Big-Data Analytics on Blended e-Learning
eLearning Forum Asia (eLFA) 2015
18 June 2015
YEUNG Sze Kiu
[email protected]
&
Ivy CHIA Sook May
[email protected]
SIM University
18 June 2015
Agenda
1.
What is Blended Learning
2.
Context of Study
3.
Investigation
4.
Findings
5.
Conclusion
Slide 2/12
“Googling” Blended Learning
•
5,360,000 hits
•
The newest consult-‐driven x-‐hype, the next big
thing replacing e-‐learning, outstanding
pedagogical innovaFon, etc.
•
"hybrid," "technology-‐mediated instrucFon,"
"web-‐enhanced instrucFon," and "mixed-‐
mode instrucFon" are oJen used
interchangeably with “blended”
Context of the Study
•
UniSIM is the largest adult university in Singapore, serving
13,369 part-‐Fme and full-‐Fme students. Average age of
students is 30.
•
It has approx. 500 or more undergraduate courses from 4
Schools (SBZ, HDSS, SASS & SST)
•
It has been implemenFng online learning since 2012, with
support of Blacbkboard LMS and other digital media tools
(e.g. interacFve iSG).
•
The target is to transit all courses to blended learning
eventually with 50% by end of 2015. Currently, 46.2% of the
courses are blended.
•
The revised structure of all courses will have 3 face-‐to-‐face
Before and AJer
Students meet tutors
6 #mes
face-‐to-‐face for
lessons (6 weeks).
Students meet tutors
3 #mes
face-‐to-‐face for
lessons, with the
remaining of the learning done
online
(6 weeks):
•
iSG (interac<ve textbooks)
•
Blackboard LMS
•
Chunked lessons (excerpts of 5-‐10 min digital content with
audio commentary)
•
Online forma<ve quiz
Data Analytics on Blended e-Learning
Blended Learning:
F2F Instruction + Online Learning (through Blackboard
LMS)
Online Learning (Blackboard LMS):
Pre-class quiz, Chunked Recorded
Lectures, Digital Content, Virtual Classrooms & Discussion forums.
UniSIM’s Learning Management
System
Demo Sharing Mr Stephen Low
Overview Video
Collaborate
Chunked Audio Lectures
T-‐tests for the Two Groups
12 Courses (4 Schools)
1420 Students
Means Scores
•
Overall Con<nuous
Assessment Score
•
Overall Exam Scores
•
Final Rank Scores
12 Courses (4 Schools)
1455 Students
Mean Scores
•
Overall Con<nuous
Assessment Score
•
Overall Exam Scores
•
Final Rank Scores
Inves<ga<on
: To find out if there is a significant difference between the mean
scores of these two groups of students.
Courses Selected for Study
Slide 4/12
School of Business
School of Arts and
Social Sciences
School of Science and
Technology
School of Human
Development and Social
Services
Data Analytics on Blended e-Learning
Data Mining
LMS
SIMS
Learning Analytics System
Student
Learning
+
OCAS
Data
Student
Record &
Performance
Data
(OCAS, OES
+ FRS)
Not Available –
preferred option
Available – used
for big-data analytics
Legend
*Significant increase
69.5 53.1 60.9 72.1 52.2 61.5 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 OCAS OES FRS M e a nOverall Mean Scores (All Schools)
Before (6F2F) AJer (3F2F)
*
70.5 50.6 60.8 59.7 59.6 59.8 77.9 55.9 62.6 70.9 52.0 61.6 71.8 50.7 61.5 62.5 52.8 57.8 80.4 52.8 61.1 74.9 58.2 66.8 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0Overall Mean Scores (by Schools)
Before (6F2F) AJer (3F2F)
*
*
* *
*
*
* * *
*
Significant decrease
p=0.05 (Level of Significance)
Overall Mean Scores (By Schools)
Overall Score
p-‐Value
Remark
OCAS
0.000
Significant
OES
0.085
Not Significant
FRS
0.110
Not Significant
58.9 61.0 67.4 60.1 61.9 54.2 64.9 63.5 58.1 59.3 67.7 65.6 59.8 60.8 72.2 56.8 63.8 58.6 62.1 55.8 65.4 67.6 65.1 60.8 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Mean Final Rank Scores
Before (6F2F) AJer (3F2F)
*
*
*
*
*
71.1 70.3 68.5 59.2 61.8 58.0 81.4 79.2 71.4 71.5 67.9 71.9 69.2 74.4 75.6 61.8 67.7 62.5 77.5 75.3 85.6 75.6 73.1 69.7 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0Mean OCAS Scores
*
*
*
*
*
*Significant increase
*
Significant decrease
46.2 51.2 65.7 60.7 59.4 50.3 57.9 56.6 52.4 46.8 67.4 59.7 50.0 46.9 68.3 51.5 59.8 54.4 55.4 47.2 56.8 59.0 56.9 51.1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
