There are some minor differences between my and Martin Spaul's approach. As an example, I make less of a difference between question and hypothesis than Martin. I do that to make your life easier, as major mistakes from your part can be corrected in tutorials. If we want, however, to be precise, Martin's position is correcter: the hypothesis is a possible, now only guessed answer to the question.

You will find maybe some academic papers quite difficult to read. In such a case we should ask the question, if the given paper is difficult also when compared with other papers from the same field; if so, you should chose an easier paper from the same area. If you cannot make sense of any paper from an area, we should ask, if the area is too demanding for you. The answer to this question should not be given lightly; you are a student and as such, albeit on a low level, some sort of academic person, so you should demand from yourself to understand as much as possible. It is not acceptable if you are quite happy to put up with not anderstanding a thing of any academic paper of any academic area. You have to make some effort, at least out of self-respect.

A paper is not academic, if it does not have, explicitly or implicitly, all the following ingredients: question and eventually hypothesis, literature review, methodology, methodology strategy, findings, analysis and finally conclusions.

A hypothesis is a tentative answer to a question. You might find that in an article which is surely academic (the tutor says so), no question or hypothesis is spelled out. But if you really understand that article, the underlying question (and eventually hypothesis) becomes apparent to you.
You might be surprised by how modest the question is, and how much effort an intelligent author puts into answering that tiny question. This is so, because the answer is very thorough; if you are supposed to be that thorough, you cannot answer quite general questions. So why does every academic author have to be that thorough? Every such author (and you should too during your dissertation) imagines that the readers of his work try very hard to find mistakes and weaknesses in his work. An academic reader has, indeed, the duty to try to find mistakes in every article.
You might also be surprised by how precise the question or hypothesis is. This should be an example to you when you'll try later to find your own hypothesis.

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Everybody is probably of the opinion that re-inventing the wheel is something stupid to do. In an academic area this means that no serious author tries to say what has already been said. So in order to know what has previously been said, our author has to read quite a lot in his own area.
He would also like to use results proven in the the past by other authors.
All this process has to be made transparent, so our author describes in his own article what other people have said, so that he can locate the starting point of his own research and set the standards against which he would measure his own results.

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The methodology represents the self-imposed restrictions under which the author intended to answer his hypothesis. These self-imposed restrictions insure that the author's answer is a pertinent and not a whimsical one.
You can find more on methodology in the page dedicated to this matter.
A sure way of deciding whether a paper is academic is to find out how stringent the used methodology is. You can learn a lot from such articles for your own methodology chapters both in this module assignment and in your dissertation.

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Every academic paper has a methodology strategy. This refers to the ways in which the author wants to apply his chosen methods. Also a well chosen methodology can be applied carelessly; that would seriously endanger the the whole research as the results cannot then be taken seriously by any academic reader.

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The raw data elicited by the practical investigation of our author are called findings.
Sometimes the methodology strategy and the findings appear in a single chapter called data gathering.

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The interpretation of the raw data by any means (statistical or otherwise) is called analysis. This is the corner stone of the author's original contribution to knowledge through his article. This analysis makes evident whether the hypothesis is confirmed or invalidated.

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The conclusions sum up in a critical overview the results presented in the analysis chapter as an answer to the hypothesis in contrast to the author's initial intentions and expectations as presented in the introduction.

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