Data Analysis (to be updated)

The choice of data analysis methods must refer back to your research questions. 

Common approaches:

1. Statistical Analysis - for numeric evidence as support 
2. Interpretation of interview transcripts - using texts (e.g. interpretation of interview transcripts).
3. Mean - for continuous data (e.g. score in the competition). The initial tests are carried out to compare different groups of participants, to see where there is a significant differences (in terms of score) between them or not before the competition. 
4. Chi square test - to see whether specific samples drawn from a population can represent the whole population or not.
5. SPSS is just a software to speed up calculation.

Mixed Mode Research Design

 Before selecting mode of research design, a researcher ought to consider:
◆ Provide a rationale for the design
◆ Include collecting quantitative and qualitative data
◆ Consider priority
◆ Consider sequence
◆ Match the data analysis to a design
◆ Diagram the procedures

6 types of Mixed Mode Research Design by Cresswell (2011)

◆ the convergent parallel design

• Data collection run simultaneously  
• Offset the weakness of other data collection
• Quantitative (Quan) & Qualitative (Qual) data are almost equal score

 
◆ the explanatory sequential design

•  Quan is done first then Qual to explain/refine the Qual results

◆ the exploratory sequential design

• Qual is done first then Quan to explain/refine the Qual result
• Focusing on Qual studies

◆ the embedded design

• Quan & Quak are doing at the same time,
• Use secondary data to understand the reasons for the correlational results

◆ the transformative design

• Use either one of the above design
• Usually request for a change

◆ the multiphase design

• Use either one of the above design
• Used in projects addressing larger program objectives. 

Feedback 2 on Writing a Paper - Introduction

 To start off with a research paper, I was guided with some FAQ:

Introduction:

1. Should be an overview of the paper or report, instead of the event. Normally it starts with " This paper aims to... " 
2. How you analyze data should be under Methods or Methodology.
3. If an event were studied and published in the past, put it in LR. Else write it in a dedicated section. 
4. What's the origin of the Topic? who did what research and what are the findings? Do you agree or disagree with the findings? Why?
5. Add in Methodology. How did you collect data? Why use questionnaire and follow up interview? Sampling method. (insert demographic profile of respondents here). Data analysis methods.

Feeback 1 on Writing a Paper - Common mistakes

 In order to mention "Evaluation", or "learning", I was advised to follow Kirkpatrick's 4 levels of evaluation

1. Level of learner satisfaction 

- use questionnaire survey to check whether learners are happy with the learning events or not

2. Level of knowledge / skill acquisition 

- use quiz or test to check whether learners have achieved the intended learning outcomes or not

3. Level of application of new knowledge / skills 

- use observation checklist to check whether learners have applied what they have acquired in other contexts

4. Level of ROI 

- use balance sheet to measure total cost spent on competition plus research expenses and compare it with the return on investment to see whether it is economical to teach cyber security through competition or not. 

Case Studies
Case studies should follow the protocol proposed by Robert Yin (2009)

Writing Style
Try to avoid showing short form in the title.

New Start week of 25th August

Normal Routine: Study, research and collecting info from other PhD students & researchers. A little blinded with rushing here and there. Time to reset and start again.

• Submitted my application for PhD. checked √.
• Finished up markings. checked √. Incoming for both universities (28/8) - 60 scripts & (26/8) 7 assignments.
• Clear up the study loan. RM1500 left (Cleared by 31st August)
• Financial Planning. EFP. checked √. But found June was not updated (it's already August).

Received email from potential PhD supervisor in 2 days time (he is fast). Notes taken:

√ Clarify of elaboration
√ Issues identified

× Scope is still general - need further scale down for 3 years studies.
    - find similar researches
    - analyse the gap - to see if research is feasible
 × Research methodology is needed. Keyword: Research Design.

Hope for the best for my PhD enrollment. A long way to go. 3 years = 12 months = 52 weeks = 365 days = 8750 hours = 525600 minutes.

Day 6

Applying my knowledge

Quite fun but just spent my night doing that.

Day 5

Expect the unexpected

Practice 1st day's lesson: Financial aware

3 years of investment and risk. There is no turning back. However, doing $ part time almost = $ working full time. Good: earn more with less days; Bad: Inconsistent classes (income). I'll still do it. Due date: Beginning of Oct (before 15 Dec)

Received a call while doing this in the morning, a little excited but the guilt is still felt in my heart. However, let's face it. & Received this:

Oo.. some how related to my 30 day challenge.

Did it just right after work. A lot hard work need to be put in (just to catch up). Might change after time, but let's put things into action and fix myself right first.