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CHU , Samuel Kai Wah, Associate Professor Head, Division of Information and Technology Studies

Is knowledge management in decline? How various social media (Facebook, blog, and wiki) can support KM in learning?. CHU , Samuel Kai Wah, Associate Professor Head, Division of Information and Technology Studies Deputy Director, Centre for Information Technology in Education

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CHU , Samuel Kai Wah, Associate Professor Head, Division of Information and Technology Studies

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  1. Is knowledge management in decline? How various social media (Facebook, blog, and wiki) can support KM in learning? CHU, Samuel Kai Wah, AssociateProfessor Head, Division of Information and Technology Studies Deputy Director, Centre for Information Technology in Education Faculty of Education, The University of Hong Kong

  2. Is Knowledge Management (KM) in decline? • Most Admired Knowledge Enterprises (MAKE) Awards • KM in Hong Kong • Dr Bonnie Cheuk's experience and observation

  3. Most Admired Knowledge Enterprises (MAKE)Awards • Commenced in 1998 (makeawards.com, 2014) • Leaders in transforming individual and enterprise knowledge into shareholder value • Eight criteria to evaluate the nominee that involves many factors like knowledge-oriented culture, leadership, knowledge intensive products, services, and solutions, intellectual capital maximization, knowledge sharing environment, organizational learning, customer knowledge, and value creation (makeawards.com, 2014) • MAKE company who has satisfactory knowledge management performance always have outstanding financial and business performance (makeawards.com, 2014)

  4. MAKE awards across the globe

  5. MAKE awards in recent years Member of the Judging Panel of the 2009, 2011 & 2014 Hong Kong Most Admired Knowledge Enterprise Award – Sam Chu

  6. Companies value KM awards

  7. Development of KM in Hong Kong • Started with consulting firms • Then with corporations, government departments, & NGO (non-governmental organization) • In recent years, with education • 1st major KM in Education seminar held by the Knowledge Management Research Center in 2011 • 1st PhD thesis on KM in school education – Implementing knowledge management in school environment : a principal's leadership-driven approach, by Chu Kai Wing in 2013 at HKU • Education Bureau begins to apply KM

  8. Bonnie Cheuk'sexperience & observation - 1 Source: http://bonniecheuk.blogspot.tw/

  9. Bonnie Cheuk'sexperience & observation - 2

  10. Bonnie Cheuk'sexperience & observation - 3 Source: http://collaboration2013.we-conect.com/en/preview/speakers/speakers-overview/ Source: http://www.erm.com/en/Analysis-and-Insight/Publications/Publications-Archive-2009---2010/Using-Minerva-to-Create-Health--Safety-Success/

  11. Bonnie Cheuk'sexperience & observation - 4 Bonnie won the Environmental Business Journal Award for Organizational Innovation (2008) and Neilson's Top 10 Best Intranet Award 2009 for ERM, the world's largest environmental consulting firm - http://collaboration2013.we-conect.com/en/preview/speakers/speakers-overview/

  12. References • makeaward.com. (2014). Introduction. Retrieved October 20, 2014, from http://www.makeaward.com/intro.php • makeaward.com. (2014). Assessment Criteria. Retrieved October 20, 2014, from http://www.makeaward.com/ac.php

  13. Knowledge Management using Social Media:A Comparative Study between Blogs and Facebook CHU, Samuel Kai Wah, AssociateProfessor Ng, Ka Wan, former HKU MScLIM student Faculty of Education, The University of Hong Kong Pokfulam Road, Hong Kong

  14. INTRODUCTION - 1 • Social media is defined as “a group of internet-based application that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user generated content” (Kaplan & Haenlein, 2010, p. 61) • Examples of social media include blogs, social networking sites, wikis, video and photo-sharing sites, etc. • Social media has recently emerged as a promising technology for knowledge management (KM) (Levy, 2009; Yates & Paquette, 2011).

  15. LITERATURE REVIEW - 1 An Integrated KM Cycle (Dalkir, 2011)

  16. LITERATURE REVIEW - 2 • Blogging was found to be a good learning tools for internship by facilitating information and knowledge sharing (Chu, Kwan & Warning 2012) • Receiving emotional support and feedbacks from both teachers and peers are important to student internship experiences (Murray-Harvey, 2001)

  17. LITERATURE GAP • Unsure about the effects of using Facebook as the communication tool during students’ internship • Very few studies, if any, have focused on comparing blogs and Facebookin terms of their effectiveness in facilitating knowledge management and cultivating a knowledge sharing culture during internship.

  18. RESEARCH QUESTIONS • Purpose: To examine the incorporation of Blogs and Facebook into internship of two groups of students over six cohorts: 3 years of Blogs intern users (n=47) and 3 years of Facebook intern users (n=64). • Research questions: • How do student users use Blogs and Facebook for knowledge management? • Is Blogs or Facebook a better tool in facilitating knowledge management activities? • Is Blogs or Facebook a better tool in cultivating a knowledge sharing culture?

  19. RESEARCH METHODS • Mixed research method • Qualitative data • Content analysis of blog/Facebook posts • Interviews • Quantitative data • Questionnaire on participants’ perceptions

  20. PARTICIPANTS • The study involved two groups of students (n=111) from the Bachelor of Information Management (BScIM) program. • They were asked to document their knowledge and experience gained during their internship (2-3 months) • Group 1 (n=47) used blogs (Xanga, Blogger, Drupal and YouBlog) • 2006-2008 • Group 2 (n=64) used Facebook • 2011-2013

  21. INSTRUCTIONAL DESIGN • A blog site or a Facebook private group page was set up and made accessible to only the participating students and course lecturers. • Students were asked to reflect and share their internship experience on the online platform every one to two days. • They were also told to post a minimum of one to two comments to their peers’ logs every week. • For both groups of students, their engagement in the corresponding online platform constitutes to part of their final grade of the course.

  22. DATA COLLECTION - 1 • Content analysis • The blog entries, posts and comments were extracted from the online blogging system and Facebook at the end of each internship period. • Questionnaire • Prompts users’ perceptions of blogs/Facebook for mutual support and collaboration • Structured telephone interviews • Investigate users’ perception of blogs/Facebook as a knowledge management tool

  23. DATA ANALYSIS - 1 • The content of the students’ blogs and Facebook was analyzed qualitatively using NVivo10 software. • Each blog entry, Facebook post or comment was considered as a unit of analysis. • The coding framework was developed from the preliminary coding. • The content was first classified into either knowledge management processes or socio-emotional expressions.

  24. DATA ANALYSIS - 2 Table 1Coding framework of knowledge management processes

  25. DATA ANALYSIS - 3 Table 2Coding framework of socio-emotional expressions

  26. DATA ANALYSIS - 4 Source: Chu, S.K.W., Chan, C.K.K., & Tiwari, A.F.Y. (2012). Using blogs to support learning during internship. Computers & Education, 58(3), 989-1000.

  27. DATA ANALYSIS - 5

  28. DATA ANALYSIS - 6 • The quantitative data were analyzed using SPSS version 20.0. • Responses on the Likert-type scales were summarized and analyzed using descriptive statistics. • Mann–Whitney tests were employed to compare the perceptual differences between blog and Facebook users. Statistical significance level was set at p < 0.05.

  29. RESULTS AND DISCUSSION - 1Knowledge management activities on blogs and Facebook Table 3 Distribution of coded blogs and posts in the theme of knowledge management processes Note: The figures represent the average number of Blog entries/Facebook posts each participant contributed. • Knowledge capture • The popularity and user-friendly interface of Facebook, as identified by a participant (HTH), were the key factors that facilitate its users to elicit tacit knowledge, and allowed it to overtake blogs in instant and quick knowledge capture. • Knowledge sharing and dissemination • As noted by one of the participants (WCM), “when you posted anything in the group, everyone can view it. With notifications users can read the most updated comments from their friends easily and immediately. Hence, it helps facilitate knowledge sharing.”

  30. RESULTS AND DISCUSSION - 2Socio-emotional expressions on blogs and Facebook Table 4 Distribution of coded blogs and posts in the theme of socio-emotional expressions Note: The figures represent the average number of Blog entries/Facebook posts each participant contributed.

  31. RESULTS AND DISCUSSION - 3Perception of social support via blogging and Facebook Table 5 Students’ overall rating on the use of Blogs and Facebook Notes: Ratings are based on a 4-point Likert-type scale: 1-‘Strongly disagree’, 2-‘Disagree’, 3-‘Agree’, and 4-‘Strongly agree’ (With a mid-point of 2.5). *statistically significant at p < 0.05.

  32. REFERENCES • Dalkir, K. (2011). Knowledge Management in Theory and Practice. England, Cambridge: The MIT Press. • Ferdig, R. E. & Trammell, K. D. (2004). Content delivery in the 'Blogosphere'. Technological Horizons in Education Journal, 31, 7. Retrieved from http://www.thejournal.com/magazine/vault/articleprintversion.cfm?aid=4677 • Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59-68. • Levy, M. (2009). Web 2.0 implications on knowledge management. Journal of Knowledge Management, 13(1), 120-134. • Ojala, M. (2005). Blogging for knowledge sharing, management and dissemination. Business Information Review, 22, 269–276. • Wiig, K. (1997). “Knowledge Management: Where Did it Come From and Where Will It Go?”, Expert Systems with Applications, Special Issues on Knowledge Management, 13(1), 1-14. • Wong, K., Kwan, R. & Leung, K. (2011). An Exploration of Using Facebook to Build a Virtual Community of Practice. Proceedings of the 4th International Conference, ICHL 2011 (pp. 316-324), Hong Kong, China. • Yates, D. & Paquette, S. (2011). Emergency Knowledge Management and Social Media Technologies: A Case Study of the 2010 Haitian Earthquake. International Journal of Information Management, 31(1), 6-13.

  33. how can wiki facilitate KM in students’ group project learning? CHU, Samuel Kai Wah, AssociateProfessor Yu, Kai Cheng, HKU student Faculty of Education, The University of Hong Kong Pokfulam Road, Hong Kong

  34. PARTICIPANTS • Students in 3 education levels, (total N = 801), participated in a survey • Group 1 386 primary school students • Group 2 347 secondary school students • Group 3 67 university school students • They were asked to answer a questionnaire including five criteria after their project completion with aid of wiki tools. • Learning 4-6 questions • Motivation 4-6 questions • Group Interaction 4-6 questions • Technology 4-6 questions • Knowledge management ( 0 for primary, 3 for secondary and 6 for university)

  35. QUESTIONNAIRE-University Student -1 Sample Size N = 67 (for all questions) Likert Scale: 1 Strongly Disagree to 5 Strongly Agree

  36. QUESTIONNAIRE-University Student -2 Sample Size N = 67 (for all questions) Likert Scale: 1 Strongly Disagree to 5 Strongly Agree

  37. Primary Level – Google Sites

  38. Secondary Level - PBWorks

  39. University- WikiBooks

  40. DATA ANALYSIS - 1 • The data from the survey was analyzed using SPSS v.22.0. • Overall comparison between 3 education levels • Use mean of all questions in one criteria as statistics • Overall scale is from 1 (strongly disagree) to 5 (strongly agree) • Primary school question scale 1 – 5. • Secondary school question scale 1 – 5. • University question scale 1 – 7 , rescale each question by 5/7. • One sample t-test on each criteria with confidence interval (i.e. CI ) • Assumptions using t-test: sample is large ( n > 30 ). • Shows in column chart with mean value and CI displayed. Note: confidence interval calculated from the given sample set. It is an estimated range of plausible values of the true value, or the true mean of the population. A 95% CI means that there is a 95% probability that one will find the true value in the estimated range. The width of the CI indicates the reliability of the estimation. A narrower CI indicates more reliable result than a wider CI (Dalgaard, 2002).

  41. DATA ANALYSIS – 2 • Knowledge Management construct • Only involve secondary school and university • One sample t-test on 3 common questionnaire questions • Knowledge creation • Knowledge sharing • Knowledge dissemination • Independent sample t-test on these 3 question to see if there’s a difference between the 2 groups • Set the significant level p<0.05 • Compare the means between two groups, secondary and university

  42. RESULT Overall Comparison Graph notation: Y-Axis: (Likert Scale) 1 (Strongly disagree) – 5 (Strongly agree) Red line: stands as neutral. Group Interaction KM Technology Learning Motivation Likert Scale 95% CI: 95% probability that one will find the true value in the estimated range.

  43. RESULT KM Impact Comparison Graph notation: Y-Axis: (Likert Scale) 1 (Strongly disagree) – 5 (Strongly agree) Red line: stands as neutral. Knowledge Transferring Knowledge Creation Knowledge Sharing Likert Scale 95% CI: 95% probability that one will find the true value in the estimated range.

  44. RESULT University Level Graph notation: Y-Axis: (Likert Scale) 1 (Strongly disagree) – 5 (Strongly agree) • Knowledge creation • A process which results in non-existing knowledge. (Hari, S., Egbu, C., Kumar, B. ,2005) • Knowledge capturing • Finding ways to make tacit knowledge explicit. (Smith, 2000) • ,2005) • Knowledge acquisition • A process of acquire existing knowledge, from knowledge capturing and creation process. (Gold, Malhotra, Segars,2001) • Knowledge application • Actual use of knowledge captured or created in KM cycle.(Dalkir, 2005) • Knowledge transferring • Aprocess of getting a packet of knowledge from one organization to another. • (Stuhlman, 2006) • Knowledge sharing • A process of exchange of knowledge. • (Stuhlman, 2006) 95% CI: 95% probability that one will find the true value in the estimated range.

  45. Obstacles for using Wiki Tools Negative comments given by students to TWiki From: “Chu, S. (2008). TWiki for knowledge building and management. Online Information Review, 32(6): 745-758.” What’s the circumstances now?

  46. References • Chu, S. (2008). TWiki for knowledge building and management. Online Information Review, 32(6): 745-758 . • Dalgaard, P. (2002). Introductory Statistics With R. New York: Springer. • Dalkir, K. (2005). Knowledge Management In Theorey And Practice. Burlington: Elsevier Butterworth-Heinnemann. • Field, A. (2009). Discovering Statistics Using SPSS 3rd Edition. London: SAGE. • Hari, S., Egbu, C., Kumar, B. (2005). A knowledge capture awareness tool: An empirical study on small and medium enterprises in the construction industry. Engineering, Construction and Architectural Management, 12, 533-567. • Gold, A.H., Malhotra, A., Segars, A.H. (2001). Knowledge Management: An Organizational Capabilities Perspective. Journal of Management Information Systems, Summer, 18(1), 185-214 • Smith, L. (2000). Knowledge discovery, capture and creation. Bulletin of the American Society for Information Science, 26, 11-12. • Stuhlman, D. D. (2006). Knowledge Management Terms. Retrieved Dec 15, 2007 from http://home.earthlink.net/~ddstuhlman/defin1.htm.

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