Overlapping Topics
I love when the Instructional Technology classes navigate the psychological research waters, because it just reinforces what I already know, while giving me a fresh perspective.
For instance, tonight in class, we covered quantitative and qualitative research methodologies. In the psychology realm, qualitative research is considered good, a case study or a more in depth probing into a topic that may or may not be applied to the population at large. The resources just aren't there to do a lot of qualitative research. (Think Quality here to remember the differences).
No, in behavioral sciences, it is more important to conduct quantitative research, to know that what you hypothesize and measure can be found in the population at large. (Think Quantity.) For an example of why quantitative measure is important, you remember how researchers in Great Britain said they had found that immunizations caused autism? Remember the firestorm it generated?
The doctors later admitted that they'd fudged the results, but more importantly, there were only TWELVE participants in the research. TWELVE. They made broad assumptions about an entire population based on the flawed data collected on TWELVE individuals.
In Instructional Technology, wherever possible, the emphasis is on getting a broader base of information from or about the end user. If the budget allows, collecting more data from each subject is valued much more than getting surface information from many.
This will be interesting when I combine the two approaches in doctoral studies. When research methods collide may end up being more fascinating to some that the topic I've chosen!
For instance, tonight in class, we covered quantitative and qualitative research methodologies. In the psychology realm, qualitative research is considered good, a case study or a more in depth probing into a topic that may or may not be applied to the population at large. The resources just aren't there to do a lot of qualitative research. (Think Quality here to remember the differences).
No, in behavioral sciences, it is more important to conduct quantitative research, to know that what you hypothesize and measure can be found in the population at large. (Think Quantity.) For an example of why quantitative measure is important, you remember how researchers in Great Britain said they had found that immunizations caused autism? Remember the firestorm it generated?
The doctors later admitted that they'd fudged the results, but more importantly, there were only TWELVE participants in the research. TWELVE. They made broad assumptions about an entire population based on the flawed data collected on TWELVE individuals.
In Instructional Technology, wherever possible, the emphasis is on getting a broader base of information from or about the end user. If the budget allows, collecting more data from each subject is valued much more than getting surface information from many.
This will be interesting when I combine the two approaches in doctoral studies. When research methods collide may end up being more fascinating to some that the topic I've chosen!
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