The Role of Semantic Differentials in Learning

Scalable Behavioral Ranges, Scalar Differential Equations

In Behavioral Science, oppositional differentials maps are the norm. The counselor will start with troublesome areas that the patient is experiencing, then map out options from there to provide a better range of freedom, and at scale, a better state of well being. So the question at hand is: can this mapping be used to advance students in more accurate proficiency/competency range(s)?

Historically, simplex to complex scales. So what does that mean? Just as early eras of humans had more simpler, narrower sets, so do individual lifespans. A child starts out with a minimal set of tools, and evolves more complex sets. Imagine 7 humans living in a cave, with bare essentials for survival, and evolve to 7 billion living and surviving~thriving (see: oppositional differential sets above) today. Now imagine that each individual as a range of narrow-to-broad spacetime (narrow~broad 'behavioral range'). Add the heavy lean toward many-to-one education in most public schools, and do the results in this fundamental equation eventually get too narrow? How long can we entrench early development into narrower sets, and expect different results?

The field of #genomics is an evolved stage of genetics. Campaigns like AncestryDNA are revealing inherited competencies as a norm now. The field of #bioinformatics is reaching new heights in disseminating data commutative (overlapping) to genomics. These fields can be integrated with #edtech with more and more accuracy.

Now ask yourself an honest and open question: would I rather have future generations with narrower behavioral ranges, or broader? Can ranges of inherent competencies be evolved with more accurate curriculum, so adult stages have more choice? How can I help integrate this burgeoning field into my system?

Inquiry-based Learning

Open vs. Closed data>info>knowledge>wisdom

Much is made in #edtech over Inquiry-based Learning, discounting Closed System Individualism too often. As usual, there’s a balance/symmetry that should be as fully understood by the mediator, to their fullest capacity/range.

In basic Topology, Open Sets are mediated by Clopen Sets, with Closed Sets completing the differential set. At scale, educational systems have been guilty of leaning toward strict Open or Closed, and rightfully so. But now we’ve passed a point of departure where a full range of learning, at earlier developmental stages, is necessary in order to broaden the following adult stages/sets to handle equally increasing complexity.

Let me place further emphasis, at this point, on “scale” - since there is a broad range of students, around the globe. The sheer volume of differentiation that arises from persistent simplicity sets, vs. complexity sets in more developed countries, should be implied.

Now lets introduce Individual/Subjective vs. Group/Objective differential sets. As a teacher, ideally, an educational system has prior evaluation data for each student, so the teacher/mediator can plan individual and group pairings on an ideal 25 student set. If a student has more Closed, Individual learning tendencies, then mediating that student amongst a balanced/symmetrical set of 5, is the ideal peak-performance set. Curriculum should equally scale to the prior and projected evaluation sets, so consistency can have more efficient, post-graduation integrative-value at the next level. Likewise, #edtech software should be consistently integrating this process, otherwise systemic entropy eventually collapses the set, and the fallout can be immensely difficult to recover from.

So is the educational system you’re involved with implementing these basic techniques? If it’s too inconsistent, asynchronous, and asymmetrical, is there someone that can take the lead that you can work with to integrate this upward scaling?