Research Project III

Course CodeBGN202
Fee CodeS3
Duration (approx)100 hours
QualificationStatement of Attainment
Being a good researcher involves more than coming up with brilliant ideas and implementing them.

Most researchers spend the majority of their time reading papers, discussing ideas with colleagues, writing and revising papers, staring blankly into space – and, of course, having brilliant ideas and implementing them.

Lesson Structure

There are 5 lessons in this course:

  1. Determining Research Priorities.
    • Beginning your research
    • Brainstorming
    • How to brainstorm
    • Basic steps for brainstorming
    • Terminology
  2. Planning Research Improvement
    • Overview
    • Mind maps
    • How to mind map
    • Concept mapping
    • Flow diagrams
    • Analytical procedures
    • Terminology
  3. Testing the Viability of Alternative Approaches
    • Research design
    • Major types of research design
    • Action research
    • Fishbone diagrams
    • Lateral thinking
    • Lateral thinking techniques
    • Pareto analysis
    • When and where to use pareto analysis
    • Observations
    • Root cause analysis
    • Finding the root cause
    • Hypothesis
    • Null and alternate hypothesis
    • Terminology
  4. Conducting Detailed Research into Commercial Work Procedures
    • Log books
    • Collecting and logging data
    • Checking data for accuracy
    • Developing a base structure
    • Data transformations
    • Analysing your data
    • What shape is data in
    • Analyzing documents
    • Analyzing interviews
    • Analyzing observations
    • Analyzing questionnaires
    • Interpretation
    • The results
    • Writing up your report
    • Report structure
    • Terminology
  5. Developing an Improved Approach to a Workplace Procedure
    • Overview
    • Terminology


  • Analyse current industry procedures to determine possible areas for improvement or innovation.
  • Plan research on the development of innovative approaches for improving a commercial work procedure.

What You Will Do

  • Often the hardest part of research is coming up with a research topic or question. Your research topic should first of all be interesting to you and relevant to the field of study/work you are in – you'll be spending a lot of time and work on your project so be sure to choose a topic that you are eager to learn more about.


Identifying the subject matter of your research is a good start, but your topic will not be truly focused until you have rephrased it as a research problem or hypothesis.

The quest for an answer to your research problem (or validation of your hypothesis) then becomes what drives your research forward.

One way to focus in on your research problem is to consider the overall purpose of your project. Are you setting out to define, classify, compare, analyse or prove a point? Whatever you are doing though, you will be attempting to gather data, then process that data.

Data Preparation involves checking or logging the data in; checking the data for accuracy; entering the data into the computer; transforming the data; and developing and documenting a database structure that integrates the various measures.
In any research project you may have data coming from a number of different sources at different times.  For example:

  • mail surveys
  • coded interview data
  • pre-test or post-test data
  • observational data

In all but the simplest of studies, you need to set up a procedure for logging the information and keeping track of it until you are ready to do a comprehensive data analysis. 


Checking Data for Accuracy

As soon as data is received you should screen it for accuracy. In some circumstances doing this right away will allow you to go back to the sample to clarify any problems or errors. There are several questions you should ask as part of this initial data screening: 

  • Are the responses legible/readable?
  • Are all important questions answered?
  • Are the responses complete?
  • Is all relevant contextual information included (e.g., data, time, place, researcher

In most social research, quality of measurement is a major issue.  Assuring that the data collection process does not contribute inaccuracies will help assure the overall quality of subsequent analyses.