2014 e learning innovations conference

1. By
Jotham Kilimo Mwale
Multimedia University of Kenya
eLearning Innovations Conference & Expo
31st July 2014

2. OUTCOMES
 By the end of this session, you will be able to
 Identify learning theories that support use of social
media
 Relate social media and eLearning
 Evaluate readiness of higher education institutions to
integrate social media in eLearning

3. Introduction
 Higher Education Institutions (HEIs) in Kenya are today in a
competitive environment.
 According to Commission for University Education (CUE),
the numbers at 30 June 2013:
 Public universities = 22 (+ 9 Constituent Colleges)
 Chartered private universities = 17 (+5 Constituent Colleges)
 Private universities with Letters of Interim Administration = 11
(+2 registered universities)
 TOTAL HEIs in Kenya = 66.
 Number of students enrolled 1st year = 93,000: 53,000 public,
30,000 public self-sponsored, 10,000 private (2013/14)
 KCSE Candidates 432,443 (2012), 444,696 (2013).
 Working class back to school
Sources: CUE (2014); Kenya Economic Report 2013

4. Introduction …
 Mobile subscribers = 31.3 million (76.9% penetration)
 Internet subscriptions = 11.6 million
 Internet users = 19.1 million (access: 47.1 per 100
people)
 Broadband subscriptions = 1.39 million
 In Africa, Kenya is:
 2nd highest Twitter usage (SA)
 4th highest user of Internet (NIG, EGY, MOR)
 7th highest user of Facebook (EGY, NIG, SA, MOR, ALG,
TUN)
Source: CCK Report Q1 2013/14; Africa Internet Statistics 2012

5. Research Aim
 Seeks to establish whether the popularity and common
usage of social networking software and associated
Web 2.0 services and applications could be translated
into tools for academic use in institutions of higher
education.

6. Research Objectives
 To obtain information from the lecturing staff on e-
Learning, social media usage and Web 2.0 technologies
in order to establish their readiness for the pedagogical
change.
 To obtain information on the student knowledge and/or
experience of social media so as to determine acceptance
level of Web 2.0 enhanced eLearning environment.
 To develop a strategy to implement the Web 2.0 e-
Learning solution based on analysis of the information
obtained above.

7. The Location
 The project is mainly carried out at the Multimedia
University of Kenya, where the researcher works as a
lecturer.
 Multimedia University of Kenya (MMU) is a public
university chartered on 1st March 2013.
 1948 Central Training School (EAP&TC)
 1992 Kenya College of Communications Technology
(KCCT)
 2008 Multimedia University College of Kenya (JKUAT)

8. Learning Theories
 Behaviorism – the learner is passive (no prior knowledge or
processing), only responding to environmental stimuli.
Since learner responds purely to the environment, it can be
assumed the role of technology will be minimal if any.
 Cognitivism – the learner processes information (through
thinking, knowing, and problem-solving) and thus action
is a consequence of thinking. This has more emphasis on
internal processing systems of the learner and the role of
technology would be minimal, probably enabling the
provision of the inputs into the internal processing system.
Source: Learning Theories (2008) http://www.learning-theories.com/paradigms

9. Learning Theories …
 Constructivism – the learner constructs information
from prior knowledge or context. Technology can play
a major role by defining the context for the learner in
terms of multimedia environment presentation.
 Humanism – the learner has cognitive needs and acts
to fulfill one’s potential. The goal is self-actualization
of the student and hence technology can facilitate this
process through an online learning environment.
 Vygotsky’s Social Development Theory helps create
learning contexts where student is more active in
learning process.
Source: Learning Theories (2008) http://www.learning-theories.com/paradigms

10. Development of the Web
 Web 1.0 – read only (one-way), static content
 HTML, HTTP, URL
 Web 2.0 – read/write, social web
 Dynamic web technologies, ASP, AJAX, SNS, podcasts
 Web 3.0 (Semantic web) –
read/write/request/collaborate big data, linked data
 RDF, XML, OWL, 3D

11. The Web and e-learning
 Web 1.0 – Content management, one-way
 CBT, LMS, VLEs, eBooks
 Pedagogy
 Web 2.0 – Blended learning, content authoring, two-way,
multimedia content
 LCMS, social networks, Video conference, VLEs , mashups
 Andragogy
 Web 3.0 – learner-centred, ubiquitous learning, knowledge
representation
 PLEs, social semantic web, second life, personal avatars
 Heutagogy

12. Elearning and Social Media
 As stated by McLoughlin and Lee (2008), Web 2.0-based
social software tools such as blogs, wikis, social networking
sites, media sharing applications, and social bookmarking
utilities are also pedagogical tools that stems from their
enabling the sharing, communication, and information
discovery.
 McLoughlin and Lee (2008) have described this as
“pedagogy 2.0”, which they define as “a framework that
aims to focus on desired learning outcomes in order to
exploit more fully affordances and potential for
connectivity enabled by Web 2.0 and social software tools.”
McLoughlin, C., Lee, M. (2008) The Three P's of Pedagogy for the Networked Society: Personalization,
Participation and Productivity

13. Pedagogy 2.0
 Pedagogy 2.0 has three principles:
 Personalization entails the student engages in making
personal choices in a ‘learner-centred’ e-learning
environment.
 Participation captures the social nature of Web 2.0 in
enabling the student interact with peers and even teachers in
a social learning space, much unlike the traditional classroom
where the teacher-student relationship is one of the giver and
the receiver of knowledge. The emphasis here is the student-
to-student peer relationship (community) and connectivity
for purposes of learning.
 Productivity is the contribution of knowledge by the student
through learner-centred activities through peer-to-peer file
and media content sharing.

14. Pedagogy 2.0 …

15. Conceptual Framework
 The framework is derived from the works of Khan
(1997) Framework for E-learning, and McLoughlin and
Lee (2008) Framework for Knowledge Creation in Web
2.0 and Pedagogy 2.0 as discussed above.
 Applying the synergy of Web 2.0 tools and affordances
in e-learning with the 3 P’s of Pedagogy 2.0 result in
knowledge creation, which is a social constructivist
learning paradigm that uniquely identifies with Web
2.0 enhanced e-learning environment
 This new framework is then applied to Khan’s
Pedagogical Dimension.
Khan, B. (1997) E-learning model framework. Retrieved from http://www.asianvu.com/bookstoread/framework/

16. Conceptual Framework For E-
learning Knowledge Creation
Productivity
Personalization
Participation
Creativity
Idea Generation
Awareness
Connection
Conversation
Collaboration
Individuals
Ideas
Community &
networks
Knowledge Creation
Pedagogy 2.0 Web 2.0
PEDAGOGICAL DIMENSION
Lecturer
enabled
Technology
enabled
Student experience

17. Research Design
 Study based at Multimedia University of Kenya
 Targets faculty staff and students for primary data
 Self-administered questionnaires based on Conceptual
Framework to test hypotheses
 Samples
 Lecturers: Population of 86; sample size of 70 for 95
confidence rating
 Students: Population of 1,850; sample size of 318. For response
rate of 60%, actual sample is 528.

18. Research Design …
 Questionnaires will collect the following data:
 Lecturers:
 preparedness for e-learning (computer literacy, access to
Internet, current use in teaching, which courses suitable for e-
learning)
 preparedness for Web 2.0 (social networking exposure, access
frequency)
 Willingness to convert some courses to e-learning platform.

19. Research Design …
 Students
 Current exposure to the Web and which activities
dominate (email, blogging, social networking,
information search, etc)
 Social networking experience (how much time spent,
main activities, access frequency)
 Willingness to use Web for education purposes.
 Data analysis
 Quantitative methods, using SPSS
 Qualitative methods: deductive approach

20. Data Collection
FACULTY POPULATION ACTUAL
1 Business 16 3
2 Engineering 42 5
3 Computing & IT 17 7
4 Media & Communication 11 6
TOTAL 86 21

21. Data Collection …
FACULTY POPULAT
ION
SAMPLE
SIZE
TARGET
FOR 60%
RESPONS
E
ACTUAL
1 Business 413 71 118 66
2 Engineering 350 60 100 76
3 Computing & IT 475 82 135 103
4 Media & Comm. 612 105 175 56
TOTAL 1,850 318 528 301

22. Data Analysis
Lecturer Questionnaire …
Mean = 3.11
SD = 1.243

23. Data Analysis
Lecturer Questionnaire …
Mean = 4.32
SD = 0.478

24. Data Analysis
Lecturer Questionnaire …
Mean = 4.16
SD = 0.375

25. Lecturer Analysis
 The respondents were too few, thus statistically
insignificant for any meaningful analysis and
generalization.
 However, the sample shows results close to another by
Pearson (2013) in personal use of social media
frequency and by site.
Seaman, J., Tinti-Kane, H (2013) Social Media for Teaching and Learning
SURVEY DAILY -
MONTHLY
RARELY DO NOT
USE
PEARSON 70.3% 13.6% 16.1%
MMU 87.6% 12.4% 0%

26. Lecturer Analysis …
 Social media usage by site
 “E-learning enables tutors to give students better
individual attention than traditional classroom”
 Mean = 3.11; Standard deviation =1.243
 Lecturers opinions very divergent
SITE PEARSON MMU
Twitter 10.5% 9.5%
LinkedIn 24.4% 23.8%
Facebook 57.0% 42.9%

27. Data Analysis
Student Questionnaire …
Mean = 3.54
SD = 1.181

28. Data Analysis
Student Questionnaire …
Mean = 3.92
SD = 0.978

29. Data Analysis
Student Questionnaire …
Mean = 4.16
SD = 0.821

30. Data Analysis
Student Questionnaire …
Mean = 3.88
SD = 1.088

31. Data Analysis
Student Questionnaire …
Mean = 3.73
SD = 1.144

32. Student Analysis
 Most agreed on “my learning is improved when I share
my ideas with fellow students”
 Mean = 4.45; SD = 0.674
 Most diverse opinion was on “I prefer e-learning to
traditional classroom because of the flexibility and
convenience of studying it gives me”
 Mean = 3.54; SD = 1.181
 Correlation highest in collaborating/sharing ideas and
belonging to community of choice
 Weak association between strong opinion on
usefulness of social networks for creativity,
collaboration, community and access frequency.

33. Student Analysis …
 Internet access frequency
 Use of social media by site
DAILY WEEKLY MONTHLY NEVER
59.4% 29.7% 5% 2%
SITE USAGE
Facebook 54.1%
Twitter 20.1%
LinkedIn 5.9%

34. Findings
 Lecturer proposition:
 The lecturers who frequent the Internet and social
networking sites are more likely to adopt Web 2.0
enhanced e-learning as a teaching tool.
 Test results:
 Not valid as sample was statistically insignificant.
 Sample had converged positive opinion on use of social
media tools for teaching.

35. Findings …
 Students proposition:
 The students who frequent social networking sites are more
likely to be ready for the adoption of Web 2.0 technologies in
e-learning.
 Test results:
 Weak association between strong opinion on usefulness of
social networks for creativity, collaboration, community and
access frequency.
 Web 2.0 (social media) tools present the technological
platform for the realization of social constructivist learning
theory.
 Students are inclined to social constructivist aspects such as
sharing, collaboration and creativity, hence more likely to
engage in such an environment for education purposes.

36. Discussions
 The lecturers were surveyed to establish their
readiness for the pedagogical change envisioned.
 The response was poor and hence cannot be generalized.
 However, it’s worth noting that those who access the
Internet and have social networking experience gave
favourable opinions on the issues of pedagogy and Web
2.0.
 This shows willingness and ability to teach in this new
environment.

37. Discussions …
 The students also showed appreciation for the Web 2.0
environment by answering favourably to the questions
on social networking experience that touched on the
creativity, sharing and collaboration aspects, which are
social constructivists learning tenets.
 Thus it can be concluded that these students are ready
and will most likely accept and benefit learning on this
environment.
 However, it must be emphasized that Pedagogy 2.0 is
the catalyst to having students apply social networking
experiences in education.

38. Conclusions …
 From the Multimedia University of Kenya study, it has
been found that:
 Lecturers are ready but not yet using social media or Web
2.0 tools for elearning.
 Students are most likely going to make good use of the
social media or Web 2.0 tools to enhance eLearning
experience when engaged by the lecturer
 Elearning enhanced by the use of social media tools will
transform the teaching and learning experience by the
infusion of social constructivist concepts of creativity,
collaboration and community.
 The result would be knowledge creation; a
transformation in higher education

39. Implementation
 Equip lecturers with basic instructional design skills
with emphasis on productivity, participation and
personalization to create eLearning courses
 Expect lecturers to use the in-built Web 2.0 tools in the
LMS/LCMS for supporting students
 Encourage lecturers to use existing social media (i.e
Facebook, Twitter, etc) to enrich student support

40. Implementation …
 Challenges to overcome:
 Lack of Institutional support
 Strategic plan, policy
 Sufficient funding
 Transforming lecturers pedagogically
 Training on e-pedagogy
 Motivation to convert courses, use social media tools
 Leveraging student social network experience for
academic opportunity
 Move from notifications to academic discussions,
collaborations

41. Implementation …
 MMU Experience
 Established Centre for Open, Distance and eLearning
(CODeL)
 Training of lecturers on ID and e-Pedagogy ongoing
(started with ‘champions’)
 Blended learning used for the course units already
uploaded on eLearning platform (Moodle)
 Expect to launch short courses in 2014 and full degree
course in 2015
 Unique challenge:
 Most of our courses are practical/technical

42. Thank you
jmwale@mmu.ac.ke