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The use of blogging tools in the second language classroom has been investigated from a variety of theoretical and methodological perspectives (Alm, 2009; Armstrong & Retterer, 2008; Dippold, 2009; Ducate & Lomicka, 2008; Elola & Oskoz, 2008; Jauregi & Banados, 2008; Lee, 2009; Petersen, Divitini, & Chabert, 2008; Pinkman, 2005;

The use of blogging tools in the second language classroom has been investigated from a variety of theoretical and methodological perspectives (Alm, 2009; Armstrong & Retterer, 2008; Dippold, 2009; Ducate & Lomicka, 2008; Elola & Oskoz, 2008; Jauregi & Banados, 2008; Lee, 2009; Petersen, Divitini, & Chabert, 2008; Pinkman, 2005; Raith, 2009; Soares, 2008; Sun, 2009, 2012; Vurdien, 2011; Yang, 2009) and a growing number of studies examine the use of microblogging tools for language learning (Antenos-Conforti, 2009; Borau, Ullrich, Feng, & Shen, 2009; Lomicka & Lord, 2011; Perifanou, 2009). Grounded in Cultural Historical Activity Theory (Engestrom, 1987), the present study explores the outcomes of a semester-long project based on the Bridging Activities framework (Thorne & Reinhardt, 2008) and implemented in an intermediate hybrid Spanish-language course at a large public university in Arizona, in which students used microblogging and blogging tools to collect digital texts, analyze perspectives of the target culture, and participate as part of an online community of language learners with a broader audience of native speakers. The research questions are: (1) What technology is used by the students, with what frequency and for what purposes in both English and Spanish prior to beginning the project?, (2) What are students' values and attitudes toward using Twitter and Blogger as tools for learning Spanish and how do they change over time through their use in the project during the semester course?, and (3) What tensions emerge in the activity systems of the intermediate Spanish-language students throughout the process of using Twitter and Blogger for the project? What are the underlying reasons for the tensions? How are they resolved? The data was collected using pre-, post-, and periodic surveys, which included Likert and open-ended questions, as well as the participants' microblog and blog posts. The quantitative data was analyzed using descriptive statistics and the qualitative data was analyzed to identify emerging themes following the Constant Comparative Method (Glaser & Strauss, 1967). Finally, three participant outliers were selected as case studies for activity theoretical analysis in order to identify tensions and, through their resolution, evidence of expansive learning.
ContributorsAlvarado, Margaret (Author) / Lafford, Barbara (Thesis advisor) / González, Verónica (Committee member) / Cerron-Palomino, Alvaro (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Micro-blogging platforms like Twitter have become some of the most popular sites for people to share and express their views and opinions about public events like debates, sports events or other news articles. These social updates by people complement the written news articles or transcripts of events in giving the

Micro-blogging platforms like Twitter have become some of the most popular sites for people to share and express their views and opinions about public events like debates, sports events or other news articles. These social updates by people complement the written news articles or transcripts of events in giving the popular public opinion about these events. So it would be useful to annotate the transcript with tweets. The technical challenge is to align the tweets with the correct segment of the transcript. ET-LDA by Hu et al [9] addresses this issue by modeling the whole process with an LDA-based graphical model. The system segments the transcript into coherent and meaningful parts and also determines if a tweet is a general tweet about the event or it refers to a particular segment of the transcript. One characteristic of the Hu et al’s model is that it expects all the data to be available upfront and uses batch inference procedure. But in many cases we find that data is not available beforehand, and it is often streaming. In such cases it is infeasible to repeatedly run the batch inference algorithm. My thesis presents an online inference algorithm for the ET-LDA model, with a continuous stream of tweet data and compare their runtime and performance to existing algorithms.
ContributorsAcharya, Anirudh (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Tong, Hanghang (Committee member) / Arizona State University (Publisher)
Created2015