A study to assess the level of perception of undergraduate students towards social networking sites for constructing virtual learning community

1. Dhanya G.
Research Scholar
School of pedagogical Sciences
M. G. University
Kottayam.
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2. Virtual learning communities
• Digital or virtual learning communities
are social aggregations for knowledge
sharing that emerges from the internet
to form webs of academic relationships
in cyberspace (Rheingold, 1993).
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3. Attributes of virtual community
(Whittaker ,Issacs & O’Day , 1997 ).
Shared goal
Active
participation
Shared activities
among
participants
Policies
determining the
access to
resources
Reciprocity of
information
Support and
services among
members
Shared context
of social
conventions
Language Protocols
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4. Social network sites
• Social network sites are web-based
services which permit individuals to
construct a public or semi-public profile
within a bounded system (Boyd &
Ellison, 2007).
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5. Need of the study
• Virtual community act as the powerful
medium for interaction in the new internet
world (Rothaermel, & Sugiyama, 2001).
• Social networking sites have large
applications for supporting collaborative
learning and active interaction.
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6. Key factors for the success of a
learning community (Palloff & Pratt, 1999).
Honesty
Responsiveness
Relevance
Respect
Openness
Empowerment
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7. Learning Community Building in
Social Networking Sites
• Profiles, friends list and public commenting
will forms primary structure of social
networking sites (Boyd, 2007).
• The success of site invariably depends on
easiness perceived by the users for their
interaction.
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8. Classification of social networking sites
Type of SNS Function Example
Academic and research
based social networks
Showcase academic accomplishments
Lists scientific conferences
Shares research papers
Academia.edu
ResearchGate.net
Scholastica
Friend based Social
Networks
Not focus on a particular topic.
Permits the users to join groups and attach to
people whose interests are alike
Facebook, MySpace,
Friendster, etc
Music and Movie based
Social Networks
Connects people with similar interest in movies
and music
LastFM, Flixter, iLike
etc.
Mobile based Social
Networks
Designed for mobile users. Loopt etc.
Business Social
Networks:
Networks for business contact
Shares information related to the job and business
LinkedIn, XING,
Konnects etc.
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9. Objectives of the Study
1. To assess the level of perception of undergraduate students towards
social networking sites for constructing virtual learning community.
2. To assess the level of perception of undergraduate students towards
various facilities of social networking sites such as (1) digital identity
management, (2) digital content creation and (3) digital collaboration.
3. To assess the difference in the perception of male and female
students towards social networking sites for constructing virtual
learning community.
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10. Perception towards Social Networking
Sites
Digital identity
management
Digital
content
creation
Digital
collaboration
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11. Digital identity management
• Management of digital identity involves
strong password and controlled access to
individual profiles.
• Identity in digital world is associated to
diverse aspects of cyber ethics.
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12. Digital content creation
• For this, information, writings and images
should be transformed to digital format.
• Uploaded photos, videos, and articles various
forms of electronic contents that can be
created through social networking sites.
• Digital creativity is the more significant here
than mere technical skills.
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13. Digital Collaboration
• It is the application open source data and
cloud technology to share knowledge,
manage information and contribute user
generated content to communities of people
regardless of time or place (Tapscott
&Williams, 2006).
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14. Sample of the Study
• A convenient sample of 120 undergraduate
internet users.
• The age of the participants ranged between 18
and 22.
• All the participants have at least one year of
experience in using social media.
• Face book is the most admired social
networking site among the participants.
• The sample includes 64% female and 36% male
students.
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15. Tool Used
• Three point scale.
• Seven statements were provided for each of
the three components .
• Certain statements in the tool were adopted
from a scale prepared by Park and Kim (2013)
for measuring intensity of social network of
graduate students.
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16. Analysis of perception of graduate students towards Social
networking sites
• The mean score obtained by the sample was
calculated : 24.33
• Standard deviation :6.74.
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17. Distribution of students based on the
perception towards social networking sites
No. Level of
perception
Frequency Percentage
1. High 28 23.3 %
2. Moderate 59 49.2%
3. Low 33 27.5%
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18. Graphical representation of distribution of students based on
the perception towards social networking sites data
0
10
20
30
40
50
60
High Moderate Low
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19. Analysis of perception of graduate students towards facilities
available in social networking sites
• The mean and standard deviation of scores
for digital identity management were 7.01
and 3.03 respectively.
• Scores of digital content creation have got
values 8. 9as mean and 2.6 as standard
deviation
• 8.7 and 2.9 were the mean and standard
deviation of the scores of digital
collaboration.
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20. Distribution of students based on the
perception towards various services of social
networking sites
Component Percentage of students having level of perception
High moderate Low
Digital identity
management
20.0% 32.5% 47.5%
Digital content
creation
45.0% 35.8% 19.2%
Digital
collaboration
39.2% 35.0% 25.8%
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21. Graphical representation of distribution of students based on
the perception towards various services of social networking
sites
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22. Analysis of perception of graduate students towards social
networking sites with regard to gender
• H0: There is no significant difference between
the mean scores of perception of boys and
girls towards social networking site.
• In order to test this, data was collected from
43 boys and 77 girls. Analysis was done using
inferential statistics t- test. The detail of the
analysis is given in table 4.
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23. Mean standard deviation and calculated t- value of scores of
male and female student
Gender N Mean S.D t-value df
Female 77 2 4.16 6.46
0.7011 119
Male 43 24.69 7.25
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24. Major Findings
• 1. Most of the students have moderate level of
perception towards social networking sites.
• 2. With regard to perception towards facilities in
social networking sites higher numbers of students
have high level perception towards digital content
creation, but most of them have lower perception
towards digital identity management.
• 3. There is no difference in the perception of male
and female students towards social networking sites.
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25. Educational Implications
• The study reveals enthusiasm of
students to participate in the activities
of learning community.
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26. Virtual extension of learning activities
• Highly structured, time bounded formal
classrooms are inadequate to ensure the
complete participation of students.
• During academic discourses in social
networking sites all students will get equal
opportunity to express their views regarding
specific content.
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27. Technical skills and ethical principles
• Digital learning community will be effective
only if the collaborating partners are efficient
in handling tools for managing digital
identity.
• Additional skill development sessions should
be arranged for teachers and students to
practice various attributes of cyber ethics.
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28. Source to improve self efficacy and
motivation of students.
• Parents and other stakeholders have access
to the contents shared in social media.
• Postings regarding student achievements
and college club activities will bring about
social recognition of students.
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29. Conclusion
• Online technology has influenced all levels of social and
academic life.
• But all sophisticated technologies are not readily available
in conventional classrooms.
• Social networking sites open tremendous opportunities
for knowledge creation, conservation and sharing.
• Although it is not an ideal substitute for face-to-face
learning, acts as reliable platform for lifelong learning.
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30. Reference
• Bhandari, S. R. (2011). Managing users ins Social networking sites. (Bachelor Degree Thesis, Lahti University of
Applied Sciences). Retrieved fromhttp://www.theseus .fi/bitstream /handle /10024 /3310.
• Boyd, D., & Ellison, N. B. (2007). Social network sites: definition, history and scholarship. Journal of Computer-
Mediated Communication, 13(1), 210-230. doi: 10.1111/j.1083-6101.2007.00393.x.
• Boyd, D. (2007). Social Network Sites: Public, Private, or What?. Knowledge Tree. Retrieved from
http://kt.flexiblelearning. net .au/tkt2007/?id=28.
• Palloff, R. M. & Pratt, K. (1999). Building learning communities in cyberspace. Sanfrancisco: Jossey-Bass Inc.,
Publishers.
• Park C. & Kim, Y. J. (2013). Intensity of Social Network Use by Involvement: A Study of Young Chinese Users.
International Journal of Business and Management, 8( 6), 22-33. doi:10.5539/ijbm.v8n6p22.
• Rheingold, H. (1993). Virtual community reading. MA: Addison Wesley.
• Rothaermel, F. T., & Sugiyama, S. (2001).Virtual internet communities and commercial success: individual and
community-level theory grounded in the atypical case of TimeZone.com. Journal of management, 27, (3), 297-312.
doi.: 10.1016/S0149-2063(01)00093-9.
• Tapscott D. & Williams, A. D. (2006). Wikinomics how mass collaboration changes everything. New York: Penguin
Group (USA) Inc.
• Whittaker, S., Issacs, E., and O’Day, V. (1997) Widening the Net: Workshop report on the theory and practice of
physical and network communities. Sigchi Bulletin, 29(3), 27–30.
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