Posts Tagged ‘Designing experiments’

Soft skills? Broad learning skills: Bye bye STEM skills?

Posted by: adonis49 on: September 26, 2020

Soft skills? Broad learning skills: Bye bye STEM skills?

Google finds STEM skills aren’t the most important skills

January 5, 2018.

Lou Glazer is President and co-founder of Michigan Future, Inc., a non-partisan, non-profit organization. Michigan Future’s mission is to be a source of new ideas on how Michigan can succeed as a world class community in a knowledge-driven economy. Its work is funded by Michigan foundations.

A Washington Post column on research done by Google on the skills that matter most to its employees success. Big surprise: it wasn’t STEM. The Post writes:

Sergey Brin and Larry Page, both brilliant computer scientists, founded their company on the conviction that only technologists can understand technology.

Google originally set its hiring algorithms to sort for computer science students with top grades from elite science universities.

In 2013, Google decided to test its hiring hypothesis by crunching every bit and byte of hiring, firing, and promotion data accumulated since the company’s incorporation in 1998.

Project Oxygen shocked everyone by concluding that, among the 8 most important qualities of Google’s top employees, STEM expertise comes in dead last.

The 7 top characteristics of success at Google are all soft skills:

Like being a good coach; communicating and listening well; possessing insights into others (including others different values and points of view); having empathy toward and being supportive of one’s colleagues; being a good critical thinker and problem solver; and being able to make connections across complex ideas.

Those traits sound more like what one gains as an English or theater major than as a programmer.

Could it be that top Google employees were succeeding despite their technical training, not because of it?

After bringing in anthropologists and ethnographers to dive even deeper into the data, the company enlarged its previous hiring practices to include humanities majors, artists, and even the MBAs that, initially, Brin and Page viewed with disdain.

This is consistent with the findings of the employer-led Partnership for 21st Century Learning who describe the foundation skills for worker success as the 4Cs: collaboration, communication, critical thinking and creativity.

And the book Becoming Brilliant which adds to those four content and confidence for the 6Cs.

And consistent with the work on the value of a liberal arts degree of journalist George Anders laid out in his book You Can Do Anything and in a Forbes article entitled That Useless Liberal Arts Degree Has Become Tech’s Hottest Ticket.

It’s far past time that Michigan policymakers and business leaders stop telling our kids if they don’t get a STEM related degree they are better off not getting a four-year degree. It simply is not accurate.

(Not to mention that many of their kids are getting non-STEM related four-year degrees.)

And instead begin to tell all kids what is accurate that the foundation skills––as Google found out––are Not narrow occupation-specific skills, but rather are broad skills related to the ability to work with others, think critically and be a lifelong learner.

The kind of skills that are best built with a broad liberal arts education.

The Post concludes:

No student should be prevented from majoring in an area they love based on a false idea of what they need to succeed.

Broad learning skills are the key to long-term, satisfying, productive careers.

What helps you thrive in a changing world isn’t rocket science. It may just well be social science, and, yes, even the humanities and the arts that contribute to making you not just workforce ready but world ready.

Note: About time students takes seriously the importance of general knowledge in everything they undertake. Most important of all is to learn designing experiments, developing the experimental mind that does Not come naturally, but with training.

Tags: adonis49, Becoming Brilliant, Broad learning skills, Designing experiments, George Anders, hiring hypothesis, knowledge-driven economy, Larry Page, Lou Glazer, Sergey Brin, soft skills, STEM skills

Graduate students: Liars, cheaters, and procrastinators

Posted by: adonis49 on: November 2, 2010

I created a new graduate course for students about ready to start finding a PhD proposal. The idea was to facilitating the task in matter of topics that a student might feel more inclined to selecting for further investigation. The purpose was initiating graduate students to openly extending feedback to their colleagues and to learn asking the right questions. The method was getting aware of the various scientific methods available in approaching and resolving problems.

The course intended for each student to researching four topics, among peer-reviewed articles: Two in different engineering or scientific disciplines and two in social sciences fields of study. Each topic will be followed up by another supporting or related subject article to be presented in each session. The final two sessions were reserved for the presentation of a definite topic that students have decided for submitting draft proposals. That proposal had nothing to do with the advisor’s line of research, but the student would greatly benefit if he shared his interest with his advisor.

There are a few graduate students who directly resume and build upon their MS thesis, saving many years of searching and suffering. Those particular students were welcomed and encouraged to enroll in the class: The only condition is that the “potential proposal” presented in the last two sessions should be different from the proposed thesis. The rational is for a graduate student to learn flexibility in focusing on several topics of research: The opportunity for that kind of research diversity and availability of alternative perspectives will be rare to come by in a “professional environment” later on.

I got the phone numbers of students and did call them during the semester to follow-up on their academic progress and behaviors. Students were not forbidden to calling me up: I lack time and resources for additional tasks that end up within the psychological domain of expertise.

For example, two days after each session, I would reserve an hour to calling up the students with sample questions such as: “Did you find an article? What is the title? You don’t remember the title then you may fill me on the subject matter. You cannot because you had no time to browse through the article? What if the day before the session you realized that the title was misleading? What if the article does not involve any experiment? You have a few more important courses to focus on? Define me what is “more important”….

In the first session, I distributed sample articles in many fields, disciplines, and experimental methods. The articles were distributed in random to students. I select one student to read his selected article to class. Actually, every session requires a student to reading to class.

The next session is basically a “looking dumb” experiment: First, all students were confused explaining new topics they were not familiar with; second, they had no idea what kind of questions to ask that made sense to them; and third, the most important factor, every student was considering the backlash of the other students when his turn comes to present his article. The student is saying: “If I ask corny questions then, the other students will get their revenge and harass me pretty good. Let me go through this course in the most advantageous peace of mind.”

Fact is, most students have not be exposed to any kind of “experimental design” courses; they had no idea what is meant by dependent variables, independent variables, control variables, or confounding variable… The students manipulated equations for years but have no idea what they are manipulating and how to discriminate among the variables. Students sat in lab courses and still have no idea of experimental methods.

The students are smart, but the logic for designing experiment and controlling variables or factors is not familiar to them: This logic requires training and frequent initiations. I tend to believe that knowledge of designing experiments is the basic common denominator method in sciences, whether hard or soft sciences. I am bewildered that most engineering and scientific fields do not require a single course in the logic or philosophy of designing experiments. How can any professional comprehend articles outside his domain if he is not initiated to designing experiments?

I gave more weight to social sciences articles because they were sources of demonstrating the far more complex experiments that social scientist are confronted with: The hundreds of human variables to control in order not to end up with confounding results that ruin months of assiduous work.

Most probably, my course was designed to initiate students on methods of designing experiments before it is too late when approaching their thesis: It is a way of encouraging the students to enrolling in “design of experiments” courses, even if not required (which was generally the case in engineering and sciences).

I used to retain two students after each session and give them each an article to read. The following session delivers what I expected: half the follow-up articles were identical to the one I handed the two students with comical excuses of how they related to their original topic.

The third session was meant to overcoming barriers erected between the presenter and the other students. Anyway, one of the main objectives of this course is asking openly the right questions with the purpose of comprehending another topic and learning to focus on the presentation instead of worrying on “when is my turn and how stupid will I look?” This objective must be the hardest to achieving and the most useful, if successful, to a professional career.

Note: This post is a fictional short story on teaching methods.

Tags: adonis49, Designing experiments, Graduate students, Human Factors, humor, hundreds of human variables, peer-reviewed articles, procrastinators, professional career, social sciences, writing

How causality relation and invariant are perceived by the brain

Posted by: adonis49 on: December 25, 2009

How causality relation and invariant are perceived by the brain; (Dec. 24, 2009)

We are born with 25% of the total number of synapses that grown up will form. Neurons have mechanisms of transferring from one section of the brain to other parts when frequent focused cognitive processes are needed. A child can perceive one event following another one but it has no further meaning but simple observation. A child is not surprised with magic outcomes; what is out of the normal for a grown up is as valid a phenomenon as another to him (elephant can fly).

The brain attaches markers or attributes to impressions that it receive from the senses. Four markers that I call exogenous markers attach to impressions as they are “registered” in the brain coming from the outside world. At least four other markers, I label “endogenous markers” are attached to internal cognitive processing and are attached to information when re-structuring or re-configurations are performed during the dream periods because massive computations are needed to these endogenous markers. There are markers that I call “reverse-exogenous” and are attached to information meant to be recorded on external means such as writing or performing art work. Maybe animals lack these reverse exogenous markers since evolution didn’t endow them with external performing limbs for writing, sculpting, painting, or doing music.

The first exogenous marker directs impressions in their order of successions. The child recognizes that this event followed the other one within a short period of occurrence. His brain can “implicitly” store the two events are following in succession in a qualitative order (for example the duration of the succession is shorter or longer than the other succession). I label this marker as “Time recognizer” in a qualitative sense of sensations.

The second marker registers and then stores an impression as a spatial configuration. At this stage, the child is able to recognize the concept of space but in a qualitative order; for example, this object is closer or further from the other object. I call this marker “space recognizer”.

The third marker is the ability to delimit a space when focusing on a collection of objects. Without this ability to first limit the range of observation (or sensing in general) it would be hard to register parts and bits of impressions within a first cut of a “coherent universe”. I label this marker “spatial delimiter”

The fourth marker attaches a “strength” of occurrence as the impression is recognized in the database. The child cannot count but the brain is already using this marker for incoming information. In a sense, the brain is assembling events and objects in special “frequency of occurrence” database during dream periods and the information are retrieved with a qualitative order strength of sensations in frequency. I call this attribute “count marker”.

The fifth marker is an endogenous attributes: this marker is attached within the internal export/import of information in the brain. This attribute is a kind of “correlation” quantity that indicates same/different trends of behavior of events or objects. In a sense, this marker will internally sort data as “analogous” or contrary collections on a time scale. People have tendency to associate correlation with cause and effect relation but it is not. A correlation quantity can be positive (two variables have the same behavioral trend in a system) or negative quantity (diverging trends). With the emergence of the 5^th marker the brain has grown a quantitative threshold in synapses and neurons to starting massive computations on impressions stored in the large original database.

The sixth marker is kind of a “probability quantity” that permits the brain to order objects according to “plausible” invariant properties in space (for example objects or figures are similar according to a particular property, including symmetrical transformations). I label this the “invariant marker” and it re-structures collections of objects and shapes in structures such as hereditary, hierarchical, or circular.

The seventh marker recognizes interactions among variables and interacts with reverse exogenous markers since a flow with outside perceptions is required for comprehension. I label this the “design marker”. Simple perceived relationships between two events or variables are usually trivial and mostly wrong; for example thunder follows lightning and thus wrongly interpreted as lightning generates thunder. Simple interactions are of the existential kind, the Pavlov reactions, where an existential rewards, such as food, are involved. Interactions among more than two variables are complex for interpretations in the mind. Designing experiments is a very complex cognitive task and not amenable to intuition: it requires learning and training to appreciating the various cause and effects among the variables.

The brain is very performing for rhetorical associations and cognitive methods are basically formal decoding the various alternative procedures that brain may process information. Whatever is created or conceived by any individual the brain has already the mechanism of processing it.

I need more time and reflection to figure out the reverse exogenous marker. This is a first draft to get the project going. I appreciate developed comments and references

Note: This article was not meant to analyze sensations, emotions, or value moral systems. It is very probable that the defined markers are valid for the moral value systems with additional markers that might be needed to store and retrieve data from the special moral system structured . In general, rational thinking retrieve data from specialized databases that are already processed and saved for pragmatic utility. I conjecture that emotions are generated from the vast original database and the endogenous correlation marker is the main computation method: the reason is that emotions are related to complex and almost infinite interactions with people and community and the brain prefers not to consume time and resources on complex computations that involve thousands of variables. Thus, an emotional reaction in the waking period is not necessarily “rational” but quick and dirty resolutions. In the dream sessions emotionally loaded impressions are barely processed because they are hidden deep in the vast original database structure and are not refreshed frequently to be exposed to the waking conscious cognitive processes and thus they flare up within the emotional reaction packages.

Research: How objective and scientific?

Posted by: adonis49 on: July 23, 2009

Human Factors in Engineering (Article #29)

“How objective and scientific are research?”

Friend, allow me just a side explanation on experimentation. Psychologists, sociologists and marketing graduates are trained to apply various experimentation methods and not just cause and effects designs.

There are many statistical packages oriented to provide dimensions and models to the set of data dumped into the experiment, so that a preliminary understanding of the system behavior is comprehended qualitatively.

Every applied science has gone through many qualitative models or schema, using various qualitative methods, before attempting to quantify their models. However, many chairmen of engineering departments, especially those who have no understanding of the discipline of Human Factors or were never exposed to designing experiments, have a conception that this field is mostly qualitative in nature.

They would ask me to concentrate in my courses on the quantitative aspects such as the environmental factors of lighting, noise, heat and any topic that requires computation or has well defined physics equations.

We have 3 concepts in the title: objectivity, scientific and research that are related in people’s mind as connoting the same concept.

However, the opposite meanings for these concepts are hard to come by without philosophical divergences or assumptions.

If we define science as a set of historical paradigms, a set of concepts, truths, facts and methods that most of them keep changing as new technologies and new methodologies enlarge the boundaries of knowledge, then you might be more inclined to discuss notions with a freer mind.

Could subjectivity be accepted as the opposite of objectivity without agreeing on a number of axioms and assumptions that are not tenable in many cases? Any agreement in the meanings of objectivity in scientific research procedures and results are basically consensual among the professionals in a discipline, for a period, until the advent of a new paradigm that changes the meaning or orientation of the previous consensus among the professionals.

Could opinions, personal experiences, recalled facts or events not be accepted in the domain of research even if they could be found in written documents but not thoroughly investigated by a researcher?

So what if you refer to an accredited research article and then it turned out that the article was fraught with errors, misleading facts with borderline results and untenable interpretations? Would the research be thrown in the dust bin as unscientific or non objective and thus not worth further investigations?

Research in Physics, Chemistry and engineering deal with objects and are related to studying the behavior of the physical nature; these kind of research can arrive to well establish mathematical models because the factors are countable, could be well controlled in experimental settings and the variability in errors are connected to the technology of the measuring instruments once the procedure is well defined and established according to experimental standards.

It is when research has to deal with the variability in the human nature such as in psychology, psychometric, sociology, marketing, business management and econometric that the notions of objectivity, research and science become complex and confusing.

The main problem is to boldly discriminate among research and admit that not every research is necessarily scientific or objective and that a research has an intrinsic value if the investigator is candid about the purpose and nature of his research.

We need to admit that every research is subjective in nature because it is the responsibility of the investigator to select his topic, his intentions, his structured theory, references, fund providers, the hypotheses, the design, the methodology, the sample size, the populations, the data collection techniques, the statistical package, emphasis on either error type I or error type II, the interpretation of results and so on.

By admitting prior subjective environment to a research endeavor, we can proffer the qualitative term of objectivity to the research only and only when the investigators provide full rationales to every subjective choices in the research process.

Every step in the research process is a variation on an accepted paradigm at one point in the history of science and the mixing of paradigms with no conscious realization of the mixing process should set a warning alarm on the validity of the research and the many pitfalls it is running through.

Acknowledging the role of subjectivity in the methodology, the data and its interpretation could open the way for more accurate and flexible judgments as to the extent of objectivity and scientific tendencies of the research.

Tags: adonis, adonis49, applied science, cause and effects designs, Designing experiments, engineering, Human Factors, Human Factors in engineering, marketing graduates, paradigm, psychologists, qualitative models, Research: How objective and scientific?, schema, social, statistical packages, system behavior, variability in the human nature, writing

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Posts Tagged ‘Designing experiments’

Soft skills? Broad learning skills: Bye bye STEM skills?

Lou Glazer is President and co-founder of Michigan Future, Inc., a non-partisan, non-profit organization. Michigan Future’s mission is to be a source of new ideas on how Michigan can succeed as a world class community in a knowledge-driven economy. Its work is funded by Michigan foundations.

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Graduate students: Liars, cheaters, and procrastinators

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How causality relation and invariant are perceived by the brain

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Research: How objective and scientific?

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