How to write an abstract?

To begin with, this post is for my use only. It might serve as a blatant no for the readers of this column which even though I wish I had in thousands are quite few….Image

Anyway, continuing further, I have embarked on a tedious journey and this blog will serve as my flag-post, a constant reminder of major issues that I might forget during this long arduous journey.

I found this nice article on a website (http://bit.ly/1kxrjw0) and am summarising it down;

Abstract has become very important these days, because no one has the time to read your long paper honest but that’s the truth. Unless, you write a few sentences that catapult the reader to jump into its car seat and make a mad rush to the library to read your full paper. Until then, the abstract that you have written is trash. So here are some key-points, that you got to remember, while you sell your paper to the research community!

  1. Motivation: See, you get motivated after you have read something and identified a gap so that gap is your problem statement that you got to write first and post which you write its results. This section should include the importance of your work, the difficulty of the area that you’re studying and the impact that it might have if you are successful.
  2. Problem statement: what’s the problem that you are trying to solve, what is its scope? Please ensure not to use too much jargon
  3. Approach: How did you solve the problem, what important variables did you control, ignore or measure? Did you use simulation, analytic models, prototype construction, or analysis of field data for an actual product?
  4. Results: What’s the answer?

Conclusions: What are the implications of your answer? Is it going to change the world (unlikely), be a significant “win”, be a nice hack, or simply serve as a road sign indicating that this path is a waste of time (all of the previous results are useful)? 

Theo Priestley: Unlocking Big Data Silos Through Integration

Theo Priestley: Unlocking Big Data Silos Through Integration – http://pulse.me/s/Ioone

3MT – Flinders University

3MT – Flinders University – http://www.flinders.edu.au/3mt/?utm_medium=referral&utm_source=pulsenews

Writing for scientific publication: 3 common mistakes

Ashish Dutt:

This post will be a constant reminder to me. Therefore, it aught to be reblogged. Thank you, for this resource full article.

Originally posted on The Research Whisperer:

Marc BaldwinMarc D. Baldwin is the founder & CEO of Edit911 Editing Service. He is also Professor of English at Hillsborough Community College and a published author.

You can find more of his writing and editing advice on the Edit911 blog.


One of the most important things you will do as a scientist or researcher is publish your work. It isn’t just a matter of sharing information—an integral part of the scientific process—it’s also about furthering your career.

Publishing your work in a scientific journal is a requirement toward earning a graduate degree at some institutions. Beyond graduation, getting published is necessary for a career in academia and, increasingly, in industry as well.

I have proofread and reviewed hundreds of original manuscripts in my career as a research scientist and lecturer. I’ve noticed over the years that most mistakes can be placed into a few simple categories. In this…

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The MOOC Express – Less Hype, More Hope

Ashish Dutt:

Tomes of people are flocking towards this new abridged edition of online learning. But what remains unanswered so far is, “The MOOC paradigm invigorate learning?”.

Originally posted on MOOCtalk:

A real-time chronicle of a seasoned professor just about to launch the fourth edition of his massively open online course.

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Last week, I headed off to Arlington, Texas, to participate in a large, international conference on MOOC education, part of the Gates Foundation funded MOOC Research Initiative (MRI). While the founders of the big, massively-funded American MOOC (“MFAM”) platforms Coursera, edX, Udacity, and Novo Ed capture most of the media’s attention, this conference was led by the small band of far less well known Canadian online-education pioneers who actually developed the MOOC concept some years earlier, in particular George Siemens and Stephen Downes who organized and ran the first MOOC in 2008, and David Cornier who forever has to live with having coined the name “MOOC”.

(There were so many Canadians in Arlington, they brought their own weather with them, as you can see from the photograph. The conference ended with participants having…

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A Java based approach to elegant data mining

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Learning Strategies and Learning Styles by Ronald R. Schmeck

France_in_XXI_Century._School

I recently read this classical text on learning styles and was instantly captivated by it. The author presents a very subtle yet a profound insight into this much discussed subject in educational psychology. While searching for a picture that could best classify the following excerpt below, i was instantly smitten by the picture that you see on your right.

The reader who approaches this topic for the first time may be confused by the usage of the terms “cognitive style” and “learning style.  “Snow, Corno, and Jackson (1996), under the heading “personal styles “, write that “no category we have covered contains a more voluminous, complex and controversy-laced literature than that of personal styles. They classified the kinds of constructs that have been studied under six headings. These are:

Cognitive styles” involved in perception and thinking (e.g. field independence versus dependence, reflection versus impulsivity.

Learning styles” involved in approaches to learning and studying (e.g.  Deep versus surface processing, comprehension learning versus operation learning).

Expressive styles,” involved in verbal or nonverbal communication (e.g. tempo, constricted versus expansive).

Response styles” involved in self-perception and self-report (e.g., acquiescence, deception). “Defensive styles” involved in accommodating anxiety and conflict (e.g. obsessive compulsive, hysterical),”Cognitive controls” a subset of style like but function-specific and uni-polar controls on attention and behaviour (e.g. constricted versus flexible control)”.

Riding and Rayner (1998) argued that learning styles are a subset of cognitive styles, and in this they agreed with Sternberg and Grigorenko (1997), who also reviewed the literature on this concept. Sternberg and Grigorenko classified styles as cognition centered, personality centered, or activity centered. Those that are cognition centered have a relationship with ability and measures of intelligence, The MBTI personality measure that has been much used among engineering students is as its focus implies personality centered. The other instrument that has appealed to engineers, The Learning Styles Inventory (Kolb) is activity-centered. It is a consolation to this writer that Snow, Corno and Jackson(1996) decided not to make any sharp distinction between learning styles and cognitive styles, or between styles and approaches. Nevertheless, there have been some distinctions and we begin with a discussion of learning strategies.

Learning strategies are devices that we use to cope with the learning environments we find ourselves in. Learning styles are dispositions we have to learning. They are preferred ways of organizing what we see and think. It has been shown that learning environments and, in particular, the assessments used can have a harmful or less than positive effect on learning, as for example, if they cause surface learning. For this reason the effects of an outcomes-based approach to assessment needs to be evaluated in terms of its effects on learning. From the perspective of engineering it has been shown that engineers require a variety of learning styles when they are engaged in projects. They need, for example, to be both convergent and divergent thinkers. The case for this view is presented. A brief discussion of field independent and field-dependent styles of thinking follows. Although spatial ability is not strictly speaking a style, it is important in engineering design. Engineers need to be able to visualize, and consequently they need a highly developed spatial ability.

Therefore, since we have predispositions to learn, the style that we have may be in conflict with the style of teaching to which we are exposed, a major question is whether teaching and learning styles should be matched. Given that engineers need a variety of styles, it is incumbent on teachers to foster their development, and that suggests teachers may have to change their teaching styles. Engineers have used a number of instruments to determine the learning styles of their students. These include Kolb’s Learning Styles Inventory and a summary of work that has been done to use it as a scheme for the design of instruction is given. Variations of the Kolb model are summarized in particular the 4MAT scheme and Honey and Mumford model.

Felder and Silverman identified 32 learning styles and developed an inventory to test for these among engineering students. This is discussed. Style and personality are related and influence the way we learn in particular environments. Engineers have been particularly interested in the Myers Briggs Personality Indicator, and much is known about the personality profiles of engineering students from this test. Much attention has been paid in higher education to learning strategies although it seems that in engineering education more attention has been focused on learning styles. However, in relation to the learning of concepts, strategies are very important, and the strategies that students employ may be strongly influenced by the instructional method and assessment procedures used (Heywood, 2000).

Marton found that “for some (students) learning is through discourse and for others learning is discourse”. Those who adopt the former strategy get involved in the activity while those who take the latter view allow learning to happen to them. It is this second group who are surface learners, who pay only superficial attention to the text, who are passive, who do not reflect, and who do not appreciate that understanding involves effort.

The complexity of learning and points out the fact that different learning environments such as the disciplines or those deriving from the culture can influence the conceptions that we have of learning.

References

Felder, R. M and L. K.Silverman (1988). Learning and teaching styles in engineering education. Engineering Education, 78,674-681.

Heywood, J (2000). Assessment in Higher Education Student Learning, Teaching, Programmes and Institutions. Jessica Kingsley, London.

Marton, F., Dall’ Alba, G., and E. Beaty (1993). Conceptions of Learning. International Journal of Education,19,(3),277-299.

Schmeck, Ronald R. , 1988. Learning Strategies and Learning Styles (Perspectives on Individual Differences). 2nd ed. na: Springer.

Snow, R. E., Como, L., and D. Jackson(1996). Individual differences in affective and conative functions. In D. C. Berliner and R. C. Calfe (eds.).  Handbook of Educational Psychology. American Psychological Association. Macmillan, New York.

Sternberg, R. J., and E. L. Grigorenko (1997). Are cognitive styles still in style? American Psychologist, 52,700-712.

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