What it does:
The Independent Samples T Test compares the mean scores of two groups on a given variable.
Where to find it:
Under the Analyze menu, choose Compare Means, the Independent Samples T Test. Move your dependent variable into the box marked "Test Variable." Move your independent variable into the box marked "Grouping Variable." Click on the box marked "Define Groups" and specify the value labels of the two groups you wish to compare.
Assumptions:
-The dependent variable is normally distributed. You can check for normal distribution with a Q-Q plot.
-The two groups have approximately equal variance on the dependent variable. You can check this by looking at the Levene's Test. See below.
-The two groups are independent of one another.
Hypotheses:
Null: The means of the two groups are not significantly different.
Alternate: The means of the two groups are significantly different.
SPSS Output
Following is a sample output of an independent samples T test. We compared the mean blood pressure of patients who received a new drug treatment vs. those who received a placebo (a sugar pill).
First, we see the descriptive statistics for the two groups. We see that the mean for the "New Drug" group is higher than that of the "Placebo" group. That is, people who received the new drug have, on average, higher blood pressure than those who took the placebo.
Next, we see the Levene's Test for Equality of Variances. This tells us if we have met our second assumption (the two groups have approximately equal variance on the dependent variable). If the Levene's Test is significant (the value under "Sig." is less than .05), the two variances are significantly different. If it is not significant (Sig. is greater than .05), the two variances are not significantly different; that is, the two variances are approximately equal. If the Levene's test is not significant, we have met our second assumption. Here, we see that the significance is .448, which is greater than .05. We can assume that the variances are approximately equal.
Finally, we see the results of the Independent Samples T Test. Read the TOP line if the variances are approximately equal. Read the BOTTOM line if the variances are not equal. Based on the results of our Levene's test, we know that we have approximately equal variance, so we will read the top line.
Our T value is 3.796.
We have 10 degrees of freedom.
There is a significant difference between the two groups (the significance is less than .05).
Therefore, we can say that there is a significant difference between the New Drug and Placebo groups. People who took the new drug had significantly higher blood pressure than those who took the placebo.
Source: http://www.wellesley.edu/Psychology/Psych205/indepttest.html
The virtual community for post graduate students of Open University Malaysia updated by Dr Richard Ng
Tuesday, December 22, 2009
Friday, December 18, 2009
A suggested thesis structure
The list of contents and chapter headings below is appropriate for some theses. In some cases, one or two of them may be irrelevant. Results and Discussion are usually combined in several chapters of a thesis. Think about the plan of chapters and decide what is best to report your work. Then make a list, in point form, of what will go in each chapter. Try to make this rather detailed, so that you end up with a list of points that corresponds to subsections or even to the paragraphs of your thesis. At this stage, think hard about the logic of the presentation: within chapters, it is often possible to present the ideas in different order, and not all arrangements will be equally easy to follow. If you make a plan of each chapter and section before you sit down to write, the result will probably be clearer and easier to read. It will also be easier to write.
Copyright waiver
Your institution may have a form for this (UNSW does). In any case, this standard page gives the university library the right to publish the work, possibly by microfilm or other medium. (At UNSW, the Postgraduate Student Office will give you a thesis pack with various guide-lines and rules about thesis format. Make sure that you consult that for its formal requirements, as well as this rather informal guide.)
Declaration
Check the wording required by your institution, and whether there is a standard form. Many universities require something like: "I hereby declare that this submission is my own work and that, to the best of my knowledge and belief, it contains no material previously published or written by another person nor material which to a substantial extent has been accepted for the award of any other degree or diploma of the university or other institute of higher learning, except where due acknowledgment has been made in the text. (signature/name/date)"
Title page
This may vary among institutions, but as an example: Title/author/"A thesis submitted for the degree of Doctor of Philosophy in the Faculty of Science/The University of New South Wales"/date.
Abstract
Of all your thesis, this part will be the most widely published and most read because it will be published in Dissertation Abstracts International. It is best written towards the end, but not at the very last minute because you will probably need several drafts. It should be a distillation of the thesis: a concise description of the problem(s) addressed, your method of solving it/them, your results and conclusions. An abstract must be self-contained. Usually they do not contain references. When a reference is necessary, its details should be included in the text of the abstract. Check the word limit. Remember: even though it appears at the beginning, an abstract is not an introduction. It is a résumé of your thesis.
Acknowledgments
Most thesis authors put in a page of thanks to those who have helped them in matters scientific, and also indirectly by providing such essentials as food, education, genes, money, help, advice, friendship etc. If any of your work is collaborative, you should make it quite clear who did which sections.
Table of contents
The introduction starts on page 1, the earlier pages should have roman numerals. It helps to have the subheadings of each chapter, as well as the chapter titles. Remember that the thesis may be used as a reference in the lab, so it helps to be able to find things easily.
Introduction
What is the topic and why is it important? State the problem(s) as simply as you can. Remember that you have been working on this project for a few years, so you will be very close to it. Try to step back mentally and take a broader view of the problem. How does it fit into the broader world of your discipline?
Especially in the introduction, do not overestimate the reader's familiarity with your topic. You are writing for researchers in the general area, but not all of them need be specialists in your particular topic. It may help to imagine such a person---think of some researcher whom you might have met at a conference for your subject, but who was working in a different area. S/he is intelligent, has the same general background, but knows little of the literature or tricks that apply to your particular topic.
The introduction should be interesting. If you bore the reader here, then you are unlikely to revive his/her interest in the materials and methods section. For the first paragraph or two, tradition permits prose that is less dry than the scientific norm. If want to wax lyrical about your topic, here is the place to do it. Try to make the reader want to read the heavy bundle that has arrived uninvited on his/her desk. Go to the library and read several thesis introductions. Did any make you want to read on? Which ones were boring?
This section might go through several drafts to make it read well and logically, while keeping it short. For this section, I think that it is a good idea to ask someone who is not a specialist to read it and to comment. Is it an adequate introduction? Is it easy to follow? There is an argument for writing this section---or least making a major revision of it---towards the end of the thesis writing. Your introduction should tell where the thesis is going, and this may become clearer during the writing.
Literature review
Where did the problem come from? What is already known about this problem? What other methods have been tried to solve it?
Ideally, you will already have much of the hard work done, if you have been keeping up with the literature as you vowed to do three years ago, and if you have made notes about important papers over the years. If you have summarised those papers, then you have some good starting points for the review.
If you didn't keep your literature notes up to date, you can still do something useful: pass on the following advice to any beginning PhD students in your lab and tell them how useful this would have been to you. When you start reading about a topic, you should open a spread sheet file, or at least a word processor file, for your literature review. Of course you write down the title, authors, year, volume and pages. But you also write a summary (anything from a couple of sentences to a couple of pages, depending on the relevance). In other columns of the spread sheet, you can add key words (your own and theirs) and comments about its importance, relevance to you and its quality.
How many papers? How relevant do they have to be before you include them? Well, that is a matter of judgement. On the order of a hundred is reasonable, but it will depend on the field. You are the world expert on the (narrow) topic of your thesis: you must demonstrate this.
A political point: make sure that you do not omit relevant papers by researchers who are like to be your examiners, or by potential employers to whom you might be sending the thesis in the next year or two.
Middle chapters
In some theses, the middle chapters are the journal articles of which the student was major author. There are several disadvantages to this format.
One is that a thesis is both allowed and expected to have more detail than a journal article. For journal articles, one usually has to reduce the number of figures. In many cases, all of the interesting and relevant data can go in the thesis, and not just those which appeared in the journal. The degree of experimental detail is usually greater in a thesis. Relatively often a researcher requests a thesis in order to obtain more detail about how a study was performed.
Another disadvantage is that your journal articles may have some common material in the introduction and the "Materials and Methods" sections.
The exact structure in the middle chapters will vary among theses. In some theses, it is necessary to establish some theory, to describe the experimental techniques, then to report what was done on several different problems or different stages of the problem, and then finally to present a model or a new theory based on the new work. For such a thesis, the chapter headings might be: Theory, Materials and Methods, {first problem}, {second problem}, {third problem}, {proposed theory/model} and then the conclusion chapter. For other theses, it might be appropriate to discuss different techniques in different chapters, rather than to have a single Materials and Methods chapter.
Here follow some comments on the elements Materials and Methods, Theory, Results and discussion which may or may not correspond to thesis chapters.
Materials and Methods
This varies enormously from thesis to thesis, and may be absent in theoretical theses. It should be possible for a competent researcher to reproduce exactly what you have done by following your description. There is a good chance that this test will be applied: sometime after you have left, another researcher will want to do a similar experiment either with your gear, or on a new set-up in a foreign country. Please write for the benefit of that researcher.
In some theses, particularly multi-disciplinary or developmental ones, there may be more than one such chapter. In this case, the different disciplines should be indicated in the chapter titles.
Theory
When you are reporting theoretical work that is not original, you will usually need to include sufficient material to allow the reader to understand the arguments used and their physical bases. Sometimes you will be able to present the theory ab initio, but you should not reproduce two pages of algebra that the reader could find in a standard text. Do not include theory that you are not going to relate to the work you have done.
When writing this section, concentrate at least as much on the physical arguments as on the equations. What do the equations mean? What are the important cases?
When you are reporting your own theoretical work, you must include rather more detail, but you should consider moving lengthy derivations to appendices. Think too about the order and style of presentation: the order in which you did the work may not be the clearest presentation.
Suspense is not necessary in reporting science: you should tell the reader where you are going before you start.
Results and discussion
The results and discussion are very often combined in theses. This is sensible because of the length of a thesis: you may have several chapters of results and, if you wait till they are all presented before you begin discussion, the reader may have difficulty remembering what you are talking about. The division of Results and Discussion material into chapters is usually best done according to subject matter.
Make sure that you have described the conditions which obtained for each set of results. What was held constant? What were the other relevant parameters? Make sure too that you have used appropriate statistical analyses. Where applicable, show measurement errors and standard errors on the graphs. Use appropriate statistical tests.
Take care plotting graphs. The origin and intercepts are often important so, unless the ranges of your data make it impractical, the zeros of one or both scales should usually appear on the graph. You should show error bars on the data, unless the errors are very small. For single measurements, the bars should be your best estimate of the experimental errors in each coordinate. For multiple measurements these should include the standard error in the data. The errors in different data are often different, so, where this is the case, regressions and fits should be weighted (i.e. they should minimize the sum of squares of the differences weighted inversely as the size of the errors.) (A common failing in many simple software packages that draw graphs and do regressions is that they do not treat errors adequately. UNSW student Mike Johnston has written a plotting routine that plots data with error bars and performs weighted least square regressions. It is at http://www.phys.unsw.edu.au/3rdyearlab/graphing/graph.html). You can just 'paste' your data into the input and it generates a .ps file of the graph.
In most cases, your results need discussion. What do they mean? How do they fit into the existing body of knowledge? Are they consistent with current theories? Do they give new insights? Do they suggest new theories or mechanisms?
Try to distance yourself from your usual perspective and look at your work. Do not just ask yourself what it means in terms of the orthodoxy of your own research group, but also how other people in the field might see it. Does it have any implications that do not relate to the questions that you set out to answer?
Final chapter, references and appendices
Conclusions and suggestions for further work
Your abstract should include your conclusions in very brief form, because it must also include some other material. A summary of conclusions is usually longer than the final section of the abstract, and you have the space to be more explicit and more careful with qualifications. You might find it helpful to put your conclusions in point form.
It is often the case with scientific investigations that more questions than answers are produced. Does your work suggest any interesting further avenues? Are there ways in which your work could be improved by future workers? What are the practical implications of your work?
This chapter should usually be reasonably short---a few pages perhaps. As with the introduction, I think that it is a good idea to ask someone who is not a specialist to read this section and to comment.
References (See also under literature review)
It is tempting to omit the titles of the articles cited, and the university allows this, but think of all the times when you have seen a reference in a paper and gone to look it up only to find that it was not helpful after all.
Should you reference web sites and, if so, how? If you cite a journal article or book, the reader can go to a library and check that the cited document and check whether or not it says what you say it did. A web site may disappear, and it may have been updated or changed completely. So references to the web are usually less satisfactory. Nevertheless, there are some very useful and authoritative sources. So, if the rules of your institution permit it, it may be appropriate to cite web sites. (Be cautious, and don't overuse such citations. In particular, don't use a web citation where you could reasonably use a "hard" citation. Remember that your examiners are likely to be older and more conservative.) You should give the URL and also the date you downloaded it. If there is a date on the site itself (last updated on .....) you should included that, too.
Appendices
If there is material that should be in the thesis but which would break up the flow or bore the reader unbearably, include it as an appendix. Some things which are typically included in appendices are: important and original computer programs, data files that are too large to be represented simply in the results chapters, pictures or diagrams of results which are not important enough to keep in the main text.
Source: http://phys.unsw.edu.au/~jw/thesis.html
Copyright waiver
Your institution may have a form for this (UNSW does). In any case, this standard page gives the university library the right to publish the work, possibly by microfilm or other medium. (At UNSW, the Postgraduate Student Office will give you a thesis pack with various guide-lines and rules about thesis format. Make sure that you consult that for its formal requirements, as well as this rather informal guide.)
Declaration
Check the wording required by your institution, and whether there is a standard form. Many universities require something like: "I hereby declare that this submission is my own work and that, to the best of my knowledge and belief, it contains no material previously published or written by another person nor material which to a substantial extent has been accepted for the award of any other degree or diploma of the university or other institute of higher learning, except where due acknowledgment has been made in the text. (signature/name/date)"
Title page
This may vary among institutions, but as an example: Title/author/"A thesis submitted for the degree of Doctor of Philosophy in the Faculty of Science/The University of New South Wales"/date.
Abstract
Of all your thesis, this part will be the most widely published and most read because it will be published in Dissertation Abstracts International. It is best written towards the end, but not at the very last minute because you will probably need several drafts. It should be a distillation of the thesis: a concise description of the problem(s) addressed, your method of solving it/them, your results and conclusions. An abstract must be self-contained. Usually they do not contain references. When a reference is necessary, its details should be included in the text of the abstract. Check the word limit. Remember: even though it appears at the beginning, an abstract is not an introduction. It is a résumé of your thesis.
Acknowledgments
Most thesis authors put in a page of thanks to those who have helped them in matters scientific, and also indirectly by providing such essentials as food, education, genes, money, help, advice, friendship etc. If any of your work is collaborative, you should make it quite clear who did which sections.
Table of contents
The introduction starts on page 1, the earlier pages should have roman numerals. It helps to have the subheadings of each chapter, as well as the chapter titles. Remember that the thesis may be used as a reference in the lab, so it helps to be able to find things easily.
Introduction
What is the topic and why is it important? State the problem(s) as simply as you can. Remember that you have been working on this project for a few years, so you will be very close to it. Try to step back mentally and take a broader view of the problem. How does it fit into the broader world of your discipline?
Especially in the introduction, do not overestimate the reader's familiarity with your topic. You are writing for researchers in the general area, but not all of them need be specialists in your particular topic. It may help to imagine such a person---think of some researcher whom you might have met at a conference for your subject, but who was working in a different area. S/he is intelligent, has the same general background, but knows little of the literature or tricks that apply to your particular topic.
The introduction should be interesting. If you bore the reader here, then you are unlikely to revive his/her interest in the materials and methods section. For the first paragraph or two, tradition permits prose that is less dry than the scientific norm. If want to wax lyrical about your topic, here is the place to do it. Try to make the reader want to read the heavy bundle that has arrived uninvited on his/her desk. Go to the library and read several thesis introductions. Did any make you want to read on? Which ones were boring?
This section might go through several drafts to make it read well and logically, while keeping it short. For this section, I think that it is a good idea to ask someone who is not a specialist to read it and to comment. Is it an adequate introduction? Is it easy to follow? There is an argument for writing this section---or least making a major revision of it---towards the end of the thesis writing. Your introduction should tell where the thesis is going, and this may become clearer during the writing.
Literature review
Where did the problem come from? What is already known about this problem? What other methods have been tried to solve it?
Ideally, you will already have much of the hard work done, if you have been keeping up with the literature as you vowed to do three years ago, and if you have made notes about important papers over the years. If you have summarised those papers, then you have some good starting points for the review.
If you didn't keep your literature notes up to date, you can still do something useful: pass on the following advice to any beginning PhD students in your lab and tell them how useful this would have been to you. When you start reading about a topic, you should open a spread sheet file, or at least a word processor file, for your literature review. Of course you write down the title, authors, year, volume and pages. But you also write a summary (anything from a couple of sentences to a couple of pages, depending on the relevance). In other columns of the spread sheet, you can add key words (your own and theirs) and comments about its importance, relevance to you and its quality.
How many papers? How relevant do they have to be before you include them? Well, that is a matter of judgement. On the order of a hundred is reasonable, but it will depend on the field. You are the world expert on the (narrow) topic of your thesis: you must demonstrate this.
A political point: make sure that you do not omit relevant papers by researchers who are like to be your examiners, or by potential employers to whom you might be sending the thesis in the next year or two.
Middle chapters
In some theses, the middle chapters are the journal articles of which the student was major author. There are several disadvantages to this format.
One is that a thesis is both allowed and expected to have more detail than a journal article. For journal articles, one usually has to reduce the number of figures. In many cases, all of the interesting and relevant data can go in the thesis, and not just those which appeared in the journal. The degree of experimental detail is usually greater in a thesis. Relatively often a researcher requests a thesis in order to obtain more detail about how a study was performed.
Another disadvantage is that your journal articles may have some common material in the introduction and the "Materials and Methods" sections.
The exact structure in the middle chapters will vary among theses. In some theses, it is necessary to establish some theory, to describe the experimental techniques, then to report what was done on several different problems or different stages of the problem, and then finally to present a model or a new theory based on the new work. For such a thesis, the chapter headings might be: Theory, Materials and Methods, {first problem}, {second problem}, {third problem}, {proposed theory/model} and then the conclusion chapter. For other theses, it might be appropriate to discuss different techniques in different chapters, rather than to have a single Materials and Methods chapter.
Here follow some comments on the elements Materials and Methods, Theory, Results and discussion which may or may not correspond to thesis chapters.
Materials and Methods
This varies enormously from thesis to thesis, and may be absent in theoretical theses. It should be possible for a competent researcher to reproduce exactly what you have done by following your description. There is a good chance that this test will be applied: sometime after you have left, another researcher will want to do a similar experiment either with your gear, or on a new set-up in a foreign country. Please write for the benefit of that researcher.
In some theses, particularly multi-disciplinary or developmental ones, there may be more than one such chapter. In this case, the different disciplines should be indicated in the chapter titles.
Theory
When you are reporting theoretical work that is not original, you will usually need to include sufficient material to allow the reader to understand the arguments used and their physical bases. Sometimes you will be able to present the theory ab initio, but you should not reproduce two pages of algebra that the reader could find in a standard text. Do not include theory that you are not going to relate to the work you have done.
When writing this section, concentrate at least as much on the physical arguments as on the equations. What do the equations mean? What are the important cases?
When you are reporting your own theoretical work, you must include rather more detail, but you should consider moving lengthy derivations to appendices. Think too about the order and style of presentation: the order in which you did the work may not be the clearest presentation.
Suspense is not necessary in reporting science: you should tell the reader where you are going before you start.
Results and discussion
The results and discussion are very often combined in theses. This is sensible because of the length of a thesis: you may have several chapters of results and, if you wait till they are all presented before you begin discussion, the reader may have difficulty remembering what you are talking about. The division of Results and Discussion material into chapters is usually best done according to subject matter.
Make sure that you have described the conditions which obtained for each set of results. What was held constant? What were the other relevant parameters? Make sure too that you have used appropriate statistical analyses. Where applicable, show measurement errors and standard errors on the graphs. Use appropriate statistical tests.
Take care plotting graphs. The origin and intercepts are often important so, unless the ranges of your data make it impractical, the zeros of one or both scales should usually appear on the graph. You should show error bars on the data, unless the errors are very small. For single measurements, the bars should be your best estimate of the experimental errors in each coordinate. For multiple measurements these should include the standard error in the data. The errors in different data are often different, so, where this is the case, regressions and fits should be weighted (i.e. they should minimize the sum of squares of the differences weighted inversely as the size of the errors.) (A common failing in many simple software packages that draw graphs and do regressions is that they do not treat errors adequately. UNSW student Mike Johnston has written a plotting routine that plots data with error bars and performs weighted least square regressions. It is at http://www.phys.unsw.edu.au/3rdyearlab/graphing/graph.html). You can just 'paste' your data into the input and it generates a .ps file of the graph.
In most cases, your results need discussion. What do they mean? How do they fit into the existing body of knowledge? Are they consistent with current theories? Do they give new insights? Do they suggest new theories or mechanisms?
Try to distance yourself from your usual perspective and look at your work. Do not just ask yourself what it means in terms of the orthodoxy of your own research group, but also how other people in the field might see it. Does it have any implications that do not relate to the questions that you set out to answer?
Final chapter, references and appendices
Conclusions and suggestions for further work
Your abstract should include your conclusions in very brief form, because it must also include some other material. A summary of conclusions is usually longer than the final section of the abstract, and you have the space to be more explicit and more careful with qualifications. You might find it helpful to put your conclusions in point form.
It is often the case with scientific investigations that more questions than answers are produced. Does your work suggest any interesting further avenues? Are there ways in which your work could be improved by future workers? What are the practical implications of your work?
This chapter should usually be reasonably short---a few pages perhaps. As with the introduction, I think that it is a good idea to ask someone who is not a specialist to read this section and to comment.
References (See also under literature review)
It is tempting to omit the titles of the articles cited, and the university allows this, but think of all the times when you have seen a reference in a paper and gone to look it up only to find that it was not helpful after all.
Should you reference web sites and, if so, how? If you cite a journal article or book, the reader can go to a library and check that the cited document and check whether or not it says what you say it did. A web site may disappear, and it may have been updated or changed completely. So references to the web are usually less satisfactory. Nevertheless, there are some very useful and authoritative sources. So, if the rules of your institution permit it, it may be appropriate to cite web sites. (Be cautious, and don't overuse such citations. In particular, don't use a web citation where you could reasonably use a "hard" citation. Remember that your examiners are likely to be older and more conservative.) You should give the URL and also the date you downloaded it. If there is a date on the site itself (last updated on .....) you should included that, too.
Appendices
If there is material that should be in the thesis but which would break up the flow or bore the reader unbearably, include it as an appendix. Some things which are typically included in appendices are: important and original computer programs, data files that are too large to be represented simply in the results chapters, pictures or diagrams of results which are not important enough to keep in the main text.
Source: http://phys.unsw.edu.au/~jw/thesis.html
Thursday, December 17, 2009
ISODEL 2009 - Parallel Session
The ISODEL 2009 conference which was held in Jogyakarta from 8 Dec to 11 Dec at the Sheraton Hotel, witnessed 55 speakers presenting their papers.
Prof. Mansor during his slide presentation
Among the speakers are Senior VP of OUM ,Prof. Dr. Mansor Fadzil, Richard Ng (Director of OUM Perak Learning Centre), Tuan Fatma, Rozeman (Senior Lecturers of OUM) and Mohd Jamaluddin (Head of Counseling Unit).
Presentation by Richard Ng
Prof. Mansor's session was slotted on the second parallel session from 3pm - 4.30pm. For the benefit of readers, I have posted the video clips of Prof. Mansor's presentation in 2 parts as follows:
Video clip part 1:
Video clip part 2:
The following are video clips in three parts of the presentation by Richard Ng:
Video clip part 1:
Video clip part 2:
Video clip part 3:
Prof. Mansor during his slide presentation
Among the speakers are Senior VP of OUM ,Prof. Dr. Mansor Fadzil, Richard Ng (Director of OUM Perak Learning Centre), Tuan Fatma, Rozeman (Senior Lecturers of OUM) and Mohd Jamaluddin (Head of Counseling Unit).
Presentation by Richard Ng
Prof. Mansor's session was slotted on the second parallel session from 3pm - 4.30pm. For the benefit of readers, I have posted the video clips of Prof. Mansor's presentation in 2 parts as follows:
Video clip part 1:
Video clip part 2:
The following are video clips in three parts of the presentation by Richard Ng:
Video clip part 1:
Video clip part 2:
Video clip part 3:
Wednesday, December 16, 2009
ISODEL 2009 - Plenary session by YBhg Tan Sri Anuwar Ali
YBhg Prof. Emeritus Tan Sri Anuwar Ali, President and Vice Chancellor of OUM was among the plenary speakers on Day 3 of the ISODEL 2009 in Jogyakarta.
Plenary speakers during the ISODEL 2009 in Jogyakarta
Other speakers include Fasli Djalal (Director General of Higher Education, MONE, Indonesia), Tian Belawati (President of AAOU) and Ronald Perkinson (Sampoerna School of Education).
The topic of YBhg Tan Sri's presentation was "International Outreach in Open, Distance E-Learning: The experience of Open University Malaysia". The session began with a short presentation of the speaker. See video clip Part 1 below.
For the benefit of the readers of this blog, I have posted video clips of YBhg Tan Sri's presentation here in four parts:
Part 1:
Part 2:
Part 3:
Part 4:
Part 5 - Question and Answer session:
Plenary speakers during the ISODEL 2009 in Jogyakarta
Other speakers include Fasli Djalal (Director General of Higher Education, MONE, Indonesia), Tian Belawati (President of AAOU) and Ronald Perkinson (Sampoerna School of Education).
The topic of YBhg Tan Sri's presentation was "International Outreach in Open, Distance E-Learning: The experience of Open University Malaysia". The session began with a short presentation of the speaker. See video clip Part 1 below.
For the benefit of the readers of this blog, I have posted video clips of YBhg Tan Sri's presentation here in four parts:
Part 1:
Part 2:
Part 3:
Part 4:
Part 5 - Question and Answer session:
Tuesday, December 1, 2009
Structural Equation Modeling
A Conceptual Overview
Structural Equation Modeling is a very general, very powerful multivariate analysis technique that includes specialized versions of a number of other analysis methods as special cases. We will assume that you are familiar with the basic logic of statistical reasoning as described in Elementary Concepts. Moreover, we will also assume that you are familiar with the concepts of variance, covariance, and correlation; if not, we advise that you read the Basic Statistics section at this point. Although it is not absolutely necessary, it is highly desirable that you have some background in factor analysis before attempting to use structural modeling.
Major applications of structural equation modeling include:
1. causal modeling, or path analysis, which hypothesizes causal relationships among variables and tests the causal models with a linear equation system. Causal models can involve either manifest variables, latent variables, or both;
2. confirmatory factor analysis, an extension of factor analysis in which specific hypotheses about the structure of the factor loadings and intercorrelations are tested;
3. second order factor analysis, a variation of factor analysis in which the correlation matrix of the common factors is itself factor analyzed to provide second order factors;
4. regression models, an extension of linear regression analysis in which regression weights may be constrained to be equal to each other, or to specified numerical values;
5. covariance structure models, which hypothesize that a covariance matrix has a particular form. For example, you can test the hypothesis that a set of variables all have equal variances with this procedure;
6. correlation structure models, which hypothesize that a correlation matrix has a particular form. A classic example is the hypothesis that the correlation matrix has the structure of a circumplex (Guttman, 1954; Wiggins, Steiger, & Gaelick, 1981).
Many different kinds of models fall into each of the above categories, so structural modeling as an enterprise is very difficult to characterize.
Most structural equation models can be expressed as path diagrams. Consequently even beginners to structural modeling can perform complicated analyses with a minimum of training.
To index
The Basic Idea Behind Structural Modeling
One of the fundamental ideas taught in intermediate applied statistics courses is the effect of additive and multiplicative transformations on a list of numbers. Students are taught that, if you multiply every number in a list by some constant K, you multiply the mean of the numbers by K. Similarly, you multiply the standard deviation by the absolute value of K.
For example, suppose you have the list of numbers 1,2,3. These numbers have a mean of 2 and a standard deviation of 1. Now, suppose you were to take these 3 numbers and multiply them by 4. Then the mean would become 8, and the standard deviation would become 4, the variance thus 16.
The point is, if you have a set of numbers X related to another set of numbers Y by the equation Y = 4X, then the variance of Y must be 16 times that of X, so you can test the hypothesis that Y and X are related by the equation Y = 4X indirectly by comparing the variances of the Y and X variables.
This idea generalizes, in various ways, to several variables inter-related by a group of linear equations. The rules become more complex, the calculations more difficult, but the basic message remains the same -- you can test whether variables are interrelated through a set of linear relationships by examining the variances and covariances of the variables.
Statisticians have developed procedures for testing whether a set of variances and covariances in a covariance matrix fits a specified structure. The way structural modeling works is as follows:
1. You state the way that you believe the variables are inter-related, often with the use of a path diagram.
2. You work out, via some complex internal rules, what the implications of this are for the variances and covariances of the variables.
3. You test whether the variances and covariances fit this model of them.
4. Results of the statistical testing, and also parameter estimates and standard errors for the numerical coefficients in the linear equations are reported.
5. On the basis of this information, you decide whether the model seems like a good fit to your data.
There are some important, and very basic logical points to remember about this process. First, although the mathematical machinery required to perform structural equations modeling is extremely complicated, the basic logic is embodied in the above 5 steps. Below, we diagram the process.
Second, we must remember that it is unreasonable to expect a structural model to fit perfectly — for a number of reasons. A structural model with linear relations is only an approximation. The world is unlikely to be linear. Indeed, the true relations between variables are probably nonlinear. Moreover, many of the statistical assumptions are somewhat questionable as well. The real question is not so much, "Does the model fit perfectly?" but rather, "Does it fit well enough to be a useful approximation to reality, and a reasonable explanation of the trends in our data?"
Third, we must remember that simply because a model fits the data well does not mean that the model is necessarily correct. One cannot prove that a model is true — to assert this is the fallacy of affirming the consequent. For example, we could say "If Joe is a cat, Joe has hair." However, "Joe has hair" does not imply Joe is a cat. Similarly, we can say that "If a certain causal model is true, it will fit the data." However, the model fitting the data does not necessarily imply the model is the correct one. There may be another model that fits the data equally well.
To index
Structural Equation Modeling and the Path Diagram
Path Diagrams play a fundamental role in structural modeling. Path diagrams are like flowcharts. They show variables interconnected with lines that are used to indicate causal flow.
One can think of a path diagram as a device for showing which variables cause changes in other variables. However, path diagrams need not be thought of strictly in this way. They may also be given a narrower, more specific interpretation.
Consider the classic linear regression equation
Y = aX + e
Any such equation may be represented in a path diagram as follows:
Such diagrams establish a simple isomorphism. All variables in the equation system are placed in the diagram, either in boxes or ovals. Each equation is represented on the diagram as follows: All independent variables (the variables on the right side of an equation) have arrows pointing to the dependent variable. The weighting coefficient is placed above the arrow. The above diagram shows a simple linear equation system and its path diagram representation.
Notice that, besides representing the linear equation relationships with arrows, the diagrams also contain some additional aspects. First, the variances of the independent variables, which we must know in order to test the structural relations model, are shown on the diagrams using curved lines without arrowheads attached. We refer to such lines as wires. Second, some variables are represented in ovals, others in rectangular boxes. Manifest variables are placed in boxes in the path diagram. Latent variables are placed in an oval or circle. For example, the variable E in the above diagram can be thought of as a linear regression residual when Y is predicted from X. Such a residual is not observed directly, but calculated from Y and X, so we treat it as a latent variable and place it in an oval.
The example discussed above is an extremely simple one. Generally, we are interested in testing models that are much more complicated than these. As the equation systems we examine become increasingly complicated, so do the covariance structures they imply. Ultimately, the complexity can become so bewildering that we lose sight of some very basic principles. For one thing the train of reasoning which supports testing causal models with linear structural equations testing has several weak links. The variables may be non-linear. They may be linearly related for reasons unrelated to what we commonly view as causality. The ancient adage, "correlation is not causation" remains true, even if the correlation is complex and multivariate. What causal modeling does allow us to do is examine the extent to which data fail to agree with one reasonably viable consequence of a model of causality. If the linear equations system isomorphic to the path diagram does fit the data well, it is encouraging, but hardly proof of the truth of the causal model.
Although path diagrams can be used to represent causal flow in a system of variables, they need not imply such a causal flow. Such diagrams may be viewed as simply an isomorphic representation of a linear equations system. As such, they can convey linear relationships when no causal relations are assumed. Hence, although one might interpret the diagram in the above figure to mean that "X causes Y," the diagram can also be interpreted as a visual representation of the linear regression relationship between X and Y.
Source: http://www.statsoft.com/TEXTBOOK/stsepath.html
Structural Equation Modeling is a very general, very powerful multivariate analysis technique that includes specialized versions of a number of other analysis methods as special cases. We will assume that you are familiar with the basic logic of statistical reasoning as described in Elementary Concepts. Moreover, we will also assume that you are familiar with the concepts of variance, covariance, and correlation; if not, we advise that you read the Basic Statistics section at this point. Although it is not absolutely necessary, it is highly desirable that you have some background in factor analysis before attempting to use structural modeling.
Major applications of structural equation modeling include:
1. causal modeling, or path analysis, which hypothesizes causal relationships among variables and tests the causal models with a linear equation system. Causal models can involve either manifest variables, latent variables, or both;
2. confirmatory factor analysis, an extension of factor analysis in which specific hypotheses about the structure of the factor loadings and intercorrelations are tested;
3. second order factor analysis, a variation of factor analysis in which the correlation matrix of the common factors is itself factor analyzed to provide second order factors;
4. regression models, an extension of linear regression analysis in which regression weights may be constrained to be equal to each other, or to specified numerical values;
5. covariance structure models, which hypothesize that a covariance matrix has a particular form. For example, you can test the hypothesis that a set of variables all have equal variances with this procedure;
6. correlation structure models, which hypothesize that a correlation matrix has a particular form. A classic example is the hypothesis that the correlation matrix has the structure of a circumplex (Guttman, 1954; Wiggins, Steiger, & Gaelick, 1981).
Many different kinds of models fall into each of the above categories, so structural modeling as an enterprise is very difficult to characterize.
Most structural equation models can be expressed as path diagrams. Consequently even beginners to structural modeling can perform complicated analyses with a minimum of training.
To index
The Basic Idea Behind Structural Modeling
One of the fundamental ideas taught in intermediate applied statistics courses is the effect of additive and multiplicative transformations on a list of numbers. Students are taught that, if you multiply every number in a list by some constant K, you multiply the mean of the numbers by K. Similarly, you multiply the standard deviation by the absolute value of K.
For example, suppose you have the list of numbers 1,2,3. These numbers have a mean of 2 and a standard deviation of 1. Now, suppose you were to take these 3 numbers and multiply them by 4. Then the mean would become 8, and the standard deviation would become 4, the variance thus 16.
The point is, if you have a set of numbers X related to another set of numbers Y by the equation Y = 4X, then the variance of Y must be 16 times that of X, so you can test the hypothesis that Y and X are related by the equation Y = 4X indirectly by comparing the variances of the Y and X variables.
This idea generalizes, in various ways, to several variables inter-related by a group of linear equations. The rules become more complex, the calculations more difficult, but the basic message remains the same -- you can test whether variables are interrelated through a set of linear relationships by examining the variances and covariances of the variables.
Statisticians have developed procedures for testing whether a set of variances and covariances in a covariance matrix fits a specified structure. The way structural modeling works is as follows:
1. You state the way that you believe the variables are inter-related, often with the use of a path diagram.
2. You work out, via some complex internal rules, what the implications of this are for the variances and covariances of the variables.
3. You test whether the variances and covariances fit this model of them.
4. Results of the statistical testing, and also parameter estimates and standard errors for the numerical coefficients in the linear equations are reported.
5. On the basis of this information, you decide whether the model seems like a good fit to your data.
There are some important, and very basic logical points to remember about this process. First, although the mathematical machinery required to perform structural equations modeling is extremely complicated, the basic logic is embodied in the above 5 steps. Below, we diagram the process.
Second, we must remember that it is unreasonable to expect a structural model to fit perfectly — for a number of reasons. A structural model with linear relations is only an approximation. The world is unlikely to be linear. Indeed, the true relations between variables are probably nonlinear. Moreover, many of the statistical assumptions are somewhat questionable as well. The real question is not so much, "Does the model fit perfectly?" but rather, "Does it fit well enough to be a useful approximation to reality, and a reasonable explanation of the trends in our data?"
Third, we must remember that simply because a model fits the data well does not mean that the model is necessarily correct. One cannot prove that a model is true — to assert this is the fallacy of affirming the consequent. For example, we could say "If Joe is a cat, Joe has hair." However, "Joe has hair" does not imply Joe is a cat. Similarly, we can say that "If a certain causal model is true, it will fit the data." However, the model fitting the data does not necessarily imply the model is the correct one. There may be another model that fits the data equally well.
To index
Structural Equation Modeling and the Path Diagram
Path Diagrams play a fundamental role in structural modeling. Path diagrams are like flowcharts. They show variables interconnected with lines that are used to indicate causal flow.
One can think of a path diagram as a device for showing which variables cause changes in other variables. However, path diagrams need not be thought of strictly in this way. They may also be given a narrower, more specific interpretation.
Consider the classic linear regression equation
Y = aX + e
Any such equation may be represented in a path diagram as follows:
Such diagrams establish a simple isomorphism. All variables in the equation system are placed in the diagram, either in boxes or ovals. Each equation is represented on the diagram as follows: All independent variables (the variables on the right side of an equation) have arrows pointing to the dependent variable. The weighting coefficient is placed above the arrow. The above diagram shows a simple linear equation system and its path diagram representation.
Notice that, besides representing the linear equation relationships with arrows, the diagrams also contain some additional aspects. First, the variances of the independent variables, which we must know in order to test the structural relations model, are shown on the diagrams using curved lines without arrowheads attached. We refer to such lines as wires. Second, some variables are represented in ovals, others in rectangular boxes. Manifest variables are placed in boxes in the path diagram. Latent variables are placed in an oval or circle. For example, the variable E in the above diagram can be thought of as a linear regression residual when Y is predicted from X. Such a residual is not observed directly, but calculated from Y and X, so we treat it as a latent variable and place it in an oval.
The example discussed above is an extremely simple one. Generally, we are interested in testing models that are much more complicated than these. As the equation systems we examine become increasingly complicated, so do the covariance structures they imply. Ultimately, the complexity can become so bewildering that we lose sight of some very basic principles. For one thing the train of reasoning which supports testing causal models with linear structural equations testing has several weak links. The variables may be non-linear. They may be linearly related for reasons unrelated to what we commonly view as causality. The ancient adage, "correlation is not causation" remains true, even if the correlation is complex and multivariate. What causal modeling does allow us to do is examine the extent to which data fail to agree with one reasonably viable consequence of a model of causality. If the linear equations system isomorphic to the path diagram does fit the data well, it is encouraging, but hardly proof of the truth of the causal model.
Although path diagrams can be used to represent causal flow in a system of variables, they need not imply such a causal flow. Such diagrams may be viewed as simply an isomorphic representation of a linear equations system. As such, they can convey linear relationships when no causal relations are assumed. Hence, although one might interpret the diagram in the above figure to mean that "X causes Y," the diagram can also be interpreted as a visual representation of the linear regression relationship between X and Y.
Source: http://www.statsoft.com/TEXTBOOK/stsepath.html
Tuesday, November 17, 2009
What statistical analysis should I use?
By Professor James D. Leeper, Ph.D
The following table shows general guidelines for choosing a statistical analysis. We emphasize that these are general guidelines and should not be construed as hard and fast rules. Usually your data could be analyzed in multiple ways, each of which could yield legitimate answers. The table below covers a number of common analyses and helps you choose among them based on the number of dependent variables (sometimes referred to as outcome variables), the nature of your independent variables (sometimes referred to as predictors). You also want to consider the nature of your dependent variable, namely whether it is an interval variable, ordinal or categorical variable, and whether it is normally distributed (see What is the difference between categorical, ordinal and interval variables? for more information on this). The table then shows one or more statistical tests commonly used given these types of variables (but not necessarily the only type of test that could be used) and links showing how to do such tests using SAS, Stata and SPSS.
Details at: http://www.ats.ucla.edu/stat/mult_pkg/whatstat/default.htm
The following table shows general guidelines for choosing a statistical analysis. We emphasize that these are general guidelines and should not be construed as hard and fast rules. Usually your data could be analyzed in multiple ways, each of which could yield legitimate answers. The table below covers a number of common analyses and helps you choose among them based on the number of dependent variables (sometimes referred to as outcome variables), the nature of your independent variables (sometimes referred to as predictors). You also want to consider the nature of your dependent variable, namely whether it is an interval variable, ordinal or categorical variable, and whether it is normally distributed (see What is the difference between categorical, ordinal and interval variables? for more information on this). The table then shows one or more statistical tests commonly used given these types of variables (but not necessarily the only type of test that could be used) and links showing how to do such tests using SAS, Stata and SPSS.
Details at: http://www.ats.ucla.edu/stat/mult_pkg/whatstat/default.htm
Saturday, November 14, 2009
ICT2010 Singapore - 30 June - 2 July 2010
Introduction
ICT2010 Singapore is an educational technology conference for academics, researchers, instructors and practitioners for the purpose of exchanging information and facilitating discussions on adult learning. The conference to be held from 30 June to 2 July is hosted by SIM University as part of its fifth anniversary celebration. The conference theme - "Inspired Solutions, Empowering Learning: Using Technology to Collaborate, Adapt and Improve Adult Learning" - focuses on how to use technology to help adult learners or mature students learn more effectively and efficiently at their own pace, space and time.
This two-and-a-half day conference features four keynote speakers. They are prominent academics well versed in their fields of expertise related to educational technology, online learning strategies and the design and development of e-content. In keeping with the subject of information communication technology, the conference will have two of its keynotes deliver presentations online.
Day 1 is set aside for peer-reviewed presentations of full papers, whilst Day 2 will showcase brief papers and poster presentations. Day 3 will be a half-day of post-conference workshops and/or visits to educational institutions, such as "Future Schools", which have, or are supporting a high level of e-Learning activities. All presentations will be in English.
ICT2010 has the support of Infocomm Development Authority of Singapore (IDA), and the Open University of Hong Kong (OUHK). In fact, the conference has its roots in a series of international conferences on "ICT in Teaching and Learning", jointly organised by OUHK and the Hong Kong Web Symposium Consortium since 2006.
Presentation Contents
We invite submissions of full and brief papers and poster presentations on three key areas linked to the conference theme, "Inspired Solutions, Empowering Learning - using technology to collaborate, adapt and improve adult learning." The focus is on how to help adult learners or mature students learn more effectively and efficiently, at their own pace, space and time.
The three key areas are:
1. Engaging Learners
Using technology to engage learners involves adapting instructional strategies that activate prior knowledge, facilitate cognitive development and promote long-term retention and transfer of skills to the workplace. What have we learned from using technology to engage learners?. Does technology adapt to specific instructional technologies or vice-versa? Is there an "e-Pedagogy" that suits the "Net Generation" of learners?
Show topics
* Audio/video Casting
* Blogging/Micro-blogging
* Classroom Techniques
* Facilitating Learning
* Interactive Content
* Social Learning/Community of Learning
2. Empowering Teaching and Learning
The roles and expectations for teaching and learning are changing, especially in an environment where technology prevails. Does technology add to a larger divide between teaching and learning, or is it a bridge to bring teaching and learning, knowledge and experience closer together? In what ways does technology empower teachers to expand their teaching strategies/practices and learners to express themselves?
Show topics
* Blended Learning
* Collaborative Learning / wiki
* e-Mentorings
* Electronic Portfolios
* Educational Psychology
* ICT Educator's Development
* Life Long Learning
* Rapid e-learning
* Strategic Leadership
* Virtual Communities
3. Emerging Technologies
The proliferation of technology in education and training is relentless. With the increased adoption of technology, learning anywhere, anyplace and anytime is increasingly a reality which is especially welcomed by part-time adult learners who are busy professionals. But how do we choose the right technology which can give the best impact on learning? How do we avoid putting technology first before pedagogy in our need or desire to free-up teaching and learning from the constraints of the classroom? Are we creating opportunities to support technological innovations that enhance curricula development or just creating more bells and whistles?
Submission Details
Key dates at a glance
Abstract (Full/Brief Paper/Best Practice Presentation) submission deadline:
30 November 2009
Abstract acceptance notification:
31 December, 2009
Full/brief paper submission deadline:
28 February 2010
Review panel submission period:
1 March to 1 May 2010
Presentation-ready paper submission deadline:
31 May 2010
We invite submissions of Full and Brief papers, and Best Practice Presentations.
Full Paper:
1. Create a user account.
2. Submit an abstract of up to 1,000 words for review and acceptance.
3. Submit a full research report of between 8 to 10 pages and up to 5,000 words for review (12-point Times New Roman font is recommended)
4. Revise full research paper based upon reviewers' recommendations.
5. Submit final paper and register for conference.
6. Present paper at conference (25 minutes including Q & A session).
Brief Paper:
1. Create a user account.
2. Submit an abstract of up to 500 words for review and acceptance.
3. Submit a brief reflection report of between 4 to 6 pages and up to 2,500 words (12-point Times New Roman font is recommended).
4. Revise brief reflection report based upon reviewers' recommendations.
5. Submit final paper and register for conference.
6. Present paper at conference (15 minutes including Q & A session).
Best Practice Presentation:
1. Create a user account.
2. Submit a write-up of at least 1,000 words of a Best Practice Presentation for review and acceptance (12-point Times New Roman font is recommended).
3. Present paper at conference (15 minutes including Q & A session).
Format for Abstract, Full/Brief Paper and Best Practice Presentation:
* Refer to Author's Guidelines
* Refer to Review Criteria
Note:
Presenters must submit the final version of Full/Brief Papers and/or Best Practice Presentations and register for the conference by 31 May 2010 to have their work included in the Conference Proceedings CD-ROM.
Eligibility for Best Paper
All papers published in the conference proceedings shall be eligible for the Best Paper Award in each key area. The chosen paper must be original and has not been published elsewhere. Only authors who attend and present their respective papers at the conference are eligible to be considered for the award.
Authors of best papers will be recommended to submit their papers to the following journals:
* International Journal of Innovation and Learning
* Asean Journal of Open and Distance Learning
* Interactive Technology and Smart Education
Details at: http://www.unisim.edu.sg/uni/pub/ICT2010/index.html
Global Learn Asia Pacific 2010 - Global Conference on Learning and Technology
The mission of the Global Learn Asia Pacific conference, organized by the Association for the Advancement of Computing in Education (AACE) is to further the advancement and innovation in learning and technology. As the educational world becomes increasingly global, new ways to explore, learn, and share knowledge are needed.
Global Learn serves as a means to connect and engage creative educators, researchers, consultants, training managers, policy makers, curriculum developers, entrepreneurs, and others in the topics and fields in which they are passionate. Many individuals are transforming learning environments in local as well as more global ways. Global Learn offers an opportunity to meet and discuss their ideas, findings, and next steps.
INVITATION
Global Learn Asia Pacific--Global Conference on Learning and Technology is an international conference, organized by the Association for the Advancement of Computing in Education (AACE).
This annual conference serves to further the advancement and innovation in learning and technology. As the educational world becomes increasingly global, new ways to explore, learn, and share knowledge are needed. Global Learn is a means to connect and engage creative educators, researchers, consultants, training managers, policy makers, curriculum developers, entrepreneurs, and others in the topics and fields in which they are passionate. Global Learn offers an opportunity to meet and discuss their ideas, findings, and next steps.
Global Learn, the premiere international conference in the field, spans all disciplines and levels of education and is expected to attracts many leaders in the field from around the world. For a list of countries represented at previous AACE conferences, see: Countries.
We invite you to attend Global Learn and submit proposals for papers, panels, roundtables, tutorials, workshops, posters/demonstrations, corporate showcases/demos, and SIG discussions. The Conference Review Policy requires that each proposal will be peer-reviewed by for inclusion in the conference program, proceedings book, and CD-ROM proceedings.
TOPICS
The scope of the conference includes, but is not limited to, the following major topics as they relate to Learning and Technology. Sub-topics listed here.
1. Advanced Technologies for Learning and Teaching
2. Assessment and Research
3. Educational Reform, Policy, and Innovation
4. Evaluation and Quality Improvement Advances
5. Global Networks, Partnerships, and Exchanges
6. Innovative Approaches to Learning and Learning Environments
7. Open Education
8. Technologies for Socially Responsive Learning
9. Virtual and Distance Education
PRESENTATION CATEGORIES
The Technical Program includes a wide range of interesting and useful activities designed to facilitate the exchange of ideas and information.
* Keynote Speakers
* Invited Panels/Speakers
* Papers
* Panels
* Posters/Demonstrations
* Corporate Showcases & Demonstrations
* Tutorials/Workshops
* Roundtables
* Symposia
For Presentation Category descriptions, and information about what to submit with your proposal, click here.
CORPORATE PARTICIPATION
A variety of opportunities are available to present research-oriented papers, or to showcase and market your products and services. For information about Corporate Showcases (30 minutes) and Corporate Demonstrations (2-hours, scheduled with the Poster/Demos), click here.
PROCEEDINGS
Accepted papers will be published in the Proceedings (book and CD-ROM formats) as well as in the AACE Digital Library. These proceedings serve as major sources in the multimedia/ hypermedia/telecommunications community, reflecting the current state of the art in the discipline.
In addition, the Proceedings also are internationally distributed through and archived in the EdITLib Digital Library.
Selected papers may be invited for publication in may be invited for publication in AACE's respected journals especially in the Journal of Educational Multimedia and Hypermedia (JEMH), International Journal on E-Learning (IJEL), or Journal of Interactive Learning Research (JILR). See: www.aace.org/pubs
PAPER AWARDS
Papers present reports of significant work or integrative reviews in research, development, and applications related to the educational multimedia, hypermedia and telecommunications/ distance education. All presented papers will be considered by the Program Committee for Outstanding Paper Awards. There will also be an award for Outstanding Student Paper (therefore, please indicate with your submission if the primary author is a full-time student).
Award winning papers will be highlighted in the AACE online periodical the AACE Journal. See previous award papers featured in the EdITLib Digital Library.
Details: https://www.aace.org/conf/glearn/call.htm
One-Way ANOVA
By Susan Archambault (Psychology Department, Wellesley College)
What it does:
The One-Way ANOVA compares the mean of one or more groups based on one independent variable (or factor).
Where to find it:
Under the Analyze menu, choose Compare Means, then choose One-Way ANOVA. Move all dependent variables into the box labeled "Dependent List," and move the independent variable into the box labeled "Factor." Click on the button labeled "Options," and check off the boxes for Descriptives and Homogeneity of Variance. Click on the box marked "Post Hoc" and choose the appropriate post hoc comparison. Generally, for Psych 205 students, you can follow this rule: If there are equal numbers of cases in each group, choose Tukey. If there are not equal numbers of cases in each group, choose Bonferroni.
Assumptions:
-The dependent variable(s) is normally distributed. You can check for normal distribution with a Q-Q plot.
-The two groups have approximately equal variance on the dependent variable. You can check this by looking at the Levene's Test. See below.
Hypotheses:
Null: There are no significant differences between the groups' mean scores.
Alternate: There is a significant difference between the groups' mean scores.
SPSS Output
Following is a sample output of a One-Way ANOVA. We compared the mean level of prejudice of first-years, sophomores, juniors, and seniors. Mean level of prejudice is our dependent variable, and year in college is our independent variable.
First, we see the descriptive statistics for each of the 4 years in college.
It looks like first-years have the highest mean level of prejudice, and seniors have the lowest mean level of prejudice.
Next we see the results of the Levene's Test of Homogeneity of Variance.
This tells us if we have met our second assumption (the groups have approximately equal variance on the dependent variable). If the Levene's Test is significant (the value under "Sig." is less than .05), the two variances are significantly different. If it is not significant (Sig. is greater than .05), the two variances are not significantly different; that is, the two variances are approximately equal. If the Levene's test is not significant, we have met our second assumption. Here, we see that the significance is .435, which is greater than .05. We can assume that the variances are approximately equal. We have met our second assumption.
Finally, we see the results of our One-Way ANOVA:
Our F value is 3.110.
Our significance value is .027.
There is a significant difference between the two groups (the significance is less than .05).
Therefore, we can say that there is a significant difference between first-years, sophomores, juniors, and seniors on their level of prejudice.
We can look at the results of the Post-Hoc Comparisons to see exactly which pairs of groups are significantly different.
SPSS notes a significant difference with an asterisk (*). We can see that first-years and sophomores are significantly different than seniors.
Source: http://www.wellesley.edu/Psychology/Psych205/anova.html
What it does:
The One-Way ANOVA compares the mean of one or more groups based on one independent variable (or factor).
Where to find it:
Under the Analyze menu, choose Compare Means, then choose One-Way ANOVA. Move all dependent variables into the box labeled "Dependent List," and move the independent variable into the box labeled "Factor." Click on the button labeled "Options," and check off the boxes for Descriptives and Homogeneity of Variance. Click on the box marked "Post Hoc" and choose the appropriate post hoc comparison. Generally, for Psych 205 students, you can follow this rule: If there are equal numbers of cases in each group, choose Tukey. If there are not equal numbers of cases in each group, choose Bonferroni.
Assumptions:
-The dependent variable(s) is normally distributed. You can check for normal distribution with a Q-Q plot.
-The two groups have approximately equal variance on the dependent variable. You can check this by looking at the Levene's Test. See below.
Hypotheses:
Null: There are no significant differences between the groups' mean scores.
Alternate: There is a significant difference between the groups' mean scores.
SPSS Output
Following is a sample output of a One-Way ANOVA. We compared the mean level of prejudice of first-years, sophomores, juniors, and seniors. Mean level of prejudice is our dependent variable, and year in college is our independent variable.
First, we see the descriptive statistics for each of the 4 years in college.
It looks like first-years have the highest mean level of prejudice, and seniors have the lowest mean level of prejudice.
Next we see the results of the Levene's Test of Homogeneity of Variance.
This tells us if we have met our second assumption (the groups have approximately equal variance on the dependent variable). If the Levene's Test is significant (the value under "Sig." is less than .05), the two variances are significantly different. If it is not significant (Sig. is greater than .05), the two variances are not significantly different; that is, the two variances are approximately equal. If the Levene's test is not significant, we have met our second assumption. Here, we see that the significance is .435, which is greater than .05. We can assume that the variances are approximately equal. We have met our second assumption.
Finally, we see the results of our One-Way ANOVA:
Our F value is 3.110.
Our significance value is .027.
There is a significant difference between the two groups (the significance is less than .05).
Therefore, we can say that there is a significant difference between first-years, sophomores, juniors, and seniors on their level of prejudice.
We can look at the results of the Post-Hoc Comparisons to see exactly which pairs of groups are significantly different.
SPSS notes a significant difference with an asterisk (*). We can see that first-years and sophomores are significantly different than seniors.
Source: http://www.wellesley.edu/Psychology/Psych205/anova.html
Thursday, October 15, 2009
King Cautions Malaysians Over Cheap And Fake Degrees
SHAH ALAM, Oct 15 (Bernama) -- Yang di-Pertuan Agong Tuanku Mizan Zainal Abidin today cautioned Malaysians against acquiring unrecognised cheap degrees secured illegally.
"Such a thing is morally wrong and, if left unchecked, will make us all members of a fake society without morals as well," he said at the first session of the 71st convocation of Universiti Teknologi Mara (UiTM), here. Also present was Raja Permaisuri Agong Tuanku Nur Zahirah.
As such, he proposed that UiTM and all other universities adopt appropriate measures to ensure quality, recognition and integrity of the degrees they awarded.
"We must undertake strict and close monitoring of any individual who comes bearing a degree to seek employment.
"We must make sure that the degree is genuine and is recognised ... we must ensure that the bearer is a capable individual whom we can trust to educate our children," he said.
Tuanku Mizan said the achievement of the graduates at the convocation was derived through hard work and wisdom, and that these graduates of quality and integrity would go on to mould a highly civilised society.
At the convocation, 21,128 graduates were awarded honours ranging from diplomas to PhD, taking the number of people graduating from UiTM this year to 35,009 and expanding the alumni of the university to more than 350,000 people.
The king advised the graduates and alumni to safeguard the good name of the university.
Also at the convocation, Tuanku Mizan presented an honorary doctorate in government and politics to former deputy prime minister Tun Musa Hitam for his contribution and service to the government and party, enabling him to be recognised as a statesman and credible politician.
Tuanku Mizan presented doctorate degrees to 16 people and the Masters degree to 402 as well as the outstanding graduate awards to nine.
The Seri Paduka Baginda Tuanku Chancellor Award was presented to Nik Muammar Bahari, 24, of Kedah who secured an honorary Bachelor's degree in Art and Design.
Nik Muammar has been working as a project designer in Hong Kong since July and is engaged with the corporate branding of the Qatar National Master Plan project.
Mohd Rashid Azhari, 34, the eldest son of Inspector-General of Police Tan Sri Musa Hassan, received his Masters in Forensic Accounting and Financial Criminology. Mohd Rashid is a manager with a consulting company.
"Such a thing is morally wrong and, if left unchecked, will make us all members of a fake society without morals as well," he said at the first session of the 71st convocation of Universiti Teknologi Mara (UiTM), here. Also present was Raja Permaisuri Agong Tuanku Nur Zahirah.
As such, he proposed that UiTM and all other universities adopt appropriate measures to ensure quality, recognition and integrity of the degrees they awarded.
"We must undertake strict and close monitoring of any individual who comes bearing a degree to seek employment.
"We must make sure that the degree is genuine and is recognised ... we must ensure that the bearer is a capable individual whom we can trust to educate our children," he said.
Tuanku Mizan said the achievement of the graduates at the convocation was derived through hard work and wisdom, and that these graduates of quality and integrity would go on to mould a highly civilised society.
At the convocation, 21,128 graduates were awarded honours ranging from diplomas to PhD, taking the number of people graduating from UiTM this year to 35,009 and expanding the alumni of the university to more than 350,000 people.
The king advised the graduates and alumni to safeguard the good name of the university.
Also at the convocation, Tuanku Mizan presented an honorary doctorate in government and politics to former deputy prime minister Tun Musa Hitam for his contribution and service to the government and party, enabling him to be recognised as a statesman and credible politician.
Tuanku Mizan presented doctorate degrees to 16 people and the Masters degree to 402 as well as the outstanding graduate awards to nine.
The Seri Paduka Baginda Tuanku Chancellor Award was presented to Nik Muammar Bahari, 24, of Kedah who secured an honorary Bachelor's degree in Art and Design.
Nik Muammar has been working as a project designer in Hong Kong since July and is engaged with the corporate branding of the Qatar National Master Plan project.
Mohd Rashid Azhari, 34, the eldest son of Inspector-General of Police Tan Sri Musa Hassan, received his Masters in Forensic Accounting and Financial Criminology. Mohd Rashid is a manager with a consulting company.
Tuesday, October 13, 2009
More adult Malaysians turn to the Net for sex info - Star
Oct 13, 2009 By JOSHUA FOONG
PETALING JAYA: More adults are relying on the Internet to get information on sex, according to a Durex Sexual Wellbeing Survey.
As much as 75% of Malaysians gave credit to the Internet for teaching them the bedroom “how-tos”.
Men (75%) outnumber women (71%) in using the Internet to surf about sex.
Seventy-three per cent of the respondents also learn about sex through magazines.
Other sources include books (65%), friends and peers (56%) and partners (43%).
All these surpass sex education at school, which makes up only 36% of them.
The number of respondents was at 1,026 with an equal number of women and men aged 18 years and above.
Despite the figures, less than half of Malaysians — 45% of men and 39% of women — think there is enough advice and information available on the issue.
The survey stated that 73% of Malaysians who had formal sex education are satisfied with their sexual wellbeing while the global average of sexual satisfaction stands at 59%.
However, the survey also found that 51% of those who received sex education at school did not learn about conception while 71% were not taught about sexually transmitted diseases.
Less than half of Malaysians (48%) had wished their sex education had included love, respect and on giving pleasure to one’s partner.
It found that about 44% of those aged between 16 and 24 liked to have received more information on the subject in comparison to 62% among those aged between 35 and 44.
The survey is the fourth in a series of reports by Durex, with this one emphasising on knowledge and education.
Previous results of the three surveys titled “Satisfaction”, “In the Bedroom” and “The Big O” can be found on www.durex.com.
PETALING JAYA: More adults are relying on the Internet to get information on sex, according to a Durex Sexual Wellbeing Survey.
As much as 75% of Malaysians gave credit to the Internet for teaching them the bedroom “how-tos”.
Men (75%) outnumber women (71%) in using the Internet to surf about sex.
Seventy-three per cent of the respondents also learn about sex through magazines.
Other sources include books (65%), friends and peers (56%) and partners (43%).
All these surpass sex education at school, which makes up only 36% of them.
The number of respondents was at 1,026 with an equal number of women and men aged 18 years and above.
Despite the figures, less than half of Malaysians — 45% of men and 39% of women — think there is enough advice and information available on the issue.
The survey stated that 73% of Malaysians who had formal sex education are satisfied with their sexual wellbeing while the global average of sexual satisfaction stands at 59%.
However, the survey also found that 51% of those who received sex education at school did not learn about conception while 71% were not taught about sexually transmitted diseases.
Less than half of Malaysians (48%) had wished their sex education had included love, respect and on giving pleasure to one’s partner.
It found that about 44% of those aged between 16 and 24 liked to have received more information on the subject in comparison to 62% among those aged between 35 and 44.
The survey is the fourth in a series of reports by Durex, with this one emphasising on knowledge and education.
Previous results of the three surveys titled “Satisfaction”, “In the Bedroom” and “The Big O” can be found on www.durex.com.
Saturday, October 10, 2009
Public, Private Universities Receive RM25 Million Research Grants
KUALA LUMPUR, Oct 9 (Bernama) -- The government has allocated RM25 million under the Fundamental Research Grant Scheme (FRGS) to sponsor 602 projects undertaken by public and private universities this year.
Higher Education Minister Datuk Seri Mohamed Khaled Nordin said 20 researchers from public universities and three from private universities received the sponsorship this year.
He said public universities had been allocated with RM23.63 million to carry out 411 projects while private universities received RM1.41 million to bring 191 projects to fruition.
The grants were channelled through the Education Ministry, the Agriculture and Agro-based Industry Ministry, and the Science, Technology and Innovation Ministry, he told reporters at the International Exposition of Research and Invention of Institutions of Higher Learning 2009 (PECIPTA 2009) award presentation here on Friday.
He said the FRGS research focused on pure science, applied science, engineering and technology, medical science, social science and humanities, arts and professional arts and natural sciences, and national heritage.
Universiti Malaya was adjudged the winner of the Premier Research Award, having clinched four gold, 14 silver and 10 bronze medals in PECIPTA 2009.
Universiti Teknologi Malaysia (UTM) came in a close second with four gold, 11 silver and 11 bronze medals.
PECIPTA 2009 with the theme "Driving Research Innovation Towards Value Creation" scrutinised 465 research submitted by 22 public and private universities.
It was jointly held by Higher Education Ministry and Universiti Malaya to spur innovations by local universities.
-- BERNAMA
Higher Education Minister Datuk Seri Mohamed Khaled Nordin said 20 researchers from public universities and three from private universities received the sponsorship this year.
He said public universities had been allocated with RM23.63 million to carry out 411 projects while private universities received RM1.41 million to bring 191 projects to fruition.
The grants were channelled through the Education Ministry, the Agriculture and Agro-based Industry Ministry, and the Science, Technology and Innovation Ministry, he told reporters at the International Exposition of Research and Invention of Institutions of Higher Learning 2009 (PECIPTA 2009) award presentation here on Friday.
He said the FRGS research focused on pure science, applied science, engineering and technology, medical science, social science and humanities, arts and professional arts and natural sciences, and national heritage.
Universiti Malaya was adjudged the winner of the Premier Research Award, having clinched four gold, 14 silver and 10 bronze medals in PECIPTA 2009.
Universiti Teknologi Malaysia (UTM) came in a close second with four gold, 11 silver and 11 bronze medals.
PECIPTA 2009 with the theme "Driving Research Innovation Towards Value Creation" scrutinised 465 research submitted by 22 public and private universities.
It was jointly held by Higher Education Ministry and Universiti Malaya to spur innovations by local universities.
-- BERNAMA
Survey finds firms now want accountants to go beyond crunching numbers - Malaysian Insider
SINGAPORE, Oct 10 — Post-crisis, accountants who believe their job is solely about counting beans and making sure the balance sheet balances will do so at their own peril.
As the operations and strategies of firms become inextricably linked with numbers and finance, accountants need be more than number crunchers, Tony Osude, the Association of Chartered Certified Accountants' (ACCA) acting director of professional development, told an ACCA conference yesterday.
“In our interviews with chief financial officers, I am getting a sense of frustration from them that accountants are not stepping up to act as the companies' business partners,” said Osude.
As businesses become increasingly pressed for solutions in a credit-scarce environment, it has become crucial to bridge the gap between practical business knowhow and financial acumen.
Research done for the latest ACCA Accountants for Business report found that some business leaders are beginning to consider training business personnel in finance to bridge that gap, instead of turning to accountants for counsel.
“This has quite significant and severe implications for the accounting profession,” Osude warned yesterday.
In the survey, the finance director of a venture capital fund management firm had said: “A bad accountant will produce a set of numbers. A good accountant will say there is a set of numbers, use a bit of analysis and provide a description of what it means for the business.”
Even when accountants do offer analysis of the business, the bar has been raised. “Accountants are very good at cutting costs but very poor at driving profits,” Osude said.
“European companies, for example, have been doing a lot of cost-cutting and the figures look OK. But what will happen next year when there are no more costs to cut?”
As part of a seismic shift in accounting approaches caused by the downturn, if cash was king before, it is now supreme ruler. “The past few months have been about cash, cash, cash. All the accountants we interviewed said that in terms of strategy, they are not looking beyond the next month,” Osude revealed.
Across the landscape of accountants, some sand dunes dwarf others. The report found that 65 per cent of respondents placed the CFO within the top five finance roles that add the most value to organisations, compared with 22 per cent for financial accountants and 18 per cent for heads of risk management.
While all the implications of such numbers are not immediately clear — Osude conceded that respondents could merely have taken a hierarchical view to answering the question — one implication is certain.
“There is too much riding on the shoulders of the CFO — he is doing too much,” said Osude.
The survey also unearthed a growing need for effective finance information technology systems, so the accountant spends less time bound to his spreadsheet and more time analysing the final numbers.
A partner from one of the Big Four accounting firms is quoted in the report as saying: “What we've found is that they spend so much time producing the number . . . and reworking and re-crunching it. . . They collapse it into the meeting not even having thought what the number means.”
The survey was conducted online with 1,353 ACCA members from more than 170 countries. — Business Times Singapore
As the operations and strategies of firms become inextricably linked with numbers and finance, accountants need be more than number crunchers, Tony Osude, the Association of Chartered Certified Accountants' (ACCA) acting director of professional development, told an ACCA conference yesterday.
“In our interviews with chief financial officers, I am getting a sense of frustration from them that accountants are not stepping up to act as the companies' business partners,” said Osude.
As businesses become increasingly pressed for solutions in a credit-scarce environment, it has become crucial to bridge the gap between practical business knowhow and financial acumen.
Research done for the latest ACCA Accountants for Business report found that some business leaders are beginning to consider training business personnel in finance to bridge that gap, instead of turning to accountants for counsel.
“This has quite significant and severe implications for the accounting profession,” Osude warned yesterday.
In the survey, the finance director of a venture capital fund management firm had said: “A bad accountant will produce a set of numbers. A good accountant will say there is a set of numbers, use a bit of analysis and provide a description of what it means for the business.”
Even when accountants do offer analysis of the business, the bar has been raised. “Accountants are very good at cutting costs but very poor at driving profits,” Osude said.
“European companies, for example, have been doing a lot of cost-cutting and the figures look OK. But what will happen next year when there are no more costs to cut?”
As part of a seismic shift in accounting approaches caused by the downturn, if cash was king before, it is now supreme ruler. “The past few months have been about cash, cash, cash. All the accountants we interviewed said that in terms of strategy, they are not looking beyond the next month,” Osude revealed.
Across the landscape of accountants, some sand dunes dwarf others. The report found that 65 per cent of respondents placed the CFO within the top five finance roles that add the most value to organisations, compared with 22 per cent for financial accountants and 18 per cent for heads of risk management.
While all the implications of such numbers are not immediately clear — Osude conceded that respondents could merely have taken a hierarchical view to answering the question — one implication is certain.
“There is too much riding on the shoulders of the CFO — he is doing too much,” said Osude.
The survey also unearthed a growing need for effective finance information technology systems, so the accountant spends less time bound to his spreadsheet and more time analysing the final numbers.
A partner from one of the Big Four accounting firms is quoted in the report as saying: “What we've found is that they spend so much time producing the number . . . and reworking and re-crunching it. . . They collapse it into the meeting not even having thought what the number means.”
The survey was conducted online with 1,353 ACCA members from more than 170 countries. — Business Times Singapore
Unitar should be re-engineered as a niche university – Najib
KUALA LUMPUR, Oct 9 – Universiti Tun Abdul Razak (Unitar), the private institution of higher learning which was set up in 1997, should be re-engineered as a niche university, Prime Minister Datuk Seri Najib Tun Razak said today.
Apart from playing its role as a boutique university which focused on small intakes of students, he said that the university should also be re-engineered to fulfil the country’s needs.
“We have no intention of turning Unitar into a mass university but to let it remain as a ‘boutique’ university, giving emphasis to a small number of students, reflecting the university’s quest for quality,” he said when opening Unitar’s Razak Campus at Capital Square, Jalan Munshi Abdullah here.
Najib said Unitar, which offers 40 first degree and post-graduate courses, including in the field of business administration and information technology, should also cater for the country’s human capital development.
“When Unitar board of directors discuss the university’s re-engineering process, they should look into its niche area,” he said.
The prime minister said that Unitar should also forge networking with various institutions either locally or internationally to further enhance its quality and status. In doing so, Najib said the university should choose the best partners.
“This should be the philosophy of Unitar’s re-engineering. I hope that we will do everything possible to achieve higher quality,” he said.
Earlier, Najib witnessed the exchange of documents related to new collaborative agreements between Unitar and UEM Group Berhad, Kumpulan Karangkraf Sdn Bhd and Amanah Raya Berhad.
Unitar recently signed a Memorandum of Agreement (MoA) with UEM in which the university’s Centre for Executive Education would receive an endowment of RM10 million from UEM to be used for the UEM Warriors program.
Following this, one of the university’s lecture halls will be renamed the “UEM Lecture Hall.”
Under the MoA with Karangkraf, Unitar will offer a RM1 million scholarship annually to selected students chosen at Karangkraf’s discretion, to pursue courses at the university. In return, the publishing company will offer Unitar RM1 million worth of advertisement in its publications per annum.
The MoA with Amanah Raya Berhad is for a collaboration in programme development, executive development and research grants in Islamic wealth management.
Unitar, named after Najib’s father and Malaysia’s second prime minister Tun Abdul Razak Hussein, is the first private university in the country and took its first intake of 162 students in September 1998.
The university was launched by Najib, who was then the Education Minister, on Dec 21, 1998. – Bernama
Thursday, October 8, 2009
Rankings 09: Asia advances
8 October 2009 By Phil Baty
America's superpower status is slipping as other countries' efforts to join the global elite begin to pay dividends. Phil Baty reports
The US domination of the top ranks of global higher education is not as strong as it has been in previous years. The Times Higher Education-QS World University Rankings 2009 show that institutions in Asian countries such as Hong Kong and Japan are growing in stature.
Although Harvard University is still ranked number one in the table of the world's top 200 universities - for the sixth consecutive year - American supremacy seems to be slipping.
While the US still has by far the most institutions in the top 200, with a total of 54, it has lost five institutions from the top 100 and four have dropped out of the top 200 altogether.
The country's decline comes amid improved showings by institutions in Japan, Hong Kong, South Korea and Malaysia.
Philip Altbach, director of the Centre for Higher Education at Boston College in the US, says several factors are behind the surges by Asian institutions.
"These countries have invested heavily in higher education in recent years, and this is reflected in the improved quality in their top institutions," he says. "They have also attempted to internationalise their universities by hiring more faculty from overseas ... this helps to improve their visibility globally.
"These universities have also stressed the importance of their professors publishing in international journals, which has no doubt increased the visibility of their research."
But he adds that this drive for internationalisation and success in global rankings may be "debatable in terms of good policy" for Asian institutions. For example, he says, stressing the importance of publishing in international journals may "tilt research away from topics relevant for national development", and fostering the use of the English language "may have a negative impact on intellectual work in the local language".
Japan counts 11 institutions in the top 200, among them two new entrants: the University of Tsukuba sharing 174th place and Keio University making an impressive debut at 142nd. Japan's representatives in the top 100 rose in number from four to six, led by the University of Tokyo at 22nd place (down from 19th).
Despite having a total of only eight government-funded tertiary institutions, Hong Kong has five institutions in the top 200, up from four last year.
Its tally includes three in the top 50: the University of Hong Kong (up two places to 24th); Hong Kong University of Science and Technology (up four to 35th); and the Chinese University of Hong Kong (down four to 46th). City University of Hong Kong rocketed up the table to 124th, from joint 147th, in its 25th anniversary year. Hong Kong Polytechnic University made the top 200, reaching 195th place.
South Korea now has four universities in the top 200, with new entrant Yonsei University in at joint 151st. Seoul National University is the country's highest-placed institution, sharing 47th place.
Malaysia returned to the top 200 with its Universiti Malaya entering at 180th place.
China replicated its standing from last year, with two institutions in the top 100 and a total of six in the top 200. The country's top-rated institution, Tsinghua University, climbed from 56th place to joint 49th, while Peking University slipped from 50th to joint 52nd. Fudan University moved up to joint 103rd from 113th.
The rise of Asia is in direct contrast to the US' fortunes. The most dramatic illustration of its slide is apparent in the top ten. Although America still claims six of the top ten spots, Yale University has slipped from second to third place in the past year - overtaken by the University of Cambridge - and the California Institute of Technology has fallen from number five to number ten.
This slide lends credence to the predictions of several international higher education experts that the US will soon lose its international ascendancy.
Don Olcott, head of the Observatory on Borderless Higher Education, spoke in August about the rise of the "new global regionalism" threatening Anglo-American dominance.
"Are we really naive enough to think that China, India, Malaysia, South Korea, the Gulf states and others do not want to build long-term, high-quality, sustainable university systems?" he told Times Higher Education.
At an Organisation for Economic Co-operation and Development conference earlier this year, it was suggested that the US and the UK would be hit far harder than most countries by the need for future public spending cuts because both will need to reduce massive budget deficits. A number of countries in Asia, including Japan and Korea, will face an easier ride. Delegates spoke of a resulting major "redistribution of brains".
According to Ben Sowter, head of research at QS, which compiles the tables for Times Higher Education, the fallout caused by America's economic problems may ultimately result in its institutions sliding even lower in subsequent rankings. As 40 per cent of the overall ranking score is based on a survey of academics' opinions (see "Talking points", page x), the US' slip in 2009 may have more to do with the improvement in the reputation of Asian institutions brought about by better marketing and communication, he says.
"In the six years of conducting this study, we have seen a drastically increased emphasis on international reputation from institutions in many countries, particularly those in Asia," he notes.
Like its southern neighbour, Canada's overall position in the rankings also dropped. It registered 11 institutions in the top 200, compared with 12 in 2008. Its two best performers both rose - McGill University climbed from 20th place to 18th, while the University of Toronto shot up from 41st to 29th - but others slipped.
Australia has nine institutions in the top 200, the same number as last year, but it increased its representation in the top 100 from seven to eight.
The Australian National University, the highest-placed institution outside the US and the UK, slipped from 16th to 17th, but Melbourne, Sydney, Queensland and Monash all improved their positions.
Russia has two institutions in the top 200, with new entrant Saint-Petersburg State University in at joint number 168.
Sweden also has one new entrant; the University of Gothenburg moved up to 185th place to lift Sweden's tally to five in the top 200. Brazil and Argentina, which had one university each in the 2008 rankings, both fell out of the top 200 altogether.
Source: http://www.timeshighereducation.co.uk/story.asp?sectioncode=26&storycode=408560&c=2
More details: http://www.timeshighereducation.co.uk/WorldUniversityRankings.html
America's superpower status is slipping as other countries' efforts to join the global elite begin to pay dividends. Phil Baty reports
The US domination of the top ranks of global higher education is not as strong as it has been in previous years. The Times Higher Education-QS World University Rankings 2009 show that institutions in Asian countries such as Hong Kong and Japan are growing in stature.
Although Harvard University is still ranked number one in the table of the world's top 200 universities - for the sixth consecutive year - American supremacy seems to be slipping.
While the US still has by far the most institutions in the top 200, with a total of 54, it has lost five institutions from the top 100 and four have dropped out of the top 200 altogether.
The country's decline comes amid improved showings by institutions in Japan, Hong Kong, South Korea and Malaysia.
Philip Altbach, director of the Centre for Higher Education at Boston College in the US, says several factors are behind the surges by Asian institutions.
"These countries have invested heavily in higher education in recent years, and this is reflected in the improved quality in their top institutions," he says. "They have also attempted to internationalise their universities by hiring more faculty from overseas ... this helps to improve their visibility globally.
"These universities have also stressed the importance of their professors publishing in international journals, which has no doubt increased the visibility of their research."
But he adds that this drive for internationalisation and success in global rankings may be "debatable in terms of good policy" for Asian institutions. For example, he says, stressing the importance of publishing in international journals may "tilt research away from topics relevant for national development", and fostering the use of the English language "may have a negative impact on intellectual work in the local language".
Japan counts 11 institutions in the top 200, among them two new entrants: the University of Tsukuba sharing 174th place and Keio University making an impressive debut at 142nd. Japan's representatives in the top 100 rose in number from four to six, led by the University of Tokyo at 22nd place (down from 19th).
Despite having a total of only eight government-funded tertiary institutions, Hong Kong has five institutions in the top 200, up from four last year.
Its tally includes three in the top 50: the University of Hong Kong (up two places to 24th); Hong Kong University of Science and Technology (up four to 35th); and the Chinese University of Hong Kong (down four to 46th). City University of Hong Kong rocketed up the table to 124th, from joint 147th, in its 25th anniversary year. Hong Kong Polytechnic University made the top 200, reaching 195th place.
South Korea now has four universities in the top 200, with new entrant Yonsei University in at joint 151st. Seoul National University is the country's highest-placed institution, sharing 47th place.
Malaysia returned to the top 200 with its Universiti Malaya entering at 180th place.
China replicated its standing from last year, with two institutions in the top 100 and a total of six in the top 200. The country's top-rated institution, Tsinghua University, climbed from 56th place to joint 49th, while Peking University slipped from 50th to joint 52nd. Fudan University moved up to joint 103rd from 113th.
The rise of Asia is in direct contrast to the US' fortunes. The most dramatic illustration of its slide is apparent in the top ten. Although America still claims six of the top ten spots, Yale University has slipped from second to third place in the past year - overtaken by the University of Cambridge - and the California Institute of Technology has fallen from number five to number ten.
This slide lends credence to the predictions of several international higher education experts that the US will soon lose its international ascendancy.
Don Olcott, head of the Observatory on Borderless Higher Education, spoke in August about the rise of the "new global regionalism" threatening Anglo-American dominance.
"Are we really naive enough to think that China, India, Malaysia, South Korea, the Gulf states and others do not want to build long-term, high-quality, sustainable university systems?" he told Times Higher Education.
At an Organisation for Economic Co-operation and Development conference earlier this year, it was suggested that the US and the UK would be hit far harder than most countries by the need for future public spending cuts because both will need to reduce massive budget deficits. A number of countries in Asia, including Japan and Korea, will face an easier ride. Delegates spoke of a resulting major "redistribution of brains".
According to Ben Sowter, head of research at QS, which compiles the tables for Times Higher Education, the fallout caused by America's economic problems may ultimately result in its institutions sliding even lower in subsequent rankings. As 40 per cent of the overall ranking score is based on a survey of academics' opinions (see "Talking points", page x), the US' slip in 2009 may have more to do with the improvement in the reputation of Asian institutions brought about by better marketing and communication, he says.
"In the six years of conducting this study, we have seen a drastically increased emphasis on international reputation from institutions in many countries, particularly those in Asia," he notes.
Like its southern neighbour, Canada's overall position in the rankings also dropped. It registered 11 institutions in the top 200, compared with 12 in 2008. Its two best performers both rose - McGill University climbed from 20th place to 18th, while the University of Toronto shot up from 41st to 29th - but others slipped.
Australia has nine institutions in the top 200, the same number as last year, but it increased its representation in the top 100 from seven to eight.
The Australian National University, the highest-placed institution outside the US and the UK, slipped from 16th to 17th, but Melbourne, Sydney, Queensland and Monash all improved their positions.
Russia has two institutions in the top 200, with new entrant Saint-Petersburg State University in at joint number 168.
Sweden also has one new entrant; the University of Gothenburg moved up to 185th place to lift Sweden's tally to five in the top 200. Brazil and Argentina, which had one university each in the 2008 rankings, both fell out of the top 200 altogether.
Source: http://www.timeshighereducation.co.uk/story.asp?sectioncode=26&storycode=408560&c=2
More details: http://www.timeshighereducation.co.uk/WorldUniversityRankings.html
Universiti Malaya climbs 50 spots to No. 180 in THE-QS rankings - Star
Oct 8, 2009 By KAREN CHAPMAN
PETALING JAYA: Universiti Malaya (UM) has put Malaysia back in the top 200 of the prestigious Times Higher Education (THE) – QS World University Rankings 2009 when it climbed 50 places from last year to 180 this year.
QS managing director Nunzio Quacquarelli said the rankings identified not just the most highly-ranked universities in the world, but also the best performing universities in key subject areas, the universities most targeted by employers, those producing the best research, those investing in teaching and those with the most international profile.
Another local university that improved in rankings was Universiti Teknologi Malaysia (UTM), standing at 320 compared to 356 last year.
Universiti Kebangsaan Malaysia (UKM), Universiti Sains Malaysia (USM) and Universiti Putra Malaysia (UPM) dropped between one and 41 places to 291, 314 and 345 respectively (see chart).
QS Quacquarelli Symonds Ltd Intelligence Unit head Ben Sowter said UM’s resurgence into the top 200 was clearly impressive.
“The apparent collective effort at the university to attract a greater proportion of international students suggests a progressive outlook,” he said in an e-mail interview.
Higher Education Minister Datuk Seri Mohamed Khaled Nordin told The Star that the ministry knew the universities’ weaknesses were in citations per faculty and peer review.
Harvard University tops the rankings once again; followed by Cambridge, Yale, University College London, Imperial College, Oxford University, Chicago University, Princeton University, Massachusetts Institute of Technology and California Institute of Technology. The highest ranked Asian institutions in the rankings are Tokyo University (22), Hong Kong University (24), Kyoto University (25) and National University of Singapore (30).
UM vice-chancellor Prof Datuk Dr Ghauth Jasmon said the success would be a major boost to the morale and motivation of all staff and students to work harder.
“The redefinition of key performance indicators for the academics and the new initiatives implemented in international networking, recruitment of international staff and students have produced a quick, positive impact,” he said.
UTM vice-chancellor Prof Datuk Dr Zaini Ujang said the improvement in the university’s rankings is a result of its strategy in networking, quality, strategic research, synergy and organisational culture.
On UKM’s drop from 250 to 291, its deputy vice-chancellor (Academic and International Affairs) Prof Dr Hassan Basri said the university was not surprised by the drop as THE-QS had indicated that the methodological adjustments and survey dynamics would significantly contribute to a drop in the scores for the academic peer review and employer survey criteria over a three-year period starting in the year 2008.
UPM vice-chancellor Prof Datuk Dr Nik Mustapha R. Abdullah said he was surprised that the university’s rankings dropped as its achievements were better last year compared to previously.
PETALING JAYA: Universiti Malaya (UM) has put Malaysia back in the top 200 of the prestigious Times Higher Education (THE) – QS World University Rankings 2009 when it climbed 50 places from last year to 180 this year.
QS managing director Nunzio Quacquarelli said the rankings identified not just the most highly-ranked universities in the world, but also the best performing universities in key subject areas, the universities most targeted by employers, those producing the best research, those investing in teaching and those with the most international profile.
Another local university that improved in rankings was Universiti Teknologi Malaysia (UTM), standing at 320 compared to 356 last year.
Universiti Kebangsaan Malaysia (UKM), Universiti Sains Malaysia (USM) and Universiti Putra Malaysia (UPM) dropped between one and 41 places to 291, 314 and 345 respectively (see chart).
QS Quacquarelli Symonds Ltd Intelligence Unit head Ben Sowter said UM’s resurgence into the top 200 was clearly impressive.
“The apparent collective effort at the university to attract a greater proportion of international students suggests a progressive outlook,” he said in an e-mail interview.
Higher Education Minister Datuk Seri Mohamed Khaled Nordin told The Star that the ministry knew the universities’ weaknesses were in citations per faculty and peer review.
Harvard University tops the rankings once again; followed by Cambridge, Yale, University College London, Imperial College, Oxford University, Chicago University, Princeton University, Massachusetts Institute of Technology and California Institute of Technology. The highest ranked Asian institutions in the rankings are Tokyo University (22), Hong Kong University (24), Kyoto University (25) and National University of Singapore (30).
UM vice-chancellor Prof Datuk Dr Ghauth Jasmon said the success would be a major boost to the morale and motivation of all staff and students to work harder.
“The redefinition of key performance indicators for the academics and the new initiatives implemented in international networking, recruitment of international staff and students have produced a quick, positive impact,” he said.
UTM vice-chancellor Prof Datuk Dr Zaini Ujang said the improvement in the university’s rankings is a result of its strategy in networking, quality, strategic research, synergy and organisational culture.
On UKM’s drop from 250 to 291, its deputy vice-chancellor (Academic and International Affairs) Prof Dr Hassan Basri said the university was not surprised by the drop as THE-QS had indicated that the methodological adjustments and survey dynamics would significantly contribute to a drop in the scores for the academic peer review and employer survey criteria over a three-year period starting in the year 2008.
UPM vice-chancellor Prof Datuk Dr Nik Mustapha R. Abdullah said he was surprised that the university’s rankings dropped as its achievements were better last year compared to previously.
Sunday, September 27, 2009
Minister denies IPTA and IPTS involved in fake Phd degrees
Higher Education Minister, Datuk Seri Khaled Nordin (second from right) entertaining his collegues from the Cabinet at his open house in Pasir Gudang today - Bernama pic
JOHOR BAHARU, Sept 27 — Higher Education Minister Datuk Seri Mohd Khaled Nordin said no public institutions of higher learning (IPTA) and private institutions of higher learning (IPTS) are involved in issuing fake PhD degrees.
“I also like to stress that there are no lecturers with fake PhDs teaching at IPTA and IPTS in the country,” he said at an Aidilfitri function organised by Pasir Gudang parliamentary constituency here today.
Khaled said his ministry had strict procedures in the recruitment of lecturers as checks were conducted on the qualification of candidates.
Information Communication and Culture Minister Datuk Seri Dr Rais Yatim had urged the Attorney-General Department to act against those who bought titles like “Datukships” and PhD degrees from overseas.
Rais said this was neccesary as such activities could create a generation of fake intellectuals.
Khaled said Rais’ statement could give a negative perception of Malaysian education and urged him to explain so that it could be discussed by the Cabinet.
On the new Universiti Pertahanan Nasional Malaysia (UPNM) campus in Pahang, he said the immediate concern was to provide teaching and learning facilities.
“We are constructing new buildings at the UPNM campus in Kuala Lumpur to house faculties.
“UPNM is a new university and as such need to be strengthened. The question of relocating the campus to Kuantan, Pahang will have to wait,” he said. — Bernama
JOHOR BAHARU, Sept 27 — Higher Education Minister Datuk Seri Mohd Khaled Nordin said no public institutions of higher learning (IPTA) and private institutions of higher learning (IPTS) are involved in issuing fake PhD degrees.
“I also like to stress that there are no lecturers with fake PhDs teaching at IPTA and IPTS in the country,” he said at an Aidilfitri function organised by Pasir Gudang parliamentary constituency here today.
Khaled said his ministry had strict procedures in the recruitment of lecturers as checks were conducted on the qualification of candidates.
Information Communication and Culture Minister Datuk Seri Dr Rais Yatim had urged the Attorney-General Department to act against those who bought titles like “Datukships” and PhD degrees from overseas.
Rais said this was neccesary as such activities could create a generation of fake intellectuals.
Khaled said Rais’ statement could give a negative perception of Malaysian education and urged him to explain so that it could be discussed by the Cabinet.
On the new Universiti Pertahanan Nasional Malaysia (UPNM) campus in Pahang, he said the immediate concern was to provide teaching and learning facilities.
“We are constructing new buildings at the UPNM campus in Kuala Lumpur to house faculties.
“UPNM is a new university and as such need to be strengthened. The question of relocating the campus to Kuantan, Pahang will have to wait,” he said. — Bernama
Friday, September 18, 2009
How to survive a thesis defence?
By Joe Wolfe
School of Physics
The University of New South Wales, Sydney
This document is an appendix to
How to write a thesis
* The thesis defence or viva is like an oral examination in some ways. It is different in many ways, however. The chief difference is that the candidate usually knows more about the syllabus than do the examiners.
* Consequently, some questions will be sincere questions: the asker asks because s/he doesn't know and expects that the candidate will be able to rectify this. Students often expect questions to be difficult and attacking, and answer them accordingly. Often the questions will be much simpler than you expect.
* In a curious relativistic effect, time expands in the mind of the student. A few seconds pause to reflect before answering seems eminently reasonable to the panel, but to the defender it seems like minutes of mute failure. Take your time.
* For the same reason, let them take their time. Let them finish, or even elaborate on, the question.
* The phrase "That's a good question" is useful. It flatters the asker and may get him/her onside, or less offside; it gives you time to think; it implies that you have understood the question and assessed it already and that you have probably thought about it before. If absolutely necessary, it can be followed by a bit more stalling "Now the answer to that is not obvious/straightforward..." which has some of the same advantages.
* If the nightmare ever did come true, and some questioner found a question that put something in the work in doubt... mind you this is thankfully very rare.... then what? Well the first thing would be to concede that the question imposes a serious limitation on the applicability of the work "You have identified a serious limitation in this technique, and the results have to be interpreted in the light of that observation". The questioner is then more likely to back off and even help answer it, whereas a straight denial may encourage him/her to pursue more ardently. Then go through the argument yourself in detail - showing listeners how serious it is while giving yourself time to find flaws in it or to limit the damage that will ensue. In the worst caese, one would then think of what can be saved. But all this is hypothetical because this won't happen.
* What usually happens is that the examiners have read the work typically twice, and looked closely at some parts that interested them most. These are usually the good bits. The examiners have standards to uphold, but they are not out to fail you. (Administratively, it is a lot more complicated to fail you than to pass you!) In general, they feel good about the idea of a new, fresh researcher coming into their area. You are no immediate threat to them. They have to show that they have read it and they have to give you the opportunity to show that you understand it (you do, of course). And they usually have a genuine interest in the work. Some of them may feel it is necessary to maintain their image as senior scholars and founts of wisdom. Judicious use of the "Good question", "Yes, you're right of course", "Good idea.." and "Thanks for that" will allow that with a minimum of fuss and a maximum of time for champagne drinking.
* If one of the examiners is real nasty, your thesis defence is probably not the best place and time in which to do anything about it, except perhaps for allowing him/her to demonstrate his/her nastiness clearly and thus to establish the support of the rest of the panel. If you want a major dispute, save it up for when you are on even ground, unless you are very, very sure of yourself and think that you have nothing to lose.
* Be ready for a 'free kick'. It is relatively common that a panel will ask one (or more) questions that, whatever the actual wording may be, are essentially an invitation to you to tell them (briefly) what is important, new and good in your thesis. You ought not stumble at this stage, so you should rehearse this. You should be able to produce on demand (say) a one minute speech and a five minute speech, and be prepared to extend them if invited by further questions. Do not try to recite your abstract: written and spoken styles should be rather different. Rather, rehearse answers to the questions: "What is your thesis about, what are the major contributions and what have you done that merits a PhD?".
* Read the first two bullet points again. Keep calm - and good luck!
Opinions expressed in these notes are mine and do not necessarily reflect the policy of the University of New South Wales or of the School of Physics.
Source: http://www.phys.unsw.edu.au/~jw/viva.html
School of Physics
The University of New South Wales, Sydney
This document is an appendix to
How to write a thesis
* The thesis defence or viva is like an oral examination in some ways. It is different in many ways, however. The chief difference is that the candidate usually knows more about the syllabus than do the examiners.
* Consequently, some questions will be sincere questions: the asker asks because s/he doesn't know and expects that the candidate will be able to rectify this. Students often expect questions to be difficult and attacking, and answer them accordingly. Often the questions will be much simpler than you expect.
* In a curious relativistic effect, time expands in the mind of the student. A few seconds pause to reflect before answering seems eminently reasonable to the panel, but to the defender it seems like minutes of mute failure. Take your time.
* For the same reason, let them take their time. Let them finish, or even elaborate on, the question.
* The phrase "That's a good question" is useful. It flatters the asker and may get him/her onside, or less offside; it gives you time to think; it implies that you have understood the question and assessed it already and that you have probably thought about it before. If absolutely necessary, it can be followed by a bit more stalling "Now the answer to that is not obvious/straightforward..." which has some of the same advantages.
* If the nightmare ever did come true, and some questioner found a question that put something in the work in doubt... mind you this is thankfully very rare.... then what? Well the first thing would be to concede that the question imposes a serious limitation on the applicability of the work "You have identified a serious limitation in this technique, and the results have to be interpreted in the light of that observation". The questioner is then more likely to back off and even help answer it, whereas a straight denial may encourage him/her to pursue more ardently. Then go through the argument yourself in detail - showing listeners how serious it is while giving yourself time to find flaws in it or to limit the damage that will ensue. In the worst caese, one would then think of what can be saved. But all this is hypothetical because this won't happen.
* What usually happens is that the examiners have read the work typically twice, and looked closely at some parts that interested them most. These are usually the good bits. The examiners have standards to uphold, but they are not out to fail you. (Administratively, it is a lot more complicated to fail you than to pass you!) In general, they feel good about the idea of a new, fresh researcher coming into their area. You are no immediate threat to them. They have to show that they have read it and they have to give you the opportunity to show that you understand it (you do, of course). And they usually have a genuine interest in the work. Some of them may feel it is necessary to maintain their image as senior scholars and founts of wisdom. Judicious use of the "Good question", "Yes, you're right of course", "Good idea.." and "Thanks for that" will allow that with a minimum of fuss and a maximum of time for champagne drinking.
* If one of the examiners is real nasty, your thesis defence is probably not the best place and time in which to do anything about it, except perhaps for allowing him/her to demonstrate his/her nastiness clearly and thus to establish the support of the rest of the panel. If you want a major dispute, save it up for when you are on even ground, unless you are very, very sure of yourself and think that you have nothing to lose.
* Be ready for a 'free kick'. It is relatively common that a panel will ask one (or more) questions that, whatever the actual wording may be, are essentially an invitation to you to tell them (briefly) what is important, new and good in your thesis. You ought not stumble at this stage, so you should rehearse this. You should be able to produce on demand (say) a one minute speech and a five minute speech, and be prepared to extend them if invited by further questions. Do not try to recite your abstract: written and spoken styles should be rather different. Rather, rehearse answers to the questions: "What is your thesis about, what are the major contributions and what have you done that merits a PhD?".
* Read the first two bullet points again. Keep calm - and good luck!
Opinions expressed in these notes are mine and do not necessarily reflect the policy of the University of New South Wales or of the School of Physics.
Source: http://www.phys.unsw.edu.au/~jw/viva.html
The literature review
What is a literature review?
According to Cooper (1988) '... a literature review uses as its database reports of primary or original scholarship, and does not report new primary scholarship itself. The primary reports used in the literature may be verbal, but in the vast majority of cases reports are written documents. The types of scholarship may be empirical, theoretical, critical/analytic, or methodological in nature. Second a literature review seeks to describe, summarise, evaluate, clarify and/or integrate the content of primary reports.'
The review of relevant literature is nearly always a standard chapter of a thesis or dissertation. The review forms an important chapter in a thesis where its purpose is to provide the background to and justification for the research undertaken (Bruce 1994). Bruce, who has published widely on the topic of the literature review, has identified six elements of a literature review. These elements comprise a list; a search; a survey; a vehicle for learning; a research facilitator; and a report (Bruce 1994).
Why do a literature review?
A crucial element of all research degrees is the review of relevant literature. So important is this chapter that its omission represents a void or absence of a major element in research (Afolabi 1992). According to Bourner (1996) there are good reasons for spending time and effort on a review of the literature before embarking on a research project. These reasons include:
* to identify gaps in the literature
* to avoid reinventing the wheel (at the very least this will save time and it can stop you from making the same mistakes as others)
* to carry on from where others have already reached (reviewing the field allows you to build on the platform of existing knowledge and ideas)
* to identify other people working in the same fields (a researcher network is a valuable resource)
* to increase your breadth of knowledge of your subject area
* to identify seminal works in your area
* to provide the intellectual context for your own work, enabling you to position your project relative to other work
* to identify opposing views
* to put your work into perspective
* to demonstrate that you can access previous work in an area
* to identify information and ideas that may be relevant to your project
* to identify methods that could be relevant to your project
http://www-development.deakin.edu.au/wmt/delete_from_uat.phpAs far as the literature review process goes, ultimately the goal for students is to complete their review in the allocated time and to ensure they can maintain currency in their field of study for the duration of their research (Bruce 1990).
The literature review process and the library
A good literature review requires knowledge of the use of indexes and abstracts, the ability to conduct exhaustive bibliographic searches, ability to organise the collected data meaningfully, describe, critique and relate each source to the subject of the inquiry, and present the organised review logically, and last, but by no means least, to correctly cite all sources mentioned (Afolabi 1992). The Library offers a range of training for research students that will assist with the production of literature reviews including sessions on electronic databases, using the bibliographic management software EndNote to download records, Internet searching using Netscape, Library catalogue searching, off-campus student orientation, subject resources, and research skills. Please contact your Liaison Librarian for more details.
EndNote reference management software
EndNote is a reference database that enables you to create your own list of bibliographical references. The EndNote software is provided on the Software Essentials CD or via the ITS Software Library and makes it possible to connect to selected library catalogues and online databases and to incorporate references directly into an EndNote database. It is also possible to export bibliographic records whilst you are searching the Deakin Library catalogue into EndNote. EndNote is a bibliography maker which can locate cited works in its databases and build and format appropriate lists automatically. It can be used in conjunction with a word processing package.
A tutorial has been developed by Deakin University Library staff to assist you to use this feature of EndNote.
Links to other sites (all open in a new browser window)
How to Critically Analyze Information Sources
Deakin Research Services
The Dissertation Doctor
Writing and Presenting Your Thesis or Dissertation
How to Write a PhD Thesis
Bibliography of cited references and other relevant sources
Afolabi, M. (1992) 'The review of related literature in research' International journal of information and library research, vol. 4, no. 1, pp. 59-66.
Bourner, T. (1996) 'The research process: four steps to success', in Greenfield, T. (ed), Research methods: guidance for postgraduates, Arnold, London.
Bruce, C. S. (1990) 'Information skills coursework for postgraduate students: investigation and response at the Queensland University of Technology' Australian Academic & Research Libraries, vol. 21, no. 4, pp. 224-232.
Bruce, C. (1993) 'When enough is enough: or how should research students delimit the scope of their literature review?', in Challenging the Conventional Wisdom in Higher Education: Selected Contributions Presented at the Ninteeth Annual National Conference and Twenty-First Birthday Celebration of the Higher Education Research and Development Society of Australasia Inc., HERDSA, University of New South Wales, Sydney, Australia. pp. 435-439.
Bruce, C. S. (1994) 'Research student's early experiences of the dissertation literature review' Studies in Higher Education, vol. 19, no. 2, pp. 217-229. Contains Full Text Articles
Bruce, C. (1994) 'Supervising literature reviews', in Zuber-Skerritt, O. and Ryan, Y. (eds), Quality in postgraduate education, Kogan Page, London.
Bruce, C. S. (1997) 'From Neophyte to expert: counting on reflection to facilitate complex conceptions of the literature review', in Zuber-Skerritt, O. (ed), Frameworks for postgraduate education, Southern Cross University, Lismore, NSW.
Caspers, J. S (1998) 'Hands-on instruction across the miles: using a web tuturial to teach the literature review research process' Research Strategies, vol. 16, no. 3, pp. 187-197. Contains Full Text Articles
Cooper, H. M. (1988) 'The structure of knowledge synthesis' Knowledge in Society, vol. 1, pp. 104-126
Cooper, H. M. (1989) Integrating research : a guide for literature reviews, 2nd ed, Sage Publications, Newbury Park, Calif.
Leedy, P. D. (1997) Practical research: planning and design, 6th ed, Merrill, Upper Saddle River, N.J.
Libutti, P.& Kopala, M. (1995) 'The doctoral student, the dissertation, and the library: a review of the literature' Reference Librarian, vol. 48, no. 5, pp. 5-25.
Mauch, J. E.& Birch, J. W. (2003) Guide to the successful thesis and dissertation: a handbook for students and faculty, 5th ed, Marcel Dekker, New York.
Library contacts
The Library has Liaison Librarians assigned to all Schools to assist students and staff. Contact details for your Liaison Librarian can be found at: http://www.deakin.edu.au/library/services/contacts/liaison/liaislib.php
Source: http://www.deakin.edu.au/library/findout/research/litrev.php
According to Cooper (1988) '... a literature review uses as its database reports of primary or original scholarship, and does not report new primary scholarship itself. The primary reports used in the literature may be verbal, but in the vast majority of cases reports are written documents. The types of scholarship may be empirical, theoretical, critical/analytic, or methodological in nature. Second a literature review seeks to describe, summarise, evaluate, clarify and/or integrate the content of primary reports.'
The review of relevant literature is nearly always a standard chapter of a thesis or dissertation. The review forms an important chapter in a thesis where its purpose is to provide the background to and justification for the research undertaken (Bruce 1994). Bruce, who has published widely on the topic of the literature review, has identified six elements of a literature review. These elements comprise a list; a search; a survey; a vehicle for learning; a research facilitator; and a report (Bruce 1994).
Why do a literature review?
A crucial element of all research degrees is the review of relevant literature. So important is this chapter that its omission represents a void or absence of a major element in research (Afolabi 1992). According to Bourner (1996) there are good reasons for spending time and effort on a review of the literature before embarking on a research project. These reasons include:
* to identify gaps in the literature
* to avoid reinventing the wheel (at the very least this will save time and it can stop you from making the same mistakes as others)
* to carry on from where others have already reached (reviewing the field allows you to build on the platform of existing knowledge and ideas)
* to identify other people working in the same fields (a researcher network is a valuable resource)
* to increase your breadth of knowledge of your subject area
* to identify seminal works in your area
* to provide the intellectual context for your own work, enabling you to position your project relative to other work
* to identify opposing views
* to put your work into perspective
* to demonstrate that you can access previous work in an area
* to identify information and ideas that may be relevant to your project
* to identify methods that could be relevant to your project
http://www-development.deakin.edu.au/wmt/delete_from_uat.phpAs far as the literature review process goes, ultimately the goal for students is to complete their review in the allocated time and to ensure they can maintain currency in their field of study for the duration of their research (Bruce 1990).
The literature review process and the library
A good literature review requires knowledge of the use of indexes and abstracts, the ability to conduct exhaustive bibliographic searches, ability to organise the collected data meaningfully, describe, critique and relate each source to the subject of the inquiry, and present the organised review logically, and last, but by no means least, to correctly cite all sources mentioned (Afolabi 1992). The Library offers a range of training for research students that will assist with the production of literature reviews including sessions on electronic databases, using the bibliographic management software EndNote to download records, Internet searching using Netscape, Library catalogue searching, off-campus student orientation, subject resources, and research skills. Please contact your Liaison Librarian for more details.
EndNote reference management software
EndNote is a reference database that enables you to create your own list of bibliographical references. The EndNote software is provided on the Software Essentials CD or via the ITS Software Library and makes it possible to connect to selected library catalogues and online databases and to incorporate references directly into an EndNote database. It is also possible to export bibliographic records whilst you are searching the Deakin Library catalogue into EndNote. EndNote is a bibliography maker which can locate cited works in its databases and build and format appropriate lists automatically. It can be used in conjunction with a word processing package.
A tutorial has been developed by Deakin University Library staff to assist you to use this feature of EndNote.
Links to other sites (all open in a new browser window)
How to Critically Analyze Information Sources
Deakin Research Services
The Dissertation Doctor
Writing and Presenting Your Thesis or Dissertation
How to Write a PhD Thesis
Bibliography of cited references and other relevant sources
Afolabi, M. (1992) 'The review of related literature in research' International journal of information and library research, vol. 4, no. 1, pp. 59-66.
Bourner, T. (1996) 'The research process: four steps to success', in Greenfield, T. (ed), Research methods: guidance for postgraduates, Arnold, London.
Bruce, C. S. (1990) 'Information skills coursework for postgraduate students: investigation and response at the Queensland University of Technology' Australian Academic & Research Libraries, vol. 21, no. 4, pp. 224-232.
Bruce, C. (1993) 'When enough is enough: or how should research students delimit the scope of their literature review?', in Challenging the Conventional Wisdom in Higher Education: Selected Contributions Presented at the Ninteeth Annual National Conference and Twenty-First Birthday Celebration of the Higher Education Research and Development Society of Australasia Inc., HERDSA, University of New South Wales, Sydney, Australia. pp. 435-439.
Bruce, C. S. (1994) 'Research student's early experiences of the dissertation literature review' Studies in Higher Education, vol. 19, no. 2, pp. 217-229. Contains Full Text Articles
Bruce, C. (1994) 'Supervising literature reviews', in Zuber-Skerritt, O. and Ryan, Y. (eds), Quality in postgraduate education, Kogan Page, London.
Bruce, C. S. (1997) 'From Neophyte to expert: counting on reflection to facilitate complex conceptions of the literature review', in Zuber-Skerritt, O. (ed), Frameworks for postgraduate education, Southern Cross University, Lismore, NSW.
Caspers, J. S (1998) 'Hands-on instruction across the miles: using a web tuturial to teach the literature review research process' Research Strategies, vol. 16, no. 3, pp. 187-197. Contains Full Text Articles
Cooper, H. M. (1988) 'The structure of knowledge synthesis' Knowledge in Society, vol. 1, pp. 104-126
Cooper, H. M. (1989) Integrating research : a guide for literature reviews, 2nd ed, Sage Publications, Newbury Park, Calif.
Leedy, P. D. (1997) Practical research: planning and design, 6th ed, Merrill, Upper Saddle River, N.J.
Libutti, P.& Kopala, M. (1995) 'The doctoral student, the dissertation, and the library: a review of the literature' Reference Librarian, vol. 48, no. 5, pp. 5-25.
Mauch, J. E.& Birch, J. W. (2003) Guide to the successful thesis and dissertation: a handbook for students and faculty, 5th ed, Marcel Dekker, New York.
Library contacts
The Library has Liaison Librarians assigned to all Schools to assist students and staff. Contact details for your Liaison Librarian can be found at: http://www.deakin.edu.au/library/services/contacts/liaison/liaislib.php
Source: http://www.deakin.edu.au/library/findout/research/litrev.php