Research Methods

Someone just reminded me that its examination season in UK Universities and Colleges so I though I might post some tips (although the best way to deal with examinations is to prepare well for them). However, here are some ideas that you might use if in the beginning, middle or end of an exam you get stuck. It has been suggested there are ONLY five basic ways in which one solves problems. Here they are, but don't forget, you can use all of them not just one.

Trial and Error the process is akin to guessing, so take a chance and see what pops into your mind, it might just get you started.

Divide and Conquer in simple terms break a large problem into smaller and therefore simpler problems. You can also say here simplify, so if you cannot do what is being asked, simplify it and if you can do the simpler problem that might give you an idea how to solve the larger problem

Generic Solutions concentrates on ideas associated with previous experience, ask have I seen ANYTHING like this before. This is almost always the most productive mechanism.

Different View Points the point is, that solutions may come if we change our viewpoint so that we see the same problem in another light or from another perspective.

Look for Relationships requires that we consider how elements affect and are affected by other elements. So look for links between things in the question and see if that helps you through

Finally, in New Scientist 9 May 2009 there is an article called "Spark of Genius" and another 8 Nov 2008 called "Vacant Mind, busy brain" and they are both about thinking and how the brain works. Two things I might say here:

The brain uses 2 to 3 times more energy when you are day-dreaming, letting your mind wander, when you are not thinking about anything in particular. The implications of this is that if you get really stuck it might helpful to just stop and day-dream, let your mind wander (BUT not too long though!!) and let you brain sort things out.

One odd bit of research from the University of British Columbia is on colour, it appears that if one looks at blue things for some unknown reason the brain seem to work better, more creatively. So if you get stuck, day-dream by looking at the sky or a blue shirt or indeed anything blue (BUT only for a minute or two)

Here are a possible set of headings for use in a degree level project or dissertation covering chapter 1. In this case they might be most useful in a technology subject area but it would be easy to modify them to suit other subject areas.

Chapter 1 – largely about scene setting and outlining the basic research elements, thus all the following must be covered although you do not have to use these sub-headings

1.1 Introduction with problem setting and client
1.2 Presenting problem definition, its causes and reason resolution
1.3 Target or the effects that would be observable if your project outcome
is used
1.4 Research Approach and Style
1.5 Overview of Primary and secondary Data
1.6 Planned Outcome and Actors
1.7 Demonstrate that the outcome is/will lead to a solution when used
1.8 Scope (what aspect is covered) and Scale (how many firms, people etc are involved
1.9 Ethical Overview
1.10 Research Question with features: interrogative, outcome, actor, problem, spotlight, activity and target
1.11 Aim with features: activity, outcome, spotlight and target
1.12 Objectives with features: activity, spotlight, milestone (visible features) plus bounded and progressive (non-visible features)
1.13 Summary and link to next chapter

For item 1.8 you are trying to set limits on what you will do and hence limits on the applicability of the outcome so this needs careful thought. For example, I might set the scope as looking at eMarketing effectiveness and my scale is to do it with three different companies. If you wish you can add in this section a brief note on the methods you might use to show they are appropriate within your chosen scope and scale. Some definitions not covered above.

Research Approach means selecting and the use of justifying induction or deduction.
Research Style means selecting and justifying qualitative or quantitative (but don't be fooled into thinking these just mean the same as data types)
Outcome means what you produce after using you data (a model, a report etc)
Actors are the people who will USE your outcome in some way.
Interrogative: most questions that ask for something start with a word like "what", "in what way" and these starting words are called interrogatives.
Spotlight means telling us in a focused manner what your primary data is
Activity means what will you actually do to identify and extract the data
Milestone is a minor outcome generated during the project
Bounded means that an activity must be completed within the project time scale

If you need further clarification or example please be specific and ask for what you need

I just noticed in other threads that a few were asking about data processing, what to do when they get primary data. So I thought I might add a few posts on this issues because it is potentially a difficult thing to do convincingly - and you will have to convince your examiners that the way you decided to process that data was sensible and reliable. But today I will just give an analogy of the whole process.

Processing Primary Data
When thinking about your primary data, keep in mind that its is what you will uses as the basis for generating your project outcome. It follows that if you say your outcome is a strategy, or a model, or a position paper then it only makes sense if you know what primary data you want and a way to combine them (called pre and post processing) so that you can manufacture that particular outcome. Suppose by way of analogy, one was making a wedding cake (analogous to your project outcome). Essentially any recipe (analogous to a research design) is in 3 parts: ingredients, quantities and making process.

Ingredients (analogous to defining and locating the primary data) - We define the ingredients we need, make a list of them and then locate a shop that sells the ingredients.

Quantities (analogous to collecting the data) - We use our ingredient list and add quantities and go get them. But of course as we collect them they will not automatically be in the right quantities and forms. Therefore at the end of this we will have bags of currents, icing sugar, flour, nuts and so on but obviously in this state we cannot use them directly to get the outcome.

Making (analogous to pre-processing and post processing to finally generate the outcome) - Pre-process the ingredients by measuring out the various ingredients and put the correct amounts into individual bowls ready for the final stage. We use the last part of the recipe to take the bowls (analogous to our structured cMaking (analogous to pre-processing and post processing to finally generate the outcome)ollection of data) and combined them correctly and then bake the cake which is our final outcome.

Implicit in this is that the levels of skill needed becomes higher and higher the closer you get to generating the outcome. Summarising: if I were making a cake (outcome) then I assemble the ingredients (the data) but I also need secondary information/data and skills: a recipe to tell me what to do, instructions on how to use the kitchen gadgets, how to set the timer, how to check cooking progress, how to manage costs, how to serve it up, definition of terms, I might watch a cooking program on TV and so on but no one would think of these extra things as ingredients (primary data) would they. By analogy this is saying you need literature support to do the work which you can use to help you know what to do and help you find meaning in your results.

On the website shown belowis a table of common data collection methods but be aware that it’s all too easy to assume you know them because they sound familiar. It is therefore essential to study the one you think is best for you and make sure you know its structure and usage patterns. It is prudent to try these out for yourself in some simulated situation. I have attached it as I don't know if a table can be inserted into a post directly. I hope you find it useful

Data Collection Elements Within every project there has to be a collection protocol for the practical collection of the primary data. Every complete protocol will several features:

1. Vehicle – this is the primary mechanism or technique employed by the researcher, typical examples are: interview, questionnaire, observation, role playing, seminar, focus groups, document searching and so on
   
2. Recording Profile – this describes how the data will be physically recorded. Typically we might use: written report/transcripts, formatted record sheets, video, sound recording, computer logging, excerpts from documents and so on.
   
3. Sample criteria – this is a profile that allows the researcher to know that he/she has a valid sample point from which data is to be collected. For example, if we wanted data on business uses of Digital Paper we need a profile of who we should ask for that information. If we do not have a profile we may not have any consistency in our data and it may therefore be meaningless.
   
4. Localisation – it goes hand in hand with knowing what the data is in knowing where the data is.
   
5. Permission – you have to feel certain that the information you seek is legitimately available to you.
   
6. Ethical Profile – you need to be clear as to what you are doing, the way you are doing it and what you are asking for is ethically acceptable. Two things are at stake: the results may be biased and the results may not be acceptable in the sense that they cannot be ethically used.
   
7. Model or Simulate - strictly this is NOT a step that one records anywhere but its acts as a check on your Spotlight and Activity. So I recommend that you invent some data just to see that what you have said makes sense and you can write it down. So I could, for example invent a few job profiles for people who work in IT support services and by that means I can feel confident I know what I am looking for as data.

http://sites.google.com/site/researc...ection-methods

PS In the above website list several data collection methods are mentioned and if you need clarification then please let me know which one and I will post a note.

Modes of Persuasion
Here are eight suggested modes of persuasion where you can use just one or more than one but they will be of no value unless you know what your main premises area with clarity. You may find some of these ideas really useful in coursework or exams and of course in life generally we are more or less continually engaged persuasion.

1. Mimic the mannerisms if the ones being persuaded.
   
2. Framing or leading people to think about an issues or opinion in a way that is advantages to you. Instead of saying inheritance tax say its death tax if you oppose it etc.
   
3. Less is more - don’t give too many reasons in favour as it can harden opinion against you. There is good evidence that working hard on just two reasons to support your arguments is optimal
   
4. Grind them down – nagging, keep at it but with reason not brute force.
   
5. The medium is the means, always consider what to use in you argument; slides, written, spoken etc
   
6. Style over substance - don’t hesitate or stumble or give them time to think
   
7. Get them angry and feel a sense of injustice so justifying your ideas
   
8. Resistance is not futile – move toward a target bit by bit

Now you know these you can use them and also of course you can be aware of them in others. There are some things you should not do: don’t insult or denigrate, don’t accuse of unethical motives, don’t say they lack knowledge, don’t say they are uneducated, don’t call them names, don’t say they are lying etc. Strategies like these will always look as if you are attacking the person not the arguments so we must always act with integrity and honesty, get you facts and premises right and stick to it.

This is a KEY element in your design since it is obvious that if you cannot explain how to generate your outcome (or you can say result) from your chosen data then your whole project must fail. Assessors will assume you chose your outcome thoughtfully with careful consideration of what primary data was needed. Therefore, if you then cannot explain how to use the data there will be serious questions about your competence in choosing your outcome and data. There are two stages

Pre-Processing Plan - primary data may be recorded in many different forms: transcripts, notes, recordings, videos and so on. It follows that the data is not at this stage expressed as an entity", some useful and organised form. One must therefore define a transformation from the raw data (the form in which it was collected) into a structured and organised form. For example, if your data was collected on 100 questionnaire forms then obviously that is not a suitable way to use that data to generate the outcome. The actual processing plan will be based on how the data was recorded and the kind of outcome planned, but in general one would take your raw data and: summarise into a table, catalogue or other useful form, check for completeness, check classification (the data is all valid), test data for reliability, decide what statistics or other qualitative processing could be used, decide how the data is to be displayed (charts, tables etc) and so on so.

Post or Outcome Processing Plan - once the raw data has been suitably organised it’s time to think how it can be processed into the intended outcome. Whatever you write here must be lucid enough so that someone else could take your data and generate your outcome. Typically one might uses a defined process, a model, a set of guidelines, a standard framework, a defined structure (such as the VISA model for strategies or the APLOM model for policies etc) but it has to be clear and well thought-out description of how the outcome is to be built.

Do not be tempted to guess and just end up writing anything. For example, students write mindless nonsense such as ‘I will look at my data and generate my feasibility report” or the terrible “I will come up with...” or something that looks a little more useful as “I will analyse my data and create the new VoIP implementation plan” as if anyone knows what a process called ‘look at’ ‘come up with’ or ‘analyse’ is supposed to be.

WARNING - some students will take data and display it for example as a chart and think that is the end of the matter. But you will be quite wrong if you think that anyone is going to be impressed just because you can display your data. You will get marks for displaying your data but a lot more marks if you can explain what it mean, what it implies.

Don't be fooled here. Some student display the data in a chart and then describe it in words: this is pointless. What tutors look for is that you use your knowledge derived from the literature review to explain what you data means.

[MOUSE]If you have questions about these two processes or the models mentioned please post them and I will see if I have an answer[/MOUSE]

I though I might add in some models that can be used with your data. Also if you have a model please post it or if you want to know about a particular model or idea tell us. I might not be able to help but someone will.

Policy Definition - an expression of a prudent mechanism for controlling or limiting actions based on an underlying ethic as expressed in the Company or organisation mission. So for example, a University we have a policy for assessment and that controls and limits what departments may do. A policy is most often accompanied by a strategy to deal with various aspects of the policy. A good way to think about a policy is to see it as having five elements (APLOM):

Policy Model

• A - Assumptions – Every policy will be underpinned by assumption of one sort or another about the workforce, the technology and so on
  
• P - Principles that are based on organisational values or on legislative or contractual elements
  
• L - Links to other organisational policies or other documentary sources. If you are not careful here you will find yourself overwriting or changing other policies that already exist in your organisation instead of referring to them.
  
• O - Definitions of the objects to be controlled
  
• M - Monitor or Track elements that set limits on what is permissible. This element will form the bulk of the policy definitions

Therefore the construction process is to set out the principles involved and make sure you are aware of any other related or relevant policies, legislative or contractual elements. Once the groundwork is done you can then set about defining the object to be controlled and lastly set up how they are to be tracked and monitored.

I notice an associated thread on getting a better memory and I endorse many of the ideas there about diet and exercise. But I thought I might offer here a story that will encourage you and some modern ideas to back up the principle of the story. So to begin with, good teachers are not enough YOU must find the best way for YOU to learn. There is a famous story about Imam Al-Ghazali who went to University in Gurgan and studied there for 4 years covering many subjects; indeed everything that could be learned there, he learned.

On his way back his caravan was attacked by Bedouins who took everything including all his course notes which were in a leather bag. He begged the Bedouin chief to give him the notes as they were no use to anybody but him and in any case the Bedouin was illiterate so could neither read nor write. The Bedouin then threw the bag of notes at Al-Ghazali and said “I thought you went to University to learn, not to take notes”! Al-Ghazali was so struck by this idea that he went back to Gurgan for 4 more years, took no new notes but thought a great deal and became one of the foremost of Islamic scholars of his age.

Some Tips - but they key idea that Al Gazali descovered from an illiterate Bedouin was that you only KNOW something when you can think it through use it not just memorise it.

1. Use your Long Term Memory - You have short and long term memory so practice putting what you know into long term memory by careful, directed repeated study effort. For example, if you find a new insight or understanding of something update your notes or at least make a concerted effort to put it into your long term memory; that is, 'practice' this new knowledge by going to an answer that has been marked and re-writing it for your own learning consolidation, you might also tell the tutor, he would like to know if you have uncovered anything of interest; no matter if it’s a minor point because it then become a shared experience.
2. Test yourself by Practice – look at the tutor’s examples, exercises or comments; see if you can spot where answers might be weak or improved or have elements that you don’t quite understand. Look at other people work and offer a critique; see what you can learn, construct examples of your own, look at samples but don’t use them as things to copy from use them as things to learn from. It is astonishing that many students never look at anything but their own work.
3. Use it – Knowledge is not there just to be repeated; there is no great intellectual effort needed to do that. It is to be used to explore, explain, describe and gain new knowledge and deepen existing knowledge and sometimes even displace what we thought was real knowledge. There is a real sense in appreciating that you never really know anything until you can use it, so knowledge must be practised.
4. What to do when Stuck – Chesterton said “It’s not that Research Methods (or any subject) has been tried and found wanting; rather it’s been found difficult and not tried”. This speaks about your character; don’t despair if this last part is you because you can if you want, make the choice to work hard and put in whatever effort is required. In practice when you get stuck go back over the basics again, look for parts you do understand and work from them, take a break and do something else, think of the 5 basic strategies listed in an earlier post. WARNING: check you have read ALL the relevant notes and examples and only as a last resort ask the tutor or someone else (if you keep asking others before any personal struggle with difficult ideas you will not grow academically).
5. Take a break and Daydream – the brain can only absorb so much in one go; its needs time to sort things out; when we stop focusing on a particular subject, the brain starts to daydream all on its own as it sorts things out all by itself so taking regular breaks for long or short periods is actually essential to learning. If you don’t take a break the brain will do it for us; just think how often in lessons or meetings you find yourself wandering off into a day dreaming mode. One might add here that often students are irresponsible and make poor choices, leaving everything to the last minute and try to cram the learning into a short period of time; well the latest brain research shows this to be impossible; because the brain needs time for reflection.

This note might help you when designing any data collection and precessing scheme to avoid your respondents loosing confidence in you or feeling that you might misuse the data. Indeed if you do lose anonymity you may not even be able to publish your data because the whole data set is effectively compromised.

Preserving Anonymity
Whenever you collect data there is always the difficulty of feeling sure that the respondents are answering truthfully and not telling you what they think you want to hear or showing you what they want you to see because they want to please you or perhaps because they are worried that you will tell someone else what they have said. One way of being sure that you can rely on the answers is to preserve anonymity. Therefore:

Anonymity can be lost at the point of collection – for example if I as your tutor send out a questionnaire at the end of a Research Methods course asking for your opinion of the unit and ask you to send it back to me then the way you fill in the questionnaire might be biased because you may worry because you know, I will know who it came from.

Anonymity can be lost by the method of collection – for example if we collect the data by online means we would give you a password so that a given student cannot submit a questionnaire twice but that means we have recorded of who you are on the system. Note anonymity means faceless, no one can know who you are.

Anonymity can be lost at presentation of results – when the results are presented to interested parties we have to be careful to remove all identification. For example, suppose I send out a paper questionnaire and on it ask for written comments. It now only makes sense if I send the comments to interested parties and I might very well do that by sending copies of the questionnaire itself. If I have not thought about it I might do that without removing any identification marks or codes or indeed answers that might identify you.

Anonymity can be lost by classifications – suppose I decide to classify my questionnaire by ethnic origin (or any other thing or things), then I might effectively tell whoever looks at the questionnaires who the respondent was.

i am doing a course named "Research and training seminar" and the instructor gave me an assignment , its an interview about islamic cmmunity
if any one can help i would appreciate it

i would like to ask you members to answer as soon as you can an interview about this community
i will post questions now but please answer them through email
the instructor strictly wants the interview answered by e-mail he will not accept the ones answered in the community please copy questions, answer them in e-mail and send them to me please
and i will post the results later on when the research is done
---
please help

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thanks for help

I noticed the post which contained a questionnaire. In practice it is quite difficult to derive unbiased constructs (questions) which clearly identify a dimension of the domain and at the same time are meaningful in terms of the kind of answer we get. The tests are for Bi-polar questions; that is question that have a scale of answers such as good to bad, agree to disagree and so on and most often expressed as a 5 points scale from one end to the other. Here are some tests for that sort of question although you may find the tests useful for many styles of question.

1. Non-bipolar – does the question have a defined bi-polar scale of values
   
   
2. Question has more than one dimension – typically indicated when the word “and” appears in the question; it amounts to asking two or more questions at the same time and that will causes confusion and therefore you cannot rely on the answers to such questions.
   
   
3. Questions have temporal characteristics – this means there are time dependent elements in the question so that the question would only apply if it was asked at a given point in time. Time dependent question are possible but you need great care when using them.
   
   
4. Questions have inappropriate global elements – occurs when words like “all” or “everyone” is used as it is obvious that one respondent cannot usually honestly answer such questions.
   
   
5. Avoid the 'halo' effect - impressions carrying over from one question to another.
   
   
6. Use of suggestive words - such as positive, suitable, best etc. The trouble with these words is that every one has a different view of what they mean and often a respondents bias will give unreliable answers because of personal bias and so if you use them it has to be done with a good deal of care.
   
   
7. Vague or unclear dimensions/response types – if YOU write a question but do not know what the dimension or type of response is supposed to be then your respondent will not know either and then answers may become worthless.
   
   
8. Inappropriate questions for the object of study – only careful thinking will tell you that the question is not suitable or inappropriate but this mistake is often associated with mistake number 7.
   
   
9. Questions do not apply to all respondents – careful definition of criteria for respondents coupled with careful thinking about what you are asking will help you avoid trying to ask a question that a respondent cannot answer as this error will bias or completely invalidate your in your results.
   
   
10. Can or will the respondent be able to answer honestly – this is largely to do with protecting anonymity and of course making sure that the questions apply more or less equally to every one in the sample.
    
    
11. Is the construct in the form of a leading question – this usually means that in the questions you suggest the answer or supply information in the question that suggests what the “right” answer is supposed to be.
    
    
12. Can the respondent in fairness be expected to give a reasoned answer – this tends to occurs when you start asking for the impossible. For example, if you wanted to know about this online discussion board and asked “what is your opinion of the technology used to support this discussion board” then it is obvious that 99.99% of respondents would have no idea what was being used and therefore have no opinion of value.
    
    
13. Response Latency – this means being aware of how hard a question is to answer or understand. If a question in this sense is difficult; respondents will stop and wonder what to do or how to answer the question and all this make the answers they give a little unsafe.
    
    
14. Does the grid have directional stability – in bi-polar questions you must make sure that every question implies the same scale direction and this needs hard work. However, you can quite easily confuse the respondents as to direction by the way you ask the question. There are two common forms of this:
    

Putting words like “not” into a question tend to make respondents think about the scale backwards and your results may be ruined. That is if you scale in all questions goes bad to good and you insert a question with 'not' in it then respondents can get muddled.

Getting answers from respondent who do not fit the criteria and so they end up interpreting the questions in the wrong way. For example, imagine you were surveying students but accidentally you also gave the survey to lecturers then it’s obvious that they may interpret some questions not as you imagined.

There are sadly always going to be bits of study that we find boring. Sometimes it's the tutor or the teaching methods are poor. But one cannot always have good staff so here are some tips but at the end of the day only YOU can do the work.

• Be Active: Soon as you get a chance in class, ask a question but make it a question that goes a bit deeper that just getting a factual answer, one that make the tutor and everyone else think. It takes a bit of practice to do this but in time you will be good at it. But don't try to be clever or annoy, do it to learn. Some tutors will not like it but many will love it and the more grouchy the students are the more creative the whole thing becomes.
  
  
• Persistence: If you have to read boring book do it a few pages every day and it will soon be over. I had to read Ulysses by James Joyce and although it is brilliant in parts there are very long dull sections but I stated off by just reading 4 pages every day as a minimum and before long it was all done. So with the boring subjects make sure you do a bit every day, and do it first.
  
  
• Look for Links: Try to look for links to other subjects, that will get your motivation up a bit and make it more palatable. The links don't have to be direct. I once had trouble with writing some notes on evaluation and I found the answer in a novel I was reading about two people sitting in a cafe. So always be on the alert for ideas, they will just come and be gone in a flash unless you are ready to accept them and write them down there and then.
  
  
• Can I do Better: Say to yourself, if I had to teach this, how would I do it, how would I make it lively and interesting?
  
  
• Practise: Everything you learn must be practised, used and if its not then there is doubt that you have learned anything at all. So always do the exercises, ask, how would I use this, what can I do with it now or tomorrow. Practice is like an investment, its gives you a store that you can draw on later.
  
  
• Know the Basics: Be careful that you know the basics as often this can stop you appreciating what the subject is all about.
  
  
• Examples and Exercises: Ask for examples/exercises from the tutor or from anyone and create your own.
  
  
• Group Discussion: Try to get into discussion, there is bound to be someone who is not bored and thinks the subject is great so it might rub off on you.

PLEASE complete the poll, if no one is interested then I will stop posting