This presentation is prepared as a brief summary for my final thesis viva in the University of Southampton. It also contains slides about self-evaluation of my PhD journey
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PhDchat: brief summary of my thesis and thoughts about my PhD journey
1. +Viva for the PhD
thesis titled: Prediction
of Course Completion
based on Participants’
Social Engagement on
a Social-Constructivist
MOOC Platform
Ayse Saliha Sunar
28 June 2017
Examiners:
Dr. Dave Millard
Professor Eileen Scanlon
Supervisors:
Dr. Su White
Professor Hugh C. Davis
2. +
Educational Background
Bachelor: Mathematics at Gazi University, Turkey
Master: Information Science at Nagoya University, Japan
Research theme: Intelligent Tutoring System
Adaptive content presentation based on the level of learners
Small-scale system
MAGIC
input:
TEXT
output:
MULTIPLE-
CHOICE
CLOZE
QUESTIONS
MAGIC
input:
TEXT
output: ADAPTIVE
PRESENTATION OF
MULTIPLE-CHOICE
CLOZE QUESTIONS
Adaptive
Model
Available system My contribution
3. +
Researching on MOOCs
PhD: Learning analytics in large-scale data
MOOCs
Pedagogy
Assessments
Stakeholders
Social
learning
through
social
features
Learning
materials
Feedback
4. +
Researching on MOOCs II
First intention: Developing a friend recommendation system
based on participants’ social engagement
Cancelled because FutureLearn did not allow us to use an external
tool due to security concerns
Research project revised: Investigating participants’ social
engagement with the course and predicting course completion
based on social engagement
Hypothesis: The data extracted from participants’ engagement in a
MOOC can be used to identify social behaviour patterns of participants
and this information can contribute to a model of course completion.
5. +
Methodological Phases in my PhD
Descriptive
Statistical
Analysis
• Participants’ contribution to online discussions
• Use of the follow feature, which is one of the unique social feature on the platform
• Relation between learners’ social presence and their performance on course
completion
Inferential
Statistical
Analysis
• The sequence of social behaviours of participants, which are defined with the aid of
characterised use of social affordances on the platform
• Correlation analyses on course completion and behaviour chains
Testing
Prediction
Models
• Prediction of MOOC participants’ course completion performance by using the
pattern of their social engagement in the course
• Random Forest Model and Support Vector Machine
6. +
Contributions of my PhD
MOOC learners who participated socially are more likely to
complete the course than others.
Some social features on the platform are actually a good
indicator for learners’ patterns of engagement.
Sequence of learners’ social behaviours can be modelled as
behaviour chains.
This social behaviour modelling is valuable since it identifies
which components of social behaviours might be the best
discriminators for predicting learners’ future behaviours.
A prediction model of course completion has been developed
by using behaviour chains.
The model performed well especially in classifying learners as
“to be in low or high completion”.
8. +
Best things I have learnt
How to individually conduct studies
How to effectively use resources on a particular study
How to gain my academic networks
How to constructively criticise other research
Time and task management
Academic writing
9. +
Difficulties during the study
Lack of some data
No data regarding to like on the platform
More accurately gathered follow data
Issue on FutureLearn’s authorisation on third party
involvements on the platform
Was informed one week before the transfer viva (at the 24th month
of the PhD)
Had to do major changes in the study
Machine Learning
Hard to learn in the beginning compare to any other new subjects
that I have learnt during the study
10. +
After the PhD
Soon:
More publication
Behaviour chains and prediction models
Soon:
Continue to collaboration with Yildiz Technical University on second
language MOOC participants
In 6 months:
Start the work in a university in Turkey
As a lecturer at the department of
Computer Engineering
Seek for new collaboration opportunities on MOOCS in the context of
education in Turkey
Karabuk Bitlis
11. +
What would I have changed if I had
a chance to do this PhD again?
Do more brain storming with other fellow learners
I did it when I really struggled with a problem.
If I had more data on learners’ social interactions on the
platform such as likes and if learners actually read the
comments, it could provide insight to learners behaviours.