University or College Study:

[Hawkeye]

Going to an Interview
I expect many of you will be going for an interview soon so you might be interested in the sort of advice and training that is given to Appointments Teams. Basically, once short-listing is competed the Appointments Team must prepare for the interview by constructing appropriate questions. As a rule the panel must ask every candidate the same questions, with questions shared amongst panel members, though differing answers can be followed up. Here are some general guidelines for best practice.

Closed Questions – brief questions of a factual nature, not requiring elaboration though such question should normally have been dealt with at candidate selection stage and asking them here implies weak selection procedures. If you must ask such questions restrict their number as it can be frustrating for the candidate as it gives them little opportunity to express themselves.

Open Questions – which invite a candidate to open up to the panel and typically this type of question starts with: why, how, what, where, when who and which in order of usefulness.

Direct Questions – similar to open questions but in these cases you are mainly looking for information not discussion from the candidate.

Follow-up Questions – this allows the panel to delve deeper into aspects of any answers given to the agreed set of questions.

Probing Questions – used when you want to gather information that a candidate may not want to divulge.

Summary Questions – these are used to ensure that the panel has been listening and so they are a kind of check that the right information has been gained.

Hypothetical Questions – are an option but it is usually best to let the candidate draw on their own real experiences or perhaps experiences they know about and so the panel may well lean more that way.

Closing Questions – the chair of the panel will usually deal with these and they are a signal that the interview is drawing to a close.

Things to Avoid – it is essential that all panel members are briefed and/or trained in asking questions and listening to answers prior to the interviews taking place so that all of the following can be avoided – however, the chair must always step in when the questioning takes a wrong turning.

Leading questions (when you in effect tell the candidate what you want the answer to be)
Multiple questions – asking more than one question at a time
Questions that impinge on a candidate’s personal privacy or confidential matters
Using jargon unless it relates to a specific skill
Making assumptions
Using ridicule or sarcasm in questions or responding to an answer
Misleading or lying in questions
Accusing the candidate of misdeeds, impure motives or lying
Engaging is fallacious reasoning

[Hawkeye]

Some Possible Definitions Academic Research Styles
When setting out on a research program to find an answer to an interesting question, various styles of reporting are available to you. For example, one might investigate whether cascading styles sheets lead to simpler accessibility on Web pages or you might evaluate the role of email management in business success or you might diligently search Journals for the latest information on a new technology. These forms may usefully be subdivided into:

Project – where one collects original primary data at a point in time from a defined source or sources in order to answer a Research Question centred on solving or partially solving a known problem.

Dissertation – where one collects information from Journals or other respectable and academically acceptable primary sources. The intention usually is to speak at length for example about a new technology or idea by summarising the latest available information. However, suitable student applications for this type of project may be rare because most students will not have easy or indeed any access to such materials unless they are at a large College or University

Thesis - Implies that the work is based on some hypothesis or premise, which is put forward without proof. The report then sets out to prove the premise and where this is not possible, to offer some discussion and evidence for its validity.

The distinction between types is made on the basis of whether primary data is involved or not.

If it’s a dissertation it will involve a detailed search of the current literature meaning books for the groundwork and then on to 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 internet security trends in business because the problem amounts to management worry of moving to eBusiness. As a dissertation I go to the library and search through Journals, CISCO reports, British Standards etc looking for relevant information so that I could construct say a position paper as my outcome.

Alternatively, I do the work buy interviewing security experts on 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 if primary data is needed. It is therefore important that you know what your College or University is asking you to do.

[Hawkeye]

Just looked at my previous post and though some might not be aware of what is meant by primary data so here is a not and some examples:

Primary Data
Primary Data is data, is new data in the sense that it will not exist as a set until I (you) define, collect and record it at a given point in time. But it must be collected for a specific purpose in that the primary data set is representative of some aspect of the area under investigation and can be processed to get a defined Outcome that will resolve or partially resolve a stated problem theme when used by situation actors.

Example 1. Suppose I want as my project outcome to define all the various accounting functions so I pick up a manual for my in-house accounting system and then go though it looking for all the various accounting functions and listing them – is that primary data and is this a valid research purpose?

No because in the first place one might just regard the manual as listing the functions anyway so in effect the data already exists, secondly, this is just one book and so its content might be complex, trivial or totally unrepresentative.

Example 2. If I extract instances of phishing from an email log would that be primary data because clearly the email log (secondary data) exists.

This looks fine because although the data exists in the log when I extract it I form a new data set that did not exits as an entity before.

Example 3. If I conduct interviews in order to describe a user purpose regarding illegal software downloads in my company with selected employees would the interview transcripts be primary data?

This is fine because clearly the transcripts could NOT have existed before I conducted the interview so it represents a new set of data. In practice one would go through all the transcripts later using text processing ideas and so arrive at a more structured and organised set of data.

Example 4. If I look through written reports (secondary data) on security violations for a particular company with a view to identifying the root cause of each violation would that be primary data?

This is fine even though the violation reports exist (secondary data) the list of root causes (my primary data) did not so it is primary data.

[Hawkeye]

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 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 post processing to finally generate the outcome (bake the cake)

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.

[Hawkeye]

This note might help you when designing any data collection and processing scheme to avoid your respondents losing 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 and you might end up getting sued or you work rejected by the University.

Preserving Anonymity
Anonymity means "without a name" or "namelessness" and so anonymity typically refers to the state of an individual's personal identity, or personally identifiable information being publicly unknown. 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.

[Hawkeye]

Here is a list of Data Collection Strategies with a brief description of typical use.

Activity logs/skill sheets/Diaries - Written documentation of participant's attendance, achievement or acquisition of skills. Useful for 'what' or 'how many' type questions.

Document searching - Review of written documents such as performance ratings, program logs, tally sheets, and other existing indicators. Useful for 'what' or 'how many' type questions.

Focus groups - Moderated discussions on a particular topic or issue where we are essentially looking for opinion on something specific. In general one might just think of this method as interviewing in groups rather than one to one. Useful for 'what', 'how', or 'why type' questions.

Interviewing - Data collection through oral conversations. Useful for 'what' or 'why' type questions

Observation - Watching people engaged in activities and recording what occurs. Useful for 'how' or 'what' or 'how many' type questions

Portfolios - Compilations in various forms but within a set theme. Useful for gaining an overview and asking ‘how’’ style questions

Questionnaire - Written responses to clearly defined questions. Useful for 'what' or 'how many' type questions.

Role Playing/Simulation - Where we simulate some activity so that it is better understood, noting pre-arranged elements. Useful when it is impossible or undesirable to observe an activity in the real world.

Seminars - Moderated discussion but led by a position paper which sets out an idea which needs to be debated. Data then is a summary of findings. Useful for testing an idea where we set out both to gain understanding and look for other views or opinions

Life Histories - Used when interviewing respondents to gain an understanding of who or what they are and why they think and act as they do.

Tests - Where one wants to see or measure performance in some way. Useful when you want control over the the situation in which the data is to be collected.

[Hawkeye]

Sample Frame
This can take many forms but is an absolutely indispensable idea in research and your research may stand or fall based on its choice or often no choice. In its purest form a sample frame is a list from which you can choose in some way, usually randomly. Remember, you can sample things as well as people but here I will just give examples for people.

Precision - In samples we often speak of the level of precision. Here precision means how well does the sample represent the population and it is obvious that precision is largely determined by the sample fame and the calculated sample size. However, it is obvious that sample frame is of the first importance since if one is selecting sample points from an unsuitable list then it really does not matter what sample size you use it will never be representative.

Here are some examples.

The phone book - if you were sampling people in a particular area then this might provide you with a useful list of names. It is not perfect of course as not everybody in the area will be listed but it is the best perhaps you can do.

A prepared list of names - if you were doing a study in a company then you could ask for a list of names that meet certain criteria to be prepared or of course you could ask for a list of everybody and then go though it excluding the ones who do not fit.

A collection of business cards that people have given you say at a product convention. This can often be useful because such cards give you lost of information.

Undefined list - this might occur if say you were sampling people booking into a hotel so you stand in the lobby and every time you see someone book in or out you ask if they will be willing to take part in your study so in a way you are defined the frame as the ones who agree. Here it would be unlikely the hotel management would give you access to their files but they might allow you to do it as I have described.

Well that probably gives you the idea but then you must think about how you choose people from the sample frame (list) and there are many ways to do this. Basically and Ideally, it would likely be best to do it randomly using a random number generator on your computer. So you number everyone on your list from say 1 to 500 (or however long the list is) and then if you want a sample of say 50 you ask the computer to generate 50 random numbers between 1 and 500.

WARNING - I strongly caution you not to try to think up your own randomisation process as more often than not they will bias the data. Be guided here and get it fixed in your memory that any process of selection that sounds remotely systematic is likely to add bias - tossing a coin sounds random but it has often been found that it lead to bias - be warned.

[Hawkeye]

Thought I would change direction a little and think about how you can present yourself in a CV and interview. Too often when you look up sites on how to do a CV they are a bit mechanical and don't always explain the foundations of a good CV. So Bill Hybels in his book "Courageous Leadership" marks out three elements he always looks for when employing someone and they are in order of importance: character, competence and chemistry.

Character - committed to: honesty, teachability, humility, reliability, persistence, punctuality, kindness, work ethic and a willingness to be entreated (told off or advised). Remember, lapses or failings in character are very hard to fix and almost impossible to do in an active team setting.

Competence - look for high skills in the area you want, go after proven competence. If someone is unhappy or if unemployed then wonder why.

Chemistry - a relation fit with members of the team, someone who has a positive emotional effect on the team - put simply it helps if you like each other in a team.

You have to take a good look at yourself when considering these qualities. You will know if you are honest, you will know if you have been lazy and uncaring, you will know if you have cheated or been unkind. Hybels said "It's a terribly lonely feeling to have no one to blame, look to no one to rescue you. It's rotten to realise that to find the bad guy, you just have to look in the mirror. The truth is that the only person who can sort you out is you. Anything else is a self-leadership fumble, an illusion."

In your CV you are trying to persuade someone of your worth and foremost in that is demonstrating your character. The value of character has been recognised from very ancient times and indeed Aristotle, some 2,500 years ago, said "Character may almost be called the most effective means of persuasion."

Now of course on a CV you cannot write down "I am honest and reliable" you have to demonstrate it. The way you do that is to say how you reacted to something. Suppose you worked in Burger King you might say something like:

Worked in Burger King for 18 months. During this time I leaned the essential value of team work and how important punctuality was coupled with helping each other during busy periods.

In this way you tell people what it is you have leaned and how your character has developed as well as giving an indication of your skills and of course you have also said something about chemistry. Very likely, the interview panel will follow this up and again it's an opportunity for you to show who you are and what you are really like. Now don't just copy what I have written because if you have any real character you will think through every job you have undertaken (no matter how small) and ask what it was you learned from it.

[Hawkeye]

Ethical Viewpoint
Ethics is about right and wrong and mostly manifests itself as questions about intention and outcome. If you like you have an intention to produce an outcome of some kind and so need to ask is that outcome right or wrong. It is very hard to compress ethics into a few lines and if you look you will find a huge number of books and papers on the subject.

In the modern world it is simply not possible to be dogmatic and say this is right and that is wrong although we see it everyday in religious writings. This is not to say we do not follow a particular religious persuasion but that is a personal choice and not every one holds to it. In any case no religious writing can possibly cover everything so it follows therefore Instead what we must do is construct arguments about what is ethically acceptable based on some empirical but agreed principles and nothing else will really do. Mary Warnock summed up these principles as follows:

Sympathy – that is when you decide and action you must think about (be sympathetic) to those that might be involved directly or indirectly.

Altruism (Unselfishness) – being ethical is not about satisfying your own position or your company and may mean sacrifice for you or others.

Imagination - this might sound like an odd idea but unless you use your imagination you will simply be unable to feel what it is like for anyone else or see what consequences there are. Without imagination you will just assume that the way you think is not only right but the only possible way so you will never appreciate the needs of others. In a very real way imagination underpins the whole of ethics.

These ideas are general; one might even say universal and as such might be usefully worked into organisational statements such as:

The requirement is for excellence with a distinct character related to a given organisation.

The standards and values relating to contractual, academic, financial and ethical considerations must be applied impartially everywhere and be of such a probity that they can be defended anywhere.

In general we start with accepted ethical principles as I have outlined above and then work out a set of ethical guidelines that are specific to an industry; so one can easily find, in the literature, books on computer usage ethics, ethics in law, ethics in medicine and so on.

[Hawkeye]

Emotional Intelligence
This is an area of interest at present because it offers a way for individuals to become more aware of themselves and others and hence make them in some sense more competent at their job. It is not entirely useful to try to define EI but Eaton and Johnson suggested it might be summarised as “the ability to inform our decisions with an understanding of our own and others’ emotions so that we can take productive action”.

EI literature talks about various emotional competences but we must not take this too far as then we end up as some sort of robot stoic, those who have no emotions at all, cannot feel another’s pain, or sympathize with another’s predicament, feel love or hate, joy or misery; who wants to be around people like that? The essential point is that emotionally we are all different and that is a strength; the fact is we all have emotional defects/strengths of one sort or another and we cannot get rid of/do not want to get rid of them but we can be AWARE of them and in some sense manage them and recognize them in others. For what it’s worth the literature usually defines 5 competences in this area but they are all essentially premised on the idea of a deep sense of self-awareness. These competences are essentially the variables in your study.

Self-Regulation - the management and control of one’s impulses and resources so as to regulate one’s self against impulsive actions, delaying instant gratification in order to remain focused.

Self-Awareness - or consciousness/sensitivity to our own emotional states and intuitions leading to recognition of their limitations and paradoxically therefore maximizing strengths.

Motivation – loosely these are emotional tendencies that facilitate the achievement of goals or you might think of it as a way of focusing internal energies and impulses on a mission to achieve excellence though any presented opportunity coupled with a considered inclination exploit them.

Empathy – strictly, this is to feel another’s pain by attuning our emotions to those of others so as to derive the knowledge and understanding of how and why other people feel, act and react the way they do in given situations, particularly when significant stress is involved.

Social Skills – enables the individual to “read” the intentions and actions of others and so adjust to or influence the operational ethos of groups so fitting into the mood, atmosphere and trust of the other team members.

[Hawkeye]

I will post later on the notion of 'common knowledge' but before I do that you need some simple definitions. To give them context think of yourself as writing a literature review and so you need to be aware of many things and that awareness should make you careful how you use other peoples work and how you construct and include thoughts of your own. With this in mind consider the following ideas.

Common Knowledge - If something is described as “common knowledge” it implies that many, if not most people know it. Such information does not belong to anyone person and it cannot normally be deduced, rather it has to be learned. It is probably talked about in several sources: the world is round; computers contain processors and memory, nothing goes faster than light are all examples of “common knowledge”. If it is common knowledge, you do not need to cite a source. Be careful because some authors will write down in their own work things that are common knowledge. In such cases, quoting them in that instance amounts to saying that a bit of what is common knowledge actually belongs to that author and that of course is an absurdity.

Obvious Knowledge - If something is described as “obvious” it implies that most people know it. Such information does not belong to anyone person but it can be discovered rationally or empirically. It is probably talked about in several sources: companies tend to grow; when the sun goes down it gets dark are all examples of “obvious knowledge”. If it is obvious you do not need to cite a source. Be careful because again some authors will write down the obvious in their own work. Quoting them in that instance amounts to saying that what is obvious to everyone actually belongs to that author and that of course is an absurdity.

Published Knowledge - Published knowledge refers to ideas and information that is found in a specific primary source which is not common or obvious knowledge but is nevertheless useful; in these cases you must always cite the source.

Original Knowledge - In any work you may include freely original ideas of your own. However, be aware that if a reader uncovers an idea that is not cited, is not common knowledge nor obvious, then they are entitled to believe that it is a new idea from you. If in fact this is not the case, then you will have plagiarised it, which is a serious academic offence. It follows that if you are introducing an idea of your own you should make it clear by the way it is presented that this is indeed your own work.

Identifying Plagiarism - Scholarship is about showing your understanding and criticism of ideas. It should be obvious that simply copying, paraphrasing or summarising, although it can show a limited understanding, fails to show any ability to criticise. You must "add value", that is make your own contribution to knowledge and you can usually only do this by both expressing published ideas in some way for yourself and also mingling them with your own thoughts and ideas.

Plagiarism is stealing ideas, even if you express the idea in your own words, (which is often good scholarship) you may still be guilty of plagiarism if you do not credit the source. Anyone can copy and paste a phrase, sentence or paragraph and cite its source and technically this is not plagiarism, it's often very poor scholarship since it is obvious that such an activity tells us nothing about the learning, if any, which occurred. For example and to exaggerate a little, supposed one copied in its entirety an essay from another student, giving it full attribution and then submitted it as your own work to the tutor – it is obvious this is not acceptable and it would be regarded as plagiarism because the perpetrator has done nothing that is unquestionably theirs. The same thing would apply if you copied into your work a quotation for example but then failed to introduce it or make any comments about it or show its validity in a given argument. Set against all that is a principle of usage of other people work and usage is the key to avoiding plagiarism – it was written by Goethe many years ago.

What is there is mine, and whether I got it from books or life is of no consequence, the only point is, whether I have made a right use of it.

If plagiarism occurs in your work, it will not matter if you say it was accidental, or you were just careless or you did not know how to do quote and cite correctly. It will still be regarded as a serious offence. It is hard to say exactly how to avoid plagiarism but in general the best way is to read widely, especially scholarly books and then you will gradually learn how it is done and that is in many ways this is the best teacher. Therefore, plagiarism is about two related things

Deliberate - attempting to make readers believe that what is presented is the student’s own work; cheating.

Ethics - trying to pass off another author’s work as if it was your own is both cheating and highly disrespectful and implies that you as a student do not know right from wrong.

[Hawkeye]

This is the first of a couple of posts on the notion of Common Sense. For those who want to go further I recommend the excellent book by Duncan Watts called "Everything is Obvious" (its also available as a eBook)

Common Sense
Roughly speaking, it is the loosely organized set of facts, observations, experiences, insights, and pieces of received wisdom that each of us accumulates over a lifetime, in the course of encountering, dealing with, and learning from, everyday situations. Beyond that, however, it tends to resist easy classification. There are perhaps two defining features of common sense that seem to differentiate it from other kinds of human knowledge, like that found in science or mathematics.

Practical - The first of these features is that unlike formal systems of knowledge, which are fundamentally theoretical, common sense is overwhelmingly practical, meaning that it is more concerned with providing answers to questions than in worrying about how it came by the answers. From the perspective of common sense, it is good enough to know that something is true, or that it is the way of things. One does not need to know why in order to benefit from the knowledge, and arguably one is better off not worrying about it too much.

Deals with things in its own terms - The second feature that differentiates common sense from formal knowledge is that while the power of formal systems resides in their ability to organise their specific findings into logical categories described by general principles, the power of common sense lies in its ability to deal with every concrete situation on its own terms. For example, it is a matter of common sense that what we wear or do or say in front of our boss will be different from how we behave in front of our friends, our parents, our parents' friends, or our friends’ parents. But whereas a formal system of knowledge would try to derive the appropriate behavior in all these situations from a single, more general “law," common sense just “knows” what is appropriate

In my next post I will elaborate on this and show that the notion of common sense can become unstable or even dangerous when we move it out of our day to day world, for which it is ideally suited, and try to use it to solve all and every problem.

[Hawkeye]

Some Further Observations on Common Sense
The fact that what is self evident to one person can be seen as totally silly by another person should make us pause about the reliability of common sense as a basis for understanding the world. How can we be confident that what we believe is right when someone else feels equally strongly that it’s wrong - especially when we can’t really articulate why we think we’re right in the first place without relying on dogma (its right because I say it is) or authority of some kind? Of course, we can always write them off as crazy or ignorant or stupid or something and therefore not worth paying attention to. But once you go down that road and we start to think for ourselves, it gets increasingly hard to account for why we ourselves believe what we do.

So if something that seemed so obvious turned out to be wrong, what else that we believe to be self-evident now will seem wrong to us in the future? Once we start to examine our own beliefs, in fact, it becomes increasingly unclear even how the various beliefs we espouse at any given time link together. Common sense, in other words, is not so much a world view but a rag bag of logically inconsistent, often contradictory beliefs, each of which seems right at the time but carries no guarantee of being right any other time.

How does common sense take us so far in the fragmented, inconsistent, and even self-contradictory our everyday lives? The reason is that everyday life is effectively broken up into small problems, grounded in very specific contexts that we can solve more or less independently of one another. Under these circumstances, being able to connect our thought processes in a logical manner isn't really the point.

Just a simple example, the electron can be regarded as a minuscule billiard ball for some calculations and a wave, a ripple for others. But common sense would say that is totally absurd, how can one thing be two different things at the same time? In short we must be wary of extending common sense beyond the everyday where it reigns supreme and therefore begin to think that our tiny minds, particularly our common sense, is the measure of all things.

[Hawkeye]

Before we get to our next note on common sense it is necessary to discuss the notion of certainty and I will create two post on this idea.

Be cautious with Certainty and Assurance.
One can often get into a position of certainty over your own knowledge; a kind of assurance that you have finally got there. Now this sounds wonderful and indeed it is nice to feel that you know and can do something well. The trouble is it can shut your mind down so reflecting from the standpoint of certitude allows no new meaning, no deeper understanding no surprises to emerge, indeed if you are certain you will implicitly tell yourself more or less that reflection is pointless because there is nothing new for you to learn.

It follows, that certitude may simply reinforce the way things are emotionally and intellectually so in that mindset reflection can become stale and unappealing and we rely on current experience and perspectives and so frustrate movement toward insight, or to put it more bluntly when something new comes along we “don’t want to know”. To counter this you need to always be on the lookout for new ideas and insights, they will not always be obvious, you do not have to swallow them wholesale but you do have to honestly chew them over, you have to be aware, seeing them as precious gifts aimed just at you, in this way you grow continually in knowledge, intelligence and emotional awareness and share what you have with others in your learning community.

It is tempting to avoid the idea of doubt because it can have negative connotations. But it is a way of thinking that is to be cherished because doubt, when you are not sure, drives you on to seek information and struggle until that doubt is removed – that is creative doubt. Doubt therefore is what brings you eventually to the truth, the answer. One might usefully recall what Dostoevsky in the Brothers Karamazov said “Without criticism there'd be nothing but Hosannas. But man cannot live by Hosannas alone, those Hosannas have to be tempered in the crucible of doubt..”

I will have more to say on this, but often we say to ourselves 'its common sense' and that invariably is dangerous because we tend not to look at it closely and just assume that our common sense will not let us down - a kind of intellectual arrogance that implicitly says 'I cannot be wrong but other are'. So beware. Finally, human beings have a inbuilt sense of logic but in practice that logic does not always work the way we classically define logic. You might see this easily if you remember the last time you bought something on impulse and you 'bent' the logic to justify it. Indeed, it is thought that human logic, or you can say your mind, works more like quantum mathematics where things act in what seem to be weird and inexplicable ways. So again be aware that YOUR logic, your mind may in fact be just that 'YOURS'.

If any one would like to explore this latter point it just so happens there is an article in New Scientist for September 3rd, 2011, Volume 211 No 2828 Page 34 called "Your Quantum Mind".

[Hawkeye]

Errors in Common Sense - There are three types of error.

1. Our Mental Model of individual behaviour is systemically flawed - When we think about why people do what they do, we invariably focus on factors like incentives, motivations, and beliefs, of which we are consciously aware. But this view of human behaviour is only the tip of the proverbial iceberg. For example, it may not occur to us that music playing in the background may influence our choice or even as simple a thing as the font in which the cover of a book is written my dispose up to buy it.

Often therefore, we don’t factor these apparently trivial or seemingly irrelevant factors into our thinking yet they do matter. The trouble is, it is probably impossible to anticipate everything that might be relevant to a given situation. The result is we make mistakes and we are likely to make even more serious mistakes when predicting how other people might behave anywhere outside of the immediate here and now.

2. Our mental model of collective behaviour is defective - the basic problem is that whenever people get together for whatever reason from dinner parties to sharing rumours and generally influencing one another’s perspectives about what is good and bad, cheap and expensive, right and wrong, these influences pile up in unexpected ways, generating collective behavior that is “emergent” in the sense that it cannot be understood solely in terms of its component parts.

Faced with such complexity, or “influencers" our explanations of collective behaviour paper over most of what is actually happening. Whenever something interesting, dramatic, or terrible happens-Hush Puppies become popular again, a book by an unknown author becomes an international best seller, the housing bubble bursts, or terrorists crash planes into the World Trade Center-we instinctively look for explanations.

3. In common sense reasoning we use less from history than we think we do - the misperception of the past skews our perception or predictions about the future. Whenever something interesting, dramatic, or terrible happens - Hush Puppies become popular again, a book by an unknown author becomes an international best seller, the housing bubble bursts, or terrorists crash planes into the World Trade Centre - we instinctively look for explanations.

Key Thought
Moreover, because we only try to explain events that strike us as sufficiently interesting, our explanations account only for a tiny fraction even of the things that do happen. The result is that what appear to us to be causal explanations are in fact just stories - descriptions of what happened that tell us little, if anything, about the mechanisms at work. Nevertheless, because these stories have the form of causal explanations, we treat them as if they have predictive power. In this way, we deceive ourselves into believing that we can make predictions that are impossible, even in principle. They create an illusion of understanding where we have papered over events with a plausible-sounding story. Common sense is wonderful at making sense of the world but not necessarily at understanding it.

The cost, however, is that we think we have understood things that in fact we have simply papered over with a plausible-sounding story. And because this illusion of understanding in turn undercuts our motivation to treat social problems the way we treat problems in medicine, engineering, and science, the unfortunate result is that common sense actually inhibits our understanding of the world.

The main point, though, is that just as an unquestioning belief in the correspondence between natural events and godly affairs had to give way in order for “real” explanations to be developed, so too, real explanations of the social world will require us to examine what it is about our common sense that misleads us into thinking that we know more than we do.

Implications
People digest new information in ways that tend to reinforce what they already think. In part, we do this by noticing information that confirms our existing beliefs more readily than information that does not. In part, we do it by subjecting disconfirming information to greater scrutiny and skepticism or tacitly ignoring it as obviously wrong than confirming information. Together, these two closely related tendencies-known as confirmation bias and motivated reasoning respectively, greatly impede our ability to resolve disputes, from petty disagreements over domestic duties to long-running political conflicts.

Even in science, confirmation bias and motivated reasoning play pemicious roles. Scientists, that is, are supposed to follow the evidence, even if it contradicts their own preexisting beliefs; and yet, more often than they should, they question the evidence instead. The result, as the physicist Max Planck famously acknowledged, is often that “A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die.