Research Methods

Hey there Hugo, how you doin?

I've wondering if you know anything about how to prepare a dissertation?
I tried googling it but unfortunately I couldn't get the answer I've been looking for.
Well thanks in advance

format_quote Originally Posted by Zico

Hey there Hugo, how you doin? I've wondering if you know anything about how to prepare a dissertation? I tried googling it but unfortunately I couldn't get the answer I've been looking for. Well thanks in advance

Yes I do know something about dissertations but the term is often used very loosely to mean any sort of College or University projects. In general, however, the distinction between types of project is made on the basis of whether primary data is involved or not. Project of all sorts have a common form although the words I use here are not necessarily universal. Usually one starts a project (or dissertation) with a problem that you want to solve and work out what sort of outcome you need to generate which can be used to do that.

If its a dissertation it will involve a detailed search of the current literature meaning journals and other primary sources but with no primary data. Alternatively, one could do the same work but define and collect primary data and use that data to generate your outcome and most often that would be called a project rather than dissertation.

• For example, suppose a client wanted information on security trends for internet users in business because the problem they have amounts to management worry over moving to eBusiness. As a dissertation I might go to the library and search through Journals, CISCO reports, British or MIL Standards, Legislation etc looking for relevant information so that I could construct say a position paper as my outcome.
  
  
• Alternatively, I could decide to do the work by interviewing security experts about current and suspected future security difficulties and technological trends. Once I have those transcripts, my primary data, I then use that data to generate a position paper. Be aware that here I am not suggesting you don't bother with the literature as that is obviously absurd because then YOU would not know enough to carry out the interviews or deal with the data when you get it.

NOTE these are the generally understood meanings but the key is always no matter what it is called to ask your tutors if primary data is needed. Secondly, depending on the level you may have to focus on journals and at lower levels books and only rarely use things like Wikipedia. Have a look at the web site below and then get back to me and try to describe what your work will be about and what level it is. Also if you are unsure what primary data and primary sources mean see posts 21 and 27

http://sites.google.com/site/researc...esearch-styles

Please VOTE in the poll to see if it is worth keeping this thread up to date

In the poll for this thread some feel it is mostly common knowledge and that might be right but as a quick test to see if the stuff mentioned here is as simple as it might look can you answer this question.

In research people often speak about quantitative and qualitative styles and students wrongly interpret these as meaning using numbers or using words/text but this is a serious error but can anyone say why?

Here is an outline for Chapter 1 for a project, here it is based on a technological project but is easily modified to any.

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, its causes and reason for its resolution
1.3 Overview of Research Plan covering: approach, style, brief study plan, primary data, outcome, actor and target and it is recommended you present them in
this order as a series of connected sentences or as bulleted points.

• Approach - inductive or deductive and you may present a hypothesis if it’s applicable
• Style – qualitative or quantitative (recall that these refer to the type of outcome NOT the type of data)
• Study plan – give the briefest of outlines as to what you will do
• Primary Data – brief outline but make sure its understandable
• Outcome – the final project product that will be used by the actors (report, review, model, plan, etc)
• Actors – those who CAN and will use the outcome to eventually deploy IT assets to effect a solution
• Target and Strategic IT - the effects that would be observable if the outcome is used and IT deployment follows. Strategic
  Business IT means demonstrate that the outcome is/will lead to a strategic use of IT.

1.4 Scope (what aspect is covered) and Scale (how many firms, people etc are involved. You may also include here any assumptions made or limitations on your study
1.5 Ethical Overview
1.6 Research Question: interrogative, outcome, actor, problem, spotlight, activity and target
1.7 Aim: activity, outcome, spotlight and target
1.8 Objectives: activity, spotlight, milestone (visible features) plus bounded and progressive (non-visible features)
1.9 Summary and link to next chapter

For item 1.4 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.

For 1.6 the order in which the features are written down will vary depending on the interrogative used so this aspect needs very careful thought. Items 1.7 and 1.8 may be combined into one section for convenience and the order of the required features when written down may vary as is best to ensure lucid wording.

References are to sources that you use in your written work whereas a bibliography is a list of sources you have identified as useful but not necessarily used. University/College will look carefully at any references to see if you are prepared for study in your chosen project/dissertation topic. For each source you must consider its:

Usage - The basic usage strategy is:

• Find – Relevant texts using a library index, the internet, online book stores and so on.
• Evaluate – Once you find a possible source you must evaluate it for content and relevance.
• Contextualise – that is fit this new source into your personal knowledge base.
• Cite – If you use a source it must be listed in your reference section and cited in the text correctly.
• Discuss – you may include something from a source in your work as a copy (quote), paraphrase or summary but in all cases you must introduce it, comment on it and cite its source.

Currency – look at the publication date and be aware that in technology books are soon dated.

Accuracy – Is the information correct? If you cannot be sure then you must not use it.

Relevance – Make sure that your sources are relevant to your project topic.

Completeness – Make sure you are looking at the final version not some draft or abstract.

Uniqueness – is the source a primary one and recall anyone can publish just about anything

Coverage and Range– Use your list of sub-topics to ensure that you cover all the areas required with a range of authors so that you are fully prepared. But make sure that you are not including multiple texts with essentially the same content.

Authority and Authenticity – ask “is the text authoritative” by considering the author, publisher, writing style and currency. It is also possible to use citation indexes to see how often the source has been used. In this respect general online sources such as Wikipedia are suspect and should only be used as a starting point not as a main source and NEVER be cited. There are two elements we need to be aware of:

Author – who is saying what you are interested in? This might seem simple but often with say internet sources we have no idea who the author is supposed to be and they may assume personas, lie or make false claims so one must consider the motives of those who publishing, particularly if it’s on the Internet

Content – what is being said and one needs to be very careful that you can distinguish between:

• Opinion – such material can be used and discussed freely.
• Assumption – be careful, but as long as the assumptions, ones knows the limits of the knowledge
• Unstated Assumption – pay careful attention as this element as it is often hard to detect.
• Tendentious – when the author wants to convince you of something and will use any means to do it.
• Context – be aware of the context of what you find; is it a University site, is it a manufacturer and so on.
• Validation – authors do not always have their materials checked by an authoritative third party
• Fact – here one needs much more care that you have the original source. Remember, facts can be quantitative data, theories and explanation but the whole notion of a fact is troublesome when used to support arguments.

Trust - in research trust nothing until you have good cause to do so. This is the opposite of what we do in our daily lives in that we tend to trust until we have reason not to.

Validity – this means that we ask is this a valid source in the sense that it was constructed in a reliable manner. Any lack of information on proof readers, editors and publishers means that mistakes are more prevalent than in print and therefore increased scope for innocent error and for outright deception.

Qualitative Data Processing Mechanisms
Many projects deal with qualitative data and this note outlines the sort of things you can do at the pre-processing stage. What I suggest here is a precursor to template analysis and you may like to research that term yourself. There is also a related technique called content analysis and it is much the same as far as ideas are concerned but differs in the detailed ways they are used.

There are four sources of data that you might want to process: text, audio, video and images. The principles in each case are similar but the methods will differ although it is possible to buy software that will help you do all 4 of these such as HyperRESEARCH™ Downloads. In this note only text processing is covered. Here I only outline methods for text processing but the principles are much the same for other types of data. For example, when looking at text, say as interview transcripts you might look for what are called outliers (unusual or odd opinions) or common threads and in a similar way if you were looking at video footage you could look for unusual movements or scenes and common features between scenes. Be aware that processing video and audio is very time consuming because it becomes very tedious if you continually want to play back little sections or you might not be quite able to make out what is being shown or said. On the other hand, watching/listening is very good for picking up emotional clues because they can often be seen in body language or heard in the voice.

Alternatively, there is software that will transcribe voice data to words (but it’s not always very accurate) and also software that can clean up a bad recordings. However, in both cases it is normally best to work out what you are looking for and then get some help so that one person can look for features A, B and C and another can look for features X, Y and Z or run through recordings noting important elements and then good back to them later.

Many projects deal with qualitative data and this note just outlines the sort of things you can do at the pre-processing stage in your research design. What I am doing here is a kind precursor to template analysis and you may like to research that term yourself. There is also a related technique called content analysis and it is much the same as far as ideas are concerned but differs in the detailed ways they are used.

Introduction It is very important to keep notes of interviews, observations or as you read through documents and make sure those notes are structured and accurate otherwise you will find your biases coming out in the results – that is you will interpret what you find the way you would like it to be. Don’t fall into the trap of collecting data and thinking that is all you have to do or ignoring it as far as getting an outcome is concerned; that can only have one result – fail.

For example, suppose I have a set of interview transcripts and a set of observation notes all collected in an attempt to generate as my project outcome a best practice portfolio on office management development. So I might pre-process this data (transcripts and observation notes) to get: common threads, outliers and labelling but obviously those three lists cannot possibly be regarded as my best practice portfolio but they are a necessary step toward me generating it from them.

Qualitative Processing Ideas
The ideas listed below are commonly used to look at qualitative data. I am not suggesting you use all of them but usually as the data emerges from your collection process you will start to get a feel for which ones might be the most useful. Commonly, people use a spreadsheet, Word or Database to deal with all this although it can also be done by hand. My preferences would always be a database because of the potential for indexing, searching or linking it to other data sets or even links within itself.

• Common Threads - Are there common response threads running through your interviews, observations or documents as these indicate a shared understanding in your sample and might be useful in formulating the project outcome. How to do it - use a tabular method to collect this evidence together by listing the themes and counting occurrences and variations.
  
• Outliers - It is often useful to look for extreme or unusual opinion or events and they might point to serious problems in the situation you are investigating. These indicate that the understanding is not shared and often means that further investigation may lead to very useful insights. How to Do it – use the same tabular record used for common threads but look for items on it where the opinion is different, unusual or extreme with very little agreement with any other sources with virtually no commonality.
  
• Word Frequency - You can construct a concordance and look at how frequently words are used and of course it also gives you the situation vocabulary. How to do it – use a software tool to generate the list of all words used and their frequencies. In fact it may be quite interesting to see how wide the vocabulary is as this might give you another “handle” on the problem theme. I would not recommend you try to do this manually unless the transcript or documents are of a very limited nature. Unfortunately, if the documents are not in an electronic form (unusual these days) then a manual process is the only one possible.
  
• Meaning - Make sure you know the meaning of any words used and what kinds of words are used: descriptive, explanatory, critical and so on. How to do it – using a constructed concordance or glossary to list all the words used and then for the important ones or ones where you do not understand the meaning write a definition.
  
• Semantics – this is just an extension of “meaning” but here you are trying to ensure that you understand what has been said – so one might look at phrases or sentences for example. Be careful, it is all too easy to see a meaning that you would like to see and not the one that is actually part of the data. It is unfortunately all too common for students to write what they think is a simplification in their own words or substitute an accepted situation word or words for one of their own and this can often turn out to be disastrous. How to do it – it is hard to find an absolutely secure process here because a certain amount of domain expertise is always needed. However, a reasonable plan is to look for and write down the key ideas in the phrase or sentence because if you have the key idea then in practice one understand what is being said. One almost always does this in conjunction with the tabulated themes because themes themselves might be an object, an activity or and idea.
  
• Labelling - It is often interesting to look at how situation elements are labelled. For example, the software might be labelled as ‘useless’ or ‘difficult’ by users or the mangers labelled as 'arrogant', 'unhelpful' or ‘lazy’. When this happens it may indicate serious problems in the situation. How to do it – using a constructed concordance or glossary to list all the words used and then for what you regard as a label search for them in the list.
  
• Structures - You can partition the answers into such things as: opinions, definition, explanation, theories, concepts, methods, policies, governance, training, environment, attitudes and so on or any other categorisation that you can identify. This will help to ensure that you have a good understanding of the situation as seen from interviews or documents. How to do it – use your tabulated list of themes and then add extra columns to code the structure that you have identified or want to use. Remember that an element may have more than one structure – something could be a definition but also be expressed in the form of an opinion.
  
• Response Validity - Always ask is the response valid or relevant in that situation or can it be discarded. The reason you want to do it is because you don’t want to be encumbered by data that has no value and one is always looking to get the smallest valid data set. How to do it – this is not easy to do and it requires good to very good domain knowledge. I would recommend you try to generate a few simple questions that you apply to the data and if they all give a yes answer then accept the data. This might be things like: “is it a common opinion”, “is it a fact”, “is it interesting or insightful” that sort of thing but don’t have too many questions else you will end up with no valid data!
  
• Response Reliability - Always ask how reliable is the data that you find or are given - this is to do with how the interview or search was carried out and can you rely on it as being truthful. How to do it - Essentially we ask would we get the same result if we did the interview/search again.
  
• Significance - Can you identify items that are clearly significant in this situation – significance here means that the response is representative of something genuine. How to do it – just look at the tabulated frequencies for the main themes, labels and significant words used. One cannot be certain from just frequency that it is significant so one must also weight it up in you mind against your research question and whether you can do something with the data. For example, to be flippant one might get a common theme emerging that there is not enough car park space and things like that it is almost certain you can do nothing about.
  
• Generalise - Is there anything that leads you to make generalisations. How to do it – essentially what one does is look at themes, labels, outliers and knowing these have emerged from a sample we now try say what it might mean for the whole population (a company for example) - can it apply to the whole company, is there some important element in this theme that has a much wider implications, is there a principle that can be established, can I construct a theory and so on.

We all state facts and opinions all the time and here is a note that might help you understand what these ideas mean so that you can better utilise them in your project or dissertation. You might also want to disagree with me or add some ideas of your own.

Facts and what may be deduced from them
We use the idea of “fact” all the time; so what is a fact; how do you know when you have a fact? For example, if I say there is a thing called gravity is that a fact, if I say that 62% of students on my IT course passed is that a fact also? If I look at a fact like "gravity" (called a natural fact) and a fact like "62% of students passed in the May cohort" (called a nominal fact) - is there any differences between these two kinds of fact?

So is it possible to prove a fact; decide whether it is true or not. The answer is that I can find proofs of gravity and I can find proofs of the pass rate. Therefore, a fact can be independently checked in some way. Now for nominal facts you may find that some people will not accept your proof. To take a perhaps extreme example, suppose I say that the existence of God or Allah or Krishna is a fact then I might cite proofs and you might or might not find them convincing but I think you will see that such proofs are not falsifiable (put simply we cannot work out how to test the proposition) and clearly not accepted by all as true. Whereas gravity is always true, can be tested and cannot be ignored by anyone.

Let us say you are a Muslim or Hindu or Christian; that is a nominal fact about you that is true and I accept that fact, but my acceptance of that fact does not mean I also automatically accept that Islam or Hinduism or Christianity as holding the truth. In other words what I do or think based on a supposed nominal fact will depend on me not the fact itself. Notice that with natural facts I cannot, for example, rationally decide that I don’t believe in gravity. But, suppose that I irrationally decide that I don’t believe in gravity, that is a matter for me but what I cannot do is avoid its effects because I do not believe in it. Put simply, you believing something to be a fact is NOT a proof of the fact itself.

Now suppose I ask you IF a fact can change what will you say? A fact is a piece of information that can be independently checked. In simple terms you can get the same information from several places. A fact sometimes can be changed and sometime not. Please be careful here; I CANNOT change the pass rate of the May cohort BUT I can in principle change the pass rate for later cohorts. Natural facts like gravity cannot be changed by you but some natural facts do change, for example, if you were asked how many planets there are in the solar system then when I was at school the answer was 9 but now there are more. Similarity, there were thought to be just two species of elephant; African and Asian but quite recently a third species has been found.

Nominal facts are important because they crop up all the time and we can in principle do something about them, change them in some way. For example: with a nominal fact I can ignore it, try to forget about it or just regard it as of no value (consider that we cannot do that with natural facts like gravity). We can take active steps to change a nominal fact. For example if I am not satisfied with a 62% pass rate I can try to change the course or students on it in some way to get that pass rate up (or even down). We can take active steps to make sure that a nominal fact is NOT changed as well

Facts and Decisions
One important idea associated with all this is that there is a tenuous link between a fact and a decision. That is we cannot be sure that a given fact will always generate a certain decision. This means we might arrive at a whole series of possible decisions from a given fact or set of facts. It follows that there is not necessarily a logical link between a fact and a given decision. In simple terms, if I tell you the pass rate for your cohort is 62%, that is a fact, but I cannot know what decision you might make based on that bit of information. Now we use nominal facts to drive our research; that is we have some information that tells us that something in the real world is or is not as we would want it to be, indicators if you like of our presenting problem.

Opinions and why they are different from facts
In contrast to a fact an opinion is person's personal beliefs, thoughts or feelings about something; these may be rationally held and based on facts or quite irrational. Notice that you cannot independently check an opinion as you could a fact. For example, if someone tells you their birthday is 26 April 1942 then you can independently get that checked. In contrast if you ask someone do they like birthday parties then you cannot check that by some other route, you can ONLY reliably get such an answer from one source?

You might also notice that we might reasonably make a decision on a fact but we would be much less sure of ourselves if we made the same decision based on an opinion.

You might like to visit the site below as it is dedicated to Research Methods and although it is a big site and you need a bit of effort to get to know it I think you will find it a useful resource. There is a software section and often you can get demo versions that have some limits but still very useful for student work

http://www.methodspace.com/

If you are collecting data then you might consider using an iPod in one of its forms. The reason it might be useful is because there are 1,000s of small applications (I read somewhere there are at least 35,000!!) that might be downloaded from Apple Store to help you and often they are free (as long as you can put up with a bit of advertising).

For example there are plenty of databases, list makers, common stats or facts, statistics, graphing and charts, mathematics, books, dictionaries, translators, questionnaires, books, calculators for all sorts of things, etc. If you also use a bit of imagination you can use apps intended for one purpose for another. For example, one can get an application say for constructing a shopping list and alter it to be a questionnaire, an application for a to-do list can be made into a simple database - there are no real limits to your imagination so go and have a go.

One problem you might get is that exporting data is not always possible. When it is available its usually in a form that allows you to email out of the app. For example, lots of shopping list type applications allow you to email your shopping list - so as I said above, turn that app into a simple data base and off you go!!

Be bold and invent uses that help you. Try these: Surveyor, Simplist, iObserve, Quick Graph, AppCreator Database Manager, Statistics Tool Kit, Statistics Formulas, Spreadsheet, Formulae, WordBook English, Wattpad, Companion Synonyms, FreeSaurus, GeniusGRE-Antonyms, Crossword Master, Bible, The Holy Qu'ran, Look Up Encyclopedia, Stanza, QuickVoice Recorder, ConvertLite, SketchPad, Brento, Print and Share, Language translators etc

I thought you might be interested to look at the idea of fallacy as it can often help when reading or listening to someone or something. Today I will just cover what are usually referred to as informal fallacies'. If you want to try them out then just visit some of the threads in the board and look through what has been said to see if the arguments are sound or fallacious.

Fallacy
This occurs when the reasoning is faulty in some way and often it is hard to see where the fault lies and this can mean you accept something that is not true or you couch an argument that cannot be shown to be correct. More often than not, fallacies occur because we have not understood or formulated the premises with sufficient rigour and we are deluded by arguments we hear or deluded into thinking our own are sound when they are not. Thus your argument can fail because it is not logical or because it is perfectly logical BUT the premises on which it is build are false. There are many forms of fallacy and I am indebted to Sharon Kay (2009. 170) for this list with some modifications added.

Formal Fallacies – these are fallacies that arise when we use the most common forms of argument. These forms of argument are listed below but we summarise the fallacies here.

Informal Fallacies – these are fallacies that arise in all sorts of debates and arguments and you would do well to familiarise yourself with them so you can make sure you don’t commit them and you can see when others use them as forms of argument.

Fallacies of Relevance - meaning that the argument is not to the point or avoids it.

Ad Populum - arguing that something is true because many believe it to be so.
Ad Ignorantiam - arguing that lack of proof proves something.
Ad Verecundian - arguing by relaying on an inappropriate authority.
Red Herring – avoiding the argument by changing the subject
Ad Baculum – appealing to force of threats to convince
Ad Misericordiam – appealing to pity or forcing guilt on you
Ad Hominem – appealing to personal considerations (rather than to fact or reason) commonly seen when supposed arguments are personal attacks and this may take the forms;

Abuse – false refutation by appealing to insults or belittling tactics.
Circumstantial - by claiming your opponent is biased because of who they are or what they believe
Poisoning or Spite - by connecting the opponent with something undesirable (ie you’re a racist, you are uneducated, etc)
Tu Quoque - accusing the opponent of being guilty of something, typically, hypocrisy or lack of knowledge

Fallacies of Presumption - meaning false or weak assumptions or guessing or simply things are taken for granted

Hasty Generalisations - arguing from some to all rather than all to some.
Circular Reasoning - going around in circles so that conclusions also become premises for the same argument.
False dilemma – arguing by reducing a variety of legitimate options to just two; usually equally unfavourable ones.
Post Hoc – assuming that temporal succession implies a causal relationship (A caused B because A came before B).
Straw Man – tending to oversimplify so creating a weak or sham argument so as to make it easier to refute.

Fallacies of Ambiguity (the argument is deliberately unsound because its meaning cannot be determined from its context).

Is Ought – arguing for prescription from a statement of fact or description
Amphiboly – ambiguous grammatical constructions so arguing by creating two meaning by faulty sentence structures
Distribution – inferring from the whole to a part or vice versa
Equivocation – using statements that are not false but cleverly avoid the truth; commonly by using the same word but in two or more ways or meaning

When we hear the premises and the argument we my be reluctant to accept the conclusion but logically to do that you either reject one or more of the premises or you reject the way the conclusion has been draw from them (you reject the reasoning as invalid or fallacious) or of course you may reject the premises and the reasoning.

For example, I might say “if my car has petrol (premise) and I turn the engine on (premise) then I can drive away (conclusion)”. But you do need to think about this kind of logic else you will end up copying it leading to a fallacy with such absurdities as “if I choose my lottery numbers and I buy a lottery ticket then I will win the lottery”. So it’s as well to be aware that logic is about the form of the argument and saying something is logical is not the same as saying it is sensible unless the premises are also sound.

See Kaye, S., M. (2009), Critical Thinking, Oneworld, ISBN 978-1-85168-654-4

I had a question about post 34 (about preserving anonymity) asking how in practice you deal with it so that you get reliable data and it occurred to me it might be of more general interest.

Well the first thing to say is it's never easy and you can never be absolutely certain. But there are steps you can take. I am sorry the answer is long but its not a simple matter. If I just speak about a survey to give us context.

Professionalism and Ethics
1. In general the rule is that you are as professional as you can be in every step of the process and that helps respondents to feel confident about responding to you. One should be aware that such confidence can be dashed instantly if you make mistakes or are seen to be careless because they will then say to themselves that if you cannot be trusted in small things then you cannot be trusted to look after the data. For example, if you make grammatical errors in questions, create poor paperwork design, spelling errors etc. Now in themselves these might not sound serious but it is very important that you understand that they do give respondents a 'picture' of you and the quality of your work which is a negative one and that alone might mean your data becomes unreliable.

2. Ethics - You must understand the nature of ethics and how to put an ethical stance into practice or in simple terms you have to have integrity and honesty and that will be conveyed to the respondents by all you do and the quality of your work from question preparation to management of the collected data.

3. Standards - are important and you must find out if there are any the apply in your area of study. If they don't exist then it might be a good idea just to think through what standards you might consider,

4. Approval - in most Universities and for any study of significance there is usually an ethical form to fill in which is checked by the course leader and if there are thought to be serious ethical issues about what you propose then it might have to go before a University Research Ethics Committee for approval or they might approve it with conditions or of course reject your proposal.

A Worked Example
1. The first thing to work out is what problem you are wanting to solve. This is not always easy to do but it must be done with persistence and care even to the smallest detail.

2. Once you know what you are trying to solve you can think about a solution route. That is, you say to yourself, "what can I produce that can then be given to someone who will then use it to bring about change".

Example – Suppose I have the problem of students coming late to seminar sessions and I want to collect data about it because I want to find a solution. To get beyond this you MUST understand how you will think about the problem: deductive or inductive;

If I am deductive I might have an idea (a theory if you like) that coming late is due to cultural norms. Because I have this theory ALL my data is going to be about cultural norms because I set out to TEST the theory to see if it is true. So I am “forced” to define only data about culture: country of origin, religion, family values, previous schooling, male/female relationships, respect for elders, the arts, prayers, eating habits etc.

If I am inductive I have no theory because implicitly I cannot decide what is causing this problem or its possible solution so in effect I just have to guess what data might be useful. So I am “forced” to define (almost randomly) data about: age, course, religion, values, respect, lodgings, transportation, the weather, friends, other classes, looking after pets and so on.

Notice that here that in the deductive case I get only ONE dimension; culture, but in the inductive case I might have many dimensions to explore because I do not have a good idea about cause.

3. Now that the data is sorted out let us supposes you are deductive so you next step, since it’s a survey is to work out exactly what questions to ask to get the cultural data that you want. Once you have a set of questions you must check them:

Form - Check the grammar and for known types of errors in questions (if you need a list of these please ask).

Consistency - Check that ALL the questions are on the same dimension (culture) and ask for different aspects of it

Reliability & Validity - Test each questions for reliability (will every one understand the question in the same way) and validity (are we really measuring an aspect of culture in each question)

Ethics - Check that ethically the question is acceptable with your intended sample (this means putting yourself their place and asking, "would such a question upset you or offend you"). This does not mean you do not ask such questions but it does mean you need special care in their wording)

Pilot - Lastly, it’s a good idea to do a pilot as a final check

4. At this stage one hopes your questions are as good as you can make them so that is your first step over in ensuring you get consistent data. The point about all this is that you can make a candidate lose confidence or trust and fear for anonymity because the questions are poorly worded or offensive causing them to suspect ulterior motives or rightly question your competence.

5. You next step is to prepare a script - a short one as to how exactly the data will be collected as well as a script that explains to a respondent what you are doing and guaranteeing anonymity. If you like it’s a contract between you and the respondents and you and can both sign it. If you are getting people to help you with data collection you MUST ensure they are fully trained by you and understand the purpose of the survey and it's ethical underpinning.

6. Data Management and Security - You MUST work out how the data is to be managed at EVERY stage so that the respondents answers are never compromised. This starts with candidate selection and goes right through to final disposal of the data and survey sheets or transcripts.

7. Respect your Data - Finally, you must treat the data with respect. You might start this by organising the collected data into a table or catalogue so you can check for missing entries or other things that might be amiss with the data. It is also possible to check certain kinds of data for reliability using for example Cronbach's Alpha and that will tell you if your questions are consistent.

This means that as best you can, you shut out your own biases or at least be very aware of them so that you are ready to accept what the data is telling you rather than what you want it to tell you. Thus, when you write the report or whatever is your outcome, it is an honest analysis of the data and be aware that you can unwittingly uncover the identities of your respondents by careless data processing and writing up.

I though you might be interested in some test questions on Research Methods, give you a chance to see how well you do. I add some notes on this type of test first but I will no be publishing answer unless you specifically ask me for them in a private email or some other way within the board as I don't want to spoil the value of the test for later readers. If there is any great interest I will publish further questions.

When tutors write multi-choice questions they will normally use a process that goes by the quaint English word ‘obfustication’ or one might say it’s an attempt to baffle, confuse and mystify you unless you really understand what is being asked in each question. The reason this is done is to make the questions a real test of your knowledge and how it might be applied. To do this each question answer will have a ring of correctness about it, that is it will not be obviously wrong but only a clear mind equipped with the necessary knowledge and how that knowledge is applied will be able to deal with them.`NOTE: This is not just about Research Methods questions and all Multi-choice tests will have this feature.

Therefore, in the test that follows you must select ONE answer to each multichoice question which you judge to be the best answer to the question as set. Please note again that all answers may have elements of correctness but only ONE answer is the best one.

Q1. A policy is something that has the following characteristics:

A. A procedure for carrying out a task at a high level.
B. A mechanism for controlling or limiting actions based on an underlying ethic.
C. A report produced by management.
D. A document that is used to generate a strategic plan.

Q2. A strategy is best described as something that:

A. Shows how a major activity is accomplished in a company or organisation.
B. Says what actions are needed and not necessarily how those actions are achieved in practice.
C. Limits what might be done in a given situation such as might be found in a company or organisation.
D. Is a plan of action that is formulated by senior managers within a company or organization.

Q3. In any research project context is very important because:

A. It is a way of expressing our viewpoint or attitude to a given situation in which we are not directly involved.
B. It expresses the situation in which a problem theme or issues exists and this is necessary for a full understanding of what needs to be done.
C. It allows one to focus on the main or primary task of an organsiation since unless that is addressed the project might fail.
D. It causes the researcher to focus on the details so that nothing of importance is missed or overlooked.

Q4. The scope of a research project may be defined as:

A. The area of interest of the researcher.
B. The area that the research covers.
C. The functions provided in a system.
D. The context in which the research takes place.

Q5. When testing research ideas that are related to change in organisations a key element of the test is to ask is it 'Culturally Feasible'; which is taken to mean:

A. Will the suggested outcome of the research lead to changes that might be acceptable or not acceptable to situation actors.
B. Will the outcome of the research be politically acceptable within the company profile.
C. Will the attitude of the researcher be a barrier to creating a feasible solution based on the research question.
D. Will the research outcome be feasible from an ethical standpoint given the culture of the country in which the Company exists?

Q6. When testing research ideas that are related to change in organisations a key test is to ask is it 'Systemically Desirable' - this is taken to mean that the changes suggested by the research:

A. Will have an effect on the whole organsiation in some way.
B. Leads to an increase in user acceptance of the new system.
C. Has a strategic significance within the framework surrounding the research question.
D. Is systematic and therefore well thought out.

Q7. Epistemology is usually taken to mean:

A: The basic idea that ones view changes as you learn more evidenced facts.
B: The science of proving a stated theory in an appropriate way.
C: This word is used to describe a body of evidenced knowledge.
D: This is the term used to express the idea of knowledge and its justification.

Q8. Which of the following could be usefully thought of as an ontology:

A: The results of research experiment.
B: A book which purports to be a summary of a given subject.
C: A set of programs making up a payroll system.
D: A library collection of encyclopedias.

Q9. The idea of symmetry in research is important because it means that:

A: The core research has a plan that balances the data collection between methods.
B: The core research is based on a real-world problem or issue of significance.
C: A researcher makes sure that the literature review and the core research are balanced.
D: A researcher words their research question so that we always get a useful result.

Q10. To understand the relationship between DRP (Disaster Recovery Plan) and IT planning'. The main fault with this objective is that it has:

A: No outcome that can be evidenced in any practical way.
B: An action - 'Understand' - that cannot be carried out effectively.
C: No time scale that can be realized within any project proposal.
D: The context in which the 'understanding' takes place is unknown.

Q11. To find out whether telemedicine has any essential impact to health care management in Malaysia. And to prove that Telemedicine has the potential to alter the structures, the procedures, and the outcomes in healthcare structures in Malaysia'. The main fault with this aim is that it has:

A: Vague actions without any clear context.
B: Not been possible to prove anything in the area of Telemedicine.
C: No value since aims are not about procedures they are about outcomes.
D: Has two distinct aims and therefore loses its focus

Q12. An issue is most usefully defined as:

A: A serious problem that needs urgent resolution.
B: An Area within and organsiation that is problematic.
C: A personal view on what is seen as problematic.
D: A matter of concern or debate amongst situation actors.

Q13. Values are most usefully thought of as:

A: Elements that are found within a given situation and to which we can attach a tangible or intangible benefit.
B: Elements related to personal judgement that one would want to preserve no matter what changes are made.
C: Items that are specified with an organization's policy portfolio and expressed within a given strategy.
D: Personal views about how we might shape an organization within a given cultural framework.

Q14. What is wrong with the following expression of a research idea: 'Is the eCommerce impact in Hong Kong positive?'

A: The idea is clear but it is not symmetrical and therefore of no great utility.
B: It is not expressed so that we know whether the answer will be fact or opinion.
C: It cannot be expressed as null hypothesis since that usually asks for negative effects.
The word impact is too vague and might be taken to mean almost anything.

Q15. When writing a research question which of the following is regarded as of most importance?

A: The question is clearly bi-polar in nature
B: That the perspective from which the question is asked is defined.
C: The form in which the answer to the question must be given.
D: The choice of the interrogative word used in the question.

Q16. Induction is a thinking style that implies we draw inferences from observations by a process that says:

A: More of the same
B: Experiment and observe
C: Focus on logical processes
D: Use reasoning based on information

Q17. In student work we see the line "My study is about the nature of trust in the design of IT systems and my thinking approach is to be deductive because at this stage I know little about the nature of trust and so will use Vignettes as my main Research Method". With this in mind which of the following might be Tutor feedback?

A: I think you might mean inductive here because you intend to make observations in this IT work area using real primary data.
B: I am worried that you have not fully taken into account the sensitive nature of trying to get data about the nature of trust.
C: This is a blunder because deduction implies a theory or speculation and that will guide you in your choice of primary data.
D: This is a good choice because the nature of trust is vague and so looking for illustrations/vignettes is an excellent way to proceed.

Q18. What is wrong with the following statement of problem: "My problem is to find a way to upgrade the network".

A: Upgrading a network is a simple issue and therefore not a problem.
B: Problems are objects that cannot be evidenced not activities.
C: The problem is really why we need to upgrade the network.
D: It is always a bad idea to think of an implementation idea.

Q19. A student suggested that her problem was “to manage helpdesk fault ticketing more effectively”. This is a very poor problem statement and points to serious lack of dedicated problem exploration because:

A: It is far too vague to just say "more effectively" as that cannot be measured.
B: It is very unclear what "fault ticketing" might mean here.
C: It is impossible manage faults so this problem cannot be solved.
D: It’s obvious this is what one wants to achieve and not the problem itself.

This thread seems to have had a fairly constant trickle of visitors but no comment one way or the other, not even further questions so I thought I would perhaps stop posting notes for a while. However, I have had questions privately about thinking styles and how to think. Some take the view that it is all about logic and you can assemble the facts (as you see them) and reach a conclusion leaving you with no doubts at all. Others have claimed they are totally open minded and accept or reject new ideas or thoughts in a logical manner. Yet others easily accept ideas which fit in with what they already believe no matter how thin the evidence and so on with a whole spectrum of how people think they think and the degree of openness and awareness they have of themselves.

With this in mind I thought it might encourage you to enter the debate about research by asking you to answer some questions so I offer two, so please post your answer or even say why you think the questions are pointless.

1. In society we often talk about being open minded and most would probably say they are open minded but what does it mean to have an open mind, what is this thing called open mindedness and perhaps give an example from College or work where you or others displayed open-mindedness?

2. In his book “The Under cover Economist” Paul Seabright tells a story of the pleas of a soviet official trying to comprehend the Western System who asked: “Tell me… who is in charge of the supply of bread to the population of London”. The question is comical but the answer is dizzying. Now, what is the answer and what useful idea or ideas can you extract from this that you can use because it gives you an insight you perhaps never had before?

Harford, T, (2007), The Undercover Economist, Random House, ISBN 978-0-345-49401-6

Someone wrote to me and asked if the following was a satisfactory way to define a problem. Defining a problem occurs in every research study and if it is not done well there are likely to be difficulties later on. It is as well to remember the old adage here that "if you aim at nothing you will probably hit it." So can you offer any view or feedback for him?

"The presenting problem is the lack of awareness of appropriate and effective countermeaures of most SMEs towards IT vulnerabilities which is evident in the delays and errors in the administrative operations".

He also when choosing his sample to collect data to deal with this problem said:

"the respondents were chosen from the list of employees from the three selected SMEs. There were 70 employees who enlisted themselves to participate in the survey, the researcher chose 50 employees as a viable number to be used in this study."

Any advice here as to whether this would be a valid and credible sample?