Tuesday, August 20, 2013

EFFECTIVE RESEARCH PROPOSALS


Effective Research Proposals


What is an effective research proposal?  It is a proposal that (1) gets accepted and (2) is a useful guide for conducting your study after it is accepted.  The basic steps of an effective proposal are almost always the same whether the proposal is for a grant application, a doctoral dissertation, or an evaluation of a project.  And, the criteria for effectiveness are virtually identical whether it is called a plan, design, or proposal.  The basic outlines of the are very similar.

In virtually all cases, it is much better to have a detailed plan, which you have to revise as you go along, than to start a research project with only a vague idea of what you are going to do.  Your time is too valuable to waste in aimless wandering.

There are 7 basic components or steps of a good research proposal.  I have listed those steps in a logical order below.  And, this is the order you would probably use to outline your proposal--and to communicate the results of your research.  But in the actual practice of conducting your research, you might need to revisit earlier steps, often more than once.  For example, when something goes wrong in the sampling plan (step 4) a way to get ideas for fixing it is to re-review previous research (step 2) to see how other investigators have dealt with your problem.

1.  A research question. 
2.  A review of previous research. 
3.  A plan for collecting data/evidence.
4.  A sampling and/or recruiting plan 
5.  A research ethics plan. 
6.  A coding and/or measurement plan.
7.  An analysis and interpretation plan


1.  A research question.  A good research question has to be researchable, meaning you could conceivably answer it with research.  Considerable explanation about why it is a good research question—it’s researchable and it’s important—is needed in an effective research proposal. 

2. A review of previous research.  This helps you avoid reinventing the wheel, or even worse, the flat tire.  A review is also a source of many ideas about the subsequent stages of the proposal: on how to collect data, from whom to collect it, the ethical implications of your data collection plan, and finally approaches to coding and analysis. 

3.  A plan for collecting data/evidence.  There are 6 basic ways to collect data: (1) surveying, (2) interviewing, (3) experimenting, (4) observing in natural settings, (5) collecting archival/secondary data, and (6) combining ways (1) through (5) in various ways.  You also need to explain why your choice of a data collection plan is a good one for answering your research question and, implicitly, why one of the others would not be better.

4.  Sampling and/or recruiting plan.  This describes from whom, how, where, and how much evidence you are going to collect.  In other terms:  Who or what are you going to study?  How many of them?  How much data from each of them? How will they be selected?

5.  A plan for conducting research ethically.  This plan tries to anticipate any ethical problems and prepares for how to deal with them.  Once you know what you will gather, how, and from whom, then before you go ahead, you need to review your plan to see if there are any ethical constraints arising from participants’ privacy and consent and potential harms.  At this stage, your plan includes preparing for IRB review.

6.  Coding.  Coding is assigning labels (words, numbers, or other symbols) to your data so that you can define, index, and sort your evidence.  It is in coding phase that the issues of distinctions of quant/qual/mixed become most prominent.  You may have made this coding decision in mind early on—perhaps you are phobic about numbers, or maybe you find verbal data annoyingly vague.  You may actually start with this as your first divider, but it would not be effective to write your proposal that way—by saying, for example:  “I like to interview people and numbers give me the creeps, so I don’t want to do survey research” or “I’m shy and I don’t want to have to interact in face-to-face interviews, so I want to do secondary analysis of data.”


7.  Analysis and interpretation.  This tends to be the skimpiest part of a research proposal.  But if you know what you are going to collect from whom and how you will code it, your first 6 steps really do shape (not completely determine) the analysis options open to you.  

5 comments:

  1. The analysis of quantitative data is perfect to implications of your data collection plan, and finally approaches to coding and analysis.

    ReplyDelete
  2. Thank you for your nice comment. I'd be interested in any further ideas you might have.
    Paul

    ReplyDelete
  3. Quantitative data depicts the quality and can be scrutinized, but measuring it precisely is daunting enough; in contrast quantitative data can be easily measured and is depicted in number or amount. See more analysis of qualitative data

    ReplyDelete
  4. Article is very different in the topic points and the way of writing.Keep updating more articles.

    BIGDATA Training in Chennai

    ReplyDelete