Reading notes: Statistics 101 (Part 1)

Learning from Andy Field, on my daily travelling between Jurong East MRT Station and Expo MRT Station

Overview
From an initial observation, explanations, or theories are generated for those observations, from which predictions (hypotheses) can be made. This is where the data come into the process because to test those predictions data are needed.
- First, collect some relevant data (i.e. identify things that can be measured) and then analyse those data.
- The analysis of the data may support the theory or give the cause to modify the theory.
- As such, the processes of data collection and analysis and generating theories are intrinsically linked: theories lead to data collection/analysis and data collection/analysis informs theories.

In the process of generating theories and hypotheses, data are important for testing hypotheses or deciding between competing theories. In essence, two things need to be decided: (1) what to measure, and (2) how to measure it.

To test hypotheses we need to measure variables.
Variables are just things that can change (or vary); they might vary between people (e.g., IQ, behaviour) or locations (e.g., unemployment) or even time (e.g., mood, profit, number of cancerous cells).

The key to testing scientific statements is to measure a proposed cause (the independent variable) and a proposed outcome (the dependent variable).

Independent variable: A variable thought to be the cause of some effect. This term is usually used in experimental research to denote a variable that the experimenter has manipulated.
== Predictor variable: A variable thought to predict an outcome variable. This is basically another term for independent variable .

Dependent variable: A variable thought to be affected by changes in an independent variable. You can think of this variable as an outcome.
==Outcome variable: A variable thought to change as a function of changes in a predictor variable; aka dependent variable.

Levels of measurement
Variables can be split into categorical and continuous, and within these types there are different levels of measurement:
1. Categorical (entities are divided into distinct categories):
1.1 Binary variable: There are only two categories (e.g., dead or alive).
1.2 Nominal variable: There are more than two categories (e.g., whether someone is an omnivore, vegetarian, vegan, or fruitarian).
1.3 Ordinal variable: The same as a nominal variable but the categories have a logical order (e.g., whether people got a fail, a pass, a merit or a distinction in their exam).

2. Continuous (entities get a distinct score):
2.1 Interval variable: Equal intervals on the variable represent equal differences in the property being measured (e.g., the difference between 6 and 8 is equivalent to the difference between 13 and 15).
2.2 Ratio variable: The same as an interval variable, but the ratios of scores on the scale must also make sense (e.g., a score of 16 on an anxiety scale means that the person is, in reality, twice as anxious as someone scoring 8).

Two measurement-related issues
1. Standard units of measurement
2. Difference in results between studies.

One way to try to ensure that measurement error is kept to a minimum is to determine properties of the measure (validity and reliability) that give us confidence that it is doing its job properly.
Validity: whether an instrument actually measures what it sets out to measure. Reliability: whether an instrument can be interpreted consistently across different situations.

Criterion validity: whether an instrument measures what it claims to measure through comparison to objective criteria.
- In an ideal world, you assess this by relating scores on your measure to real-world observations.

== Concurrent validity: a form of criterion validity where there is evidence that scores from an instrument correspond to concurrently recorded external measures conceptually related to the measured construct.

== Predictive validity: a form of criterion validity where there is evidence that scores from an instrument predict external measures (recorded at a different point in time) conceptually related to the measured construct.

- Assessing criterion validity (whether concurrently or predictively) is often impractical because objective criteria that can be measured easily may not exist.
- With attitudes it might be the person’s perception of reality rather than reality itself that you’re interested in.

Content validity: evidence that the content of a test corresponds to the content of the construct it was designed to cover.

Validity is a necessary but not sufficient condition of a measure.
A second consideration is reliability, which is the ability of the measure to produce the same results under the same conditions.
To be valid the instrument must first be reliable.
The easiest way to assess reliability is to test the same group of people twice: a reliable instrument will produce similar scores at both points in time (test–retest reliability).
Sometimes, however, you will want to measure something that does vary over time.

Experiences of applying for IRB

In my PhD, Warwick University had established a rigorous process and standard for ethical approval in educational studies. So applying for the approval is a norm and nobody thinks it as a burden.

However, when I returned to Malaysia where IRB application was not there, I tried to retain the practice and attitude for ethics in education research.

Now when I am working in SUTD, I found academics and staff are scared by the tedious process and revision needed in applying IRB. The process in Singapore institutions is indeed more complicated. And people who don't see the benefits of doing it felt frustrated with the process and rejection.

This prompted the thought of challenges faced if UPSI is going to impose IRB. We need a dedicated and strict team to implement this.

Talk by the VC of Cambridge University

Title: Universities and Their Role in an Era of Global Challenges

Delivered by Professor Sir Leszek Borysiewicz FRS, FMedSci, the Vice Chancellor of Cambridge University

Organiser: Jeffrey Cheah Distinguished Speakers Series (JCDSS) Sunway University

The role of universities in an era of global challenges, an era where expertise itself is fall into question. 

What does it is actually mean in this day of age to be a world-class university?

League tables are too simplistic...it does not show the depth of any academic institution has to deliver. 

A university is global when it reflects global diversity, addresses global issues; when it establishes global partnership; and when it assumes global leadership. 

The diversity is the key.

Cambridge is suffering in offering courses via MOOC to cope with the global change.

Cambridge is facing immense challenges in replicating the colleagial ambience in physical unversity outside of Cambridge.

"We are global because we address global issues."
... Looking for practical solutions to issues we face.

It has to become the daily work of academics.

World class university must harness... collaboration.

Strategic partnership
Collaboration network
Retain collaboration at all costs.

Global leadership requires courage, creativity and cooperation.

Global diversity addressing global issues...

Failure to address these issues would leave universities out.

Trust gap between the uninformed  and the academic experts is alarming.

When expert is now a term of abuse.

It's damaging to our reputation...

We need the experts
Let's continue
Engage the wider society
Stand up and be heard
Strike to be more transparent...
Make no apology for it at all.
Keep doing what we can do best.
Doing so will not make us popular

Be sincere.

To contribute to the society ...
If we do not serve the society, the global society,

It is the yardstick....

How to develop a framework

One way of developing framework: come out with a framework without obvious methodogic approach. For example, Prof Dr Badrul Huda Khan said his E-learning Framework was not based or grounded on any research, instead from listening and understanding the needs of students.
The framework becomes highly recommended and recognized, and then he wrote books about the model.

Another way of developing a model or framework is like doing the process-based design of NRGS Programme led by UPSI.

To me and my postgraduate students, herewith what I suggest for developing a  framework:
1. Review literature on issues and key concepts associated that may form a framework.
2. Develop provisional guiding principles for ideal practice.
3. Structure a provisional framework based on provisional guiding principles.
4. Define all key concepts used in the provisional framework.
5. Design and develop instrument(s) to validate the framework.
6. Validate the instrument(s)
7. Validate the framework through empirical studies using the validated instrument(s)

Notes taken from "Meaningful E-Learning in Education"

Learning is the main thing. "E" is the technology, the sidekick not the main thing.

"I cannot live without sarung...
I bring the flavor of Bangla to America."
"Thinking globally, acting locally."

I asked, "What is non-meaningful e-learning?"
Non-meaningful e-learning means students do not get what suppose to get from learning.

New book: Data Analytics in Education

Agenda:
1. People Process Product Continuum.
2. Stakeholders' needs
3. E-learning framework

"E-learning is an instructional model that allows instructor, students, and content to be located in different noncentralized locations so that instruction and learning occur independent of time and place."

"E-learning is distributed".

"I am not the technology guy, I am just the messager."

"Tools here are going to jeopardy your life, you have to decide whether the tools are supplementing or empowering you or not."

Instructional designer is like an architect, who will come out with the blueprint of instruction.

A high quality e-learning system must be meaningful to stakeholders. It is more likely to be meaningful to learners when it is:
- easily accessible
- clearly organized
- well written
- authoritatively presented (it is something educational)
- learner-centered
- affordable
- efficient
- flexible, and has a
- facilitated learning environment.

"Maybe some of them aren't even ready for the lecture."

A Thai student asked, "Is University going to stay?"

"When passion becomes profession, life is no longer boring."

Try to make your profession your passion, then you enjoy what you are doing.

Don't do e-learning unless you are ready.

When learners display a high level of participation and success in meeting courses goals...

When learners enjoy all available support services provided in the course without any interruptions, it makes support services staff happy as...

Finally, e-learning is meaningful to an organization when it has a sound  ROI, a moderate to high level of learners' satisfaction...

Today, I would like to introduce a framework which I believe will help us identify important criteria for quality e-learning and blended learning.

Framework of E-learning
http://bookstoread.com/framework/scroller.htm

Learning arts systematically? How I survived back then.

When I entred MMU in 1999, I chose a wrong programme.
However, I took the challenge to rectify my mistake, as an appreciation of getting PTPTN from the government and as an opportunity to obtain a Bachelor degree.

The first problem I faced when choosing a wrong programme was the need to master drawing skills. To be honest, drawing was not my cup of tea at that moment, and I did not have interest to learn drawing. However, for the sake of survival, I treated drawing as a professional work systematically.

I established a systematic learning sequence for arts: definition, incubation, illumination and verification.

Step 1: Definition
Before entering a class, I do pre-lesson learning by clarifying meanings of all jargons used in the lesson. I believed I need to know exactly what I need to do when I was given instructions to draw something. Thanks to internet, I managed to get definitions of all art movement, e.g. pointillism, expressionism, realism, photo-realism, Art Nouveau, Art Deco, etc. I also made to best of the visit to National Art Gallery (now National Visual Arts Gallery) in KL. I kept asking questions in the class, and seeking for meanings of particular art movement and style in MMU Library.
With sufficient knowledge and understanding on what jargon actually means, I could at least talk about arts--without a mastery of creating them.

Step 2: Incubation
To produce quality drawing requires incubation time. This would be the time spent to establish the ambience for inspiration and generation of ideas. Preparation to draw, like setting up the canvas, mixing colours, washing brushes, sharpening pencils or charcoal, etc, can be regarded as incubation as well. I also built up a habit to listen to New Age music during this period of my life. I particularly like Enya's music.

Step 3: Illumination
I started drawing by sketching what I had in mind without worrying the beauty of the sketches of work or not. After multiple attempts, I would proceed to the illumination stage, when I began to fill in colours, lighting, and life into the sketches. Static drawing or sketches turned animated in my mind. I began to think and express what I thought through illumination on the drawing.

Step 4: Verification
After getting a few versions of drawing done, I spent time framing them accurately according to the specifications set by lecturers. Then I brought all the framed works to the faculty and got hold of my lecturers to comment on and verify their quality. The chosen or preferred version would be considered as verified version. I moved on to finalise this verified version, adding values to the work and submit on the due date.

-----------------

Learning and re-learning drawing in MMU in 1999 and 2000 was indeed a painful experience in my life. However, during those years, I tried convincing myself: even if I cannot draw now, but I can learn to draw! And I realised most of my course mates also cannot draw like me. Those who actually can draw, among my peers, I can actually count by hand. I did think of changing faculty, to IT or Management, but that would lead to two problems:

a) financial problem: I already spent money buying drawing materials, tools, etc. The study loan was approved and changing programme would lead to chaotic situations, and I did not actually have money to repay fee in the new programme.

b) curriculum: I was not scoring very well in physics, add maths, etc, and I might not be able to score flying colours in IT or science-oriented programmes.

So to master drawing, I thought of following the footstep of Leonardo Da Vinci, get a Master and learn from him persistently until I succeed. To cover the weakness of drawing, I will work harder on non-drawing subject matters, hoping that I could score in those subjects to compensate. I managed to establish good discipline, i.e. spending most time learning and practice instead of going out the campus, like my peers did.

In fact, I was reaching the end of the journey, it would not be worthwhile to give up at that moment.

Setting the functions of workspace

After resuming non-admin working life, I started to sort out things I planned years ago. One of them was to re-establishing a conducive work space in UPSI.

When I was the Director of UERL, I split my working life into two--one in the admin office at the Sultan Azlan Shah Campus, another in FSKIK. Now, I finally managed to merge them into one. Also, after becoming a father, my work space at home turned chaos because I have to reset the positions of most of my stuff to avoid being ruined by Thales or being hidden somewhere in the house. 

To sort out things for a conducive workspace, I would start tagging all materials in the office according to their functions:

1. Research and Development (R&D)

1.1. Universiti Research Projects

1.2 MyGrants 

1.3 External grants

2. Publication

2.1 Book & Book Chapters

2.2 Journal article & journal management

2.3 Conference papers 

2.4 Commission writing project

2.5 News Articles 

3. Supervision of students

3.1 Postgraduate student supervision

3.2 Undergraduate student supervision

3.3 Intern supervision

4. Teaching

4.1 Undergraduate teaching

4.2 Diploma teaching 

4.3 Exam papers 

5. Consultation

5.1 Paid consultation projects

5.2 Pro bono projects

6. Community Service

6.1 Civil Defence 

6.2 Martial Arts 

6.3 Volunteerism 

7. Administration 

7.1 Academic Qualifications & Professional Affiliation 

7.2 Meeting records, letters, memos