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My Dissertation Proposal Defense

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Defending chapter 1, 2 & 3 of my final dissertation; my contract to analyze data & finish!
2-25-14

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My Dissertation Proposal Defense

  1. 1. ATPI Dissertation Proposal of Laura A. Pasquini Department of Learning Technologies - College of Information, University of North Texas Major Professor: Dr. Jeff M. Allen Committee: Dr. Kim Nimon & Dr. Mark Davis 1
  2. 2. Social Media Guidance in Higher Education: Using Latent Semantic Analysis to Review Social Media Guideline and Policy Documents Laura A. Pasquini, B.A., M.S. Ed. Department of Learning Technologies, College of Information - University of North Texas 2
  3. 3. Research Study Examination of social media guideline & policy documents, which are accessible online from postsecondary education (PSE) institutions using the text mining method, Latent Semantic Analysis (LSA). 3
  4. 4. Background • Social media use has increased in higher education (Brenner & Smith, 2013); however guideline and policy documents have rarely been examined (Joosten, 2012; Joosten et al., 2013; Reed, 2013) • Institutions direct & moderate how students, staff, faculty & administrators use social media on campus (Blankenship, 2011; Moran, Seaman, & Tinti-Kane, 2011) 4 pp. 3-5
  5. 5. Need for Study • Social learning and learning cultures experience (Vygotsky, 1962; Bandura, 1977; Brown, 2001) • Communities of practice (Wenger, 1999) • Personal learning networks (Warlick, 2009) • Social media creates an information network where information, ideas, learning & passion grows (Thomas & Brown, 2011) 5 pp. 5-8
  6. 6. How is Social Media Being “Guided” in Higher Ed? Mergel et al. (2012) • Create a social media policy before using social media or experimentation with social media within the organization to generate and apply guidance. Wandel (2009) and Joosten et al. (2013) • Security and privacy are two of the primary concerns Rodriguez (2011) • Deal with challenges related to privacy, ownership of intellectual property, legal use, identity management, and literacy development 6 pp. 8-11
  7. 7. Purpose The purpose of this study is to analyze social media guideline and policy documents that are accessible online from post-secondary education (PSE) institutions. 7 p. 11
  8. 8. Theoretical Framework Latent Semantic Analysis (LSA) is a Theory of Meaning: •“the meaning of a yet is largely conveyed by the words from which it is composed” (Landauer, McNamara, Dennis, & Kintsch, 2013) 8
  9. 9. Research Questions • R1. What latent semantic factors are relevant to structuring the body of textual data in current higher education social media guideline and policy documents? • R2. What naturally emerging inherent categories and themes, can be identified in higher education social media guidelines and policies? 9 p. 14
  10. 10. Limitations Latent Semantic Analysis (LSA is): •Text content only •Dimension reduction of the dataset •Orthogonal (Lee, Song & Kim, 2010) •Polysemy issues (Li & Joshi, 2012) 10 pp. 14-15
  11. 11. Delimitations No indicates bound of the study controlled by the researcher that might influence the validity of the study. The researcher will follow LSA methodological recommendations for this type of text mining procedure. (Evangelopoulos, Zhang, & Prybutok, 2012) 11 p. 15
  12. 12. Terms & Definitions Social Media (pp. 15-16) Post-Secondary Education Institutions (p. 17) Guideline and Policy Documents (pp. 17-18) 12
  13. 13. Literature Review Greenhow and Robelia (2009) •create rich experiences for learners to improve educational achievement and student engagement Joosten (2012), Chapman andRussell (2009), & Dohn (2009) •Instructors use for pedagogical practice and to supplement the face-to-face classroom learning Danciu and Grosseck (2011) •Digital literacy development for continuous discovery, digital curation, network development, and connected engagement Silius, Kailanto, and Tervakari (2011) •Allow for a hands-on, interactive approach for engagement… enhance teamwork and collaboration 13 pp.18-24
  14. 14. Why Social Media Guideline and Policy Document Analysis in PSE? • • • • • • • • Limited research Recruitment and admissions Student-led initiatives Scholars & researchers Peer-review publications Enhances student learning Privacy & control Institutional leadership & implementation 14 pp.18-24
  15. 15. Other concerns… 15 pp. 24-26
  16. 16. Methodology Data mining (Romero, Ventura, & Garcia, 2008). Text mining •(Hearst, 1997; Feldman & Dagan, 1995; Fayyad, Piatesky-Shapiro, & Smyth, 1996; Simoudis, 1996). 16 pp.26-28
  17. 17. Research Methods Latent Semantic Analysis (LSA) • a computational research method that simulates human like analysis with language (Landauer, 2011) • used for information retrieval query optimization (Deerwester, Dumais, Furnas, Landauer, & Harshman, 1990, Dumais 2004). 17 p. 30
  18. 18. Vector Space Model (VSM) (Salton, 1975; Evangelopoulos, Zhang, & Prybutok, 2010). 18 pp. 28-29
  19. 19. Research Design Step 1: Establish the Corpus Step 2: Pre-Process the Data Step 3: Extract Knowledge 19 p. 36
  20. 20. Research Design 20 p. 36
  21. 21. Sampling 21 pp. 43-44
  22. 22. Gathering Guideline & Policy Documents www.socialmediaguidance.wordpress.com 22
  23. 23. Data Collection www.socialmediaguidance.wordpress.com 23
  24. 24. Institutional Research Board 24
  25. 25. Instrumentation • Appendix B 25 pp. 82-89
  26. 26. Data Cleaning & Organization • Appendix A 26 pp. 68-81
  27. 27. Data Analysis • Appendix A 27 pp. 68-81
  28. 28. Next Steps • Comments • Run & feedback from committee data analysis • Analyze findings • Discuss findings & implications • Revisions (committee suggestions) • Professional editor • Revisions/edits • Defense 28
  29. 29. Questions 29

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