Nearly every leader in our nation is saying that we need to have students get more STEM education (Science, Technology, Engineering, and Math), so that our country will not fall behind technologically and economically from the rest of the world. But, what they don’t say (possibly, because they don’t know), is that the type of math that is needed for Information and Communication Technologies (ICT) and Computer Science (CS) is not the math that is normally taught in high school.
I have started to read the book Probability Theory: The Logic of Science, by the late E. T. Jaynes. From what I understand so far, I think there is a high plausibility that it will help me have a more unified and deeper understanding of probability (and hence statistics). In reading the preface, he makes some interesting observations about probability and human thinking, and it seems quite apropos, and relevant to the recent advances in the fields of artificial intelligence, such as the recent match of Go.
A quote from the book that particularly struck me was the following:
… it is clear that probability theory is telling us something about the way our own minds operate when we form intuitive judgments, of which we may not have been consciously aware. Some may feel uncomfortable at these revelations; others may see in them useful tools for psychological, sociological, or legal research.
I wrote recently about my thoughts on whether MOOCs have been a failure. Udacity is showing that they are not, and is an example of where the potential of technology to “disrupt” a market is finally entering the realm of education. And it has now put its “money where its mouth is”, by doing something no college (that I know of) has done: guarantee its graduates a job. But what is the catch (if there is one)?
There is a paradox: Humanity’s most developed organizations and systems are based upon what is learned in our education systems; yet, the field of education lags behind nearly all others. One such area I have seen, is how feature-poor Student Information Systems (SIS) are. Despite such systems being case studies in many database books, most of these systems do not use any data science methods to improve operations. Specifically, I have usually not seen active security, predictive analytics, nor even resource optimization as features. Here is why these are important to have, and my invitation for SIS providers to come into the 21st century.
As I work to enter back into a doctoral program with UNISA, I have realized that I haven’t yet had a quick cohesive explanation of why it is so important to me to do the research I am doing. So here is that attempt to explain why I believe what I’m working on will make a significant contribution to the field of education, and beyond that, why it could be something that truly changes the world, and also how others can get involved. Who knows, maybe some day this will become a real TED Talk 🙂
As part of my data science self-study, I was reading Flaws and Fallacies in Statistical Thinking, and ran across the quote by H.G. Wells: “Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.” Since I know many quotes (even those in textbooks) are at least partially apocryphal, I searched, and found the original quote to be: