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frankm | page | Dec 10, 2008 - 6:35pm

This page holds work for the Fall 2008 IS 366a course. You can view other people's portfolios by clicking on the IS366a tag on the bottom of this page, or by editing this page and looking in the sidebar.

 

 

That having been said, my takeaway from this class is a much clearer understanding of the qualitative research process.   

 

 

Like many of my classmates, my early training and education involved primarily quantitative methods of research, including collecting data from experiments -- that didn't really include humans at all.  Most experimentation that I conducted in IS&T was what some of my professors have characterized as "computer science".  Be that as it may, until I entered SISAT, I really had no other concept of useful data that could be collected in the IS&T industry setting.  Most of the data collection that involved people, I considered "marketing".  

 

 

 

Now, it's different.  I know more about human component of IS&T and its relevance to academia and the industry.  The final piece of the man/machine puzzle is observing and reporting on the way that people and information and machines do their jobs.  And how do they affect each other in how those jobs are done.  (If you want to substitute "activity" for "job", it might be just as appropriate.)  In this semester, I have discovered that it is definitely possible to acquire and disseminate useful information by following the methodologies, formats, and protocols of qualitative studies.  

 

 

I actually have data in the form of interviews that I, and a classmate, have collected.  The problem was trying to figure out how to properly analyze and disseminate the information that we found useful.  I think that I now have the tools to take a crack getting the first version out the door during the break.  

 

 

If there is one thing that I would have liked to do, and would have perhaps found even more useful down the road, it would have been the collection and analysis of qualitative data using automated tools.  I'm sure that I will find a way to deal with that omission down the road one way or another.  


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frankm | page | Nov 1, 2008 - 8:21pm

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frankm | page | Nov 1, 2008 - 8:21pm

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frankm | page | Nov 1, 2008 - 8:21pm

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frankm | weblog comment | Dec 4, 2006 - 1:13pm
I also found Chapter 4 interesting.  All the studies about short term and long term memory and chunks really gave me insight into the human mind.  Before reading this, I thought that basic computers were designed around logic circuits and only only robotics was obsessed with thinking.  Now I realize that basic computer memory structure is also modeled after the human mind.  You say that we tend to design machines that act like we do.  So is that why they are temperamental and break down?

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frankm | weblog comment | Nov 26, 2006 - 6:59pm
I agree with you that if the authors add some graphical data representations in this paper, it will be easier to understand the data. In addition, I think that extrinsic motivators do not work for knowledge sharing because of complexity of humans' behavior and attitude. They may feel guilty if they will share their knowledge due to rewards and money. They may think that their knowledge is much more valuable than money. Sometimes an human's thought is very difficult to understand and predict.

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frankm | weblog comment | Nov 26, 2006 - 6:47pm
The word that seems to be missing from the article is 'relationships.'  People share based on relationships.  The organization can foster certain relationships to create sharing environments.  I think that was one lesson from agile programming.  A certain level ofsSocializing is encouraged to create relationships that foster sharing.  In any case there has to be a reward of some kind.  As Frank pointed out elsewhere, it's a real challenge given the extreme competitiveness in U.S. companies.

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frankm | weblog | Nov 26, 2006 - 6:16pm

Wow.  This is a heavy read.  And lots to think about.  


I don't know why I thought Simon was from Britain.  I was halfway through Chapter 3 when I checked out the back cover and saw the man's credentials.  Pretty interesting.  He's a professor of Computer Science and Psychology with a Nobel Prize in Economics.  That's what I call a Renaissance Man.  


I have been most impressed with Chapter 3 so far.  The comparison of human activity with those of an ant trying to get back into the anthill gave me pause for reflection.  I'm not sure if I would completely agree with Simon on that one point, but it is an interesting point of view.  


Tomorrow (Monday), I'm going to be teaching a little lesson on encryption in my CalPoly Extension class – at the request of the students.  I think I'm going to use his DONALD+GERALD=ROBERT cryptarithmetic example to confound the class – both of them!  That was a really interesting little exercise in testing one's problem solving creativity.  


I find it also interesting in Chapter 4, where Simon is approaching Short Term Memory and Long Term Memory  challenges like he is designing a new chip!  There are obvious parallels in the architectures and I believe, perhaps wrongly, that we tend to design machines that act like we do, if they don't always look like we do.  So perhaps eventually we (humans) will design and build CPUs that behave more and more like the real human mind.  


I just hope we give them a nice personality;-)  



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frankm | weblog comment | Nov 26, 2006 - 5:14pm
Since there has been so much research on TRA, I wonder how applicable this study is for the field of IS. It seems to me that some of the recommended future work by these authors have already been done, such as knowledge brokering, before they published this article. I guess there are lags in publishing time that can make work seem outdated very easily.

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frankm | weblog comment | Nov 26, 2006 - 12:22pm
I was also surprised that even though the companies studied had extrinsic motivators like mileage points and bonuses they were not the factor that influenced knowledge sharing.  I am not sure it would transfer well to all other countries--maybe Japan with very strong company loyalty and lifetime jobs.  But in the U.S. where layoffs are frequent and your knowledge is your currency, I suspect that it would take bonuses or promotions to extract a lot of a person's knowledge.  I also found it interesting that most of the hypotheses had attitude first and then intention second.

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