practices (CIP), and levels of teaching innovation (LoTi). With this information, budgetary decisions and professional development can be tailored to the meet the technology implementation needs of this district. The result of this study determined a significant relationship between the level of teaching innovation, personal computer use, and current instructional practices with teachers who teach with iPad, Chromebook, and/or interactive whiteboard. There was an increase in LoTi, PCU, and CIP scores with increasing years of experience of Title I teachers. There was also a significant relationship between teachers with 20 years or more teaching experience and their LoTi score.

VOX POPULI: THREE ESSAYS ON THE USE OF SOCIAL MEDIA FOR VALUE CREATION IN SERVICES

Prior research shows that electronic word of mouth (eWOM) wields considerable influence over consumer behavior. However, as the volume and variety of eWOM grows, firms are faced with challenges in analyzing and responding to this information. In this dissertation, I argue that to meet the new challenges and opportunities posed by the expansion of eWOM and to more accurately measure its impacts on firms and consumers, we need to revisit our methodologies for extracting insights from eWOM. This dissertation consists of three essays that further our understanding of the value of social media analytics, especially with respect to eWOM. In the first essay, I use machine learning techniques to extract semantic structure from online reviews. These semantic dimensions describe the experiences of consumers in the service industry more accurately than traditional numerical variables. To demonstrate the value of these dimensions, I show that they can be used to substantially improve the accuracy of econometric models of firm survival. In the second essay, I explore the effects on eWOM of online deals, such as those offered by Groupon, the value of which to both consumers and merchants is controversial. Through a combination of Bayesian econometric models and controlled lab experiments, I examine the conditions under which online deals affect online reviews and provide strategies to mitigate the potential negative eWOM effects resulting from online deals. In the third essay, I focus on how eWOM can be incorporated into efforts to reduce foodborne illness, a major public health concern. I demonstrate how machine learning techniques can be used to monitor hygiene in restaurants through crowd-sourced online reviews. I am able to identify instances of moral hazard within the hygiene inspection scheme used in New York City by leveraging a dictionary specifically crafted for this purpose. To the extent that online reviews provide some visibility into the hygiene practices of restaurants, I show how losses from information asymmetry may be partially mitigated in this context. Taken together, this dissertation contributes by revisiting and refining the use of eWOM in the service sector through a combination of machine learning and econometric methodologies.