(Abandoned, and cannot update): Analyzing and Comparing the Efficacy of Two Common Learning Methods - Immersion Versus Self-Quizzing.

 Originally published: 09/21/2021

Every now and then, I get quizzed on knowledge base, perceptual acuity , memory tasks of contexts pertaining to occurrences and developments in my life, and of “seemingly” random tidbits of learning, taxonomy, culture, or lore (otherwise), in my remote-sensing environments which happen upon me.

This sort of thing happens on a regular basis. The remote-sensing quorums are attended by various classes and types of individuals, yet commonly, the topic basis is one of a civil complaint against me, and I find myself chronically stressed out, in life, of various sorts of consequences. The pursuit of an ever more leisurely outlook and disposition, in life, is an obvious lure for me, and unfortunately, I find myself deprecating in to former and legacy modes of behaviors, such as seeking novel or imprudent sorts of entertainment online, for example, rather than using my strengths, and building upon gainful and productive aspirations in life. 

 The app I have in mind, in this instance, is a simplistic one, although I would strongly presume that the merits are founded, and sure. 

Why an app? 

Mobile development is an industry that had a significant heyday leading up to the time of the Pandemic, and by all means, it’s an industry that will see growth, to come, as various demographics see a rise and fall in their social and class status underpinnings; I’d suppose that would happen, based on much of the “conjectural” (perceptual?) confessionals and Freudian Slips that I’d been privy to, as we’re all under interrogation by the higher authority, until we become the highest authority, when it comes to a remote sensing tech and lifestyle sort of, uh, lifestyle. 

Within the gold rush timespan, leading up to the era of high-powered mobile device hardware, we saw many shining stars emerge in app development, which fulfilled many of the needed purposes to be seen through in app development in an ever-increasingly more compact, more large if need be; more graphics, higher data throughput and storage capability expectation and demand, on our devices. Activities and pursuits of merit, once confined, largely, to the classroom environment and to libraries, were suitably accommodated and made much more accessible to the layperson of an aspirational creed, who would shrug off the influence of pirating goods (and jailbreaking,, etc.), and go with the program, as far as discovering what was available and being offered through mainstream big tech app stores, offered by Google, Apple, and now Amazon (does Microsoft do an App Store for their mobile devices? I don’t know, off-hand, but I’d assume so). 

The point is,

is that many developers and programmers had staked their worth and product offerings, early on, and they’d established themselves, app-wise, as the go-to solution that people would come to discover, and support, for menial scrum pay - that many App Store offerings were given to people as, with archetypes such as the iTunes Store’s $0.99 offerings of parted-out pieces of what could, would, or had been full albums, previously; many of such apps, themselves, offering a similarly compartmentalized concept of what productivity and development, or “work,” on mobile devices could, and ought be, as it was envisioned and carried out. 

My go-to app, for learning about neural networks, all learning and literature (mostly) aside, came to be Neuronify. Was it free? Did I pay for it? I don’t quite remember, but if it cost anything, it was a couple, or several dollars, or so. It seemed to do the job, as imaginable as it might be, for a dilettante entry in to app-attainment goals, for my arrays, choices, and learning-basis inclusions on to my mobile devices, and for that matter, SSD hard drive space, on an iPad, even more so than on a mobile phone device - it goes a lot further than on a desktop environment (as well as better than phones can offer). I’ve currently (September 2021) got 569 apps, 6020 photos, 346 videos, 168 songs, on my device, which features 256 GB of SSD storage, and I’m only down to about 161 GB remaining. I do anywhere from a 4+ hour to 8-hour screen time daily average, given a week, on my iPad Pro device, particularly now that I’d lost my Google Android Pixel 4a 5G, which is part of a great series of mobile phones, for the cost, by the way. For that matter, the Google Store also features the Neuronify DIY neural networks mapping (doing) app, as well. 

The premise of a neural network is fairly basic, in essence. There aren’t all that many parameters and objects that would be featured in Neuronify, but the significant feature of having development and productivity, on mobile, playing out, at the speed of whatever measure of achievement that could be wrought out of the device and app, through the user’s input, as a moving visual image: interactive, and engaging that it is, playing out on the screen, is part of an attainment, in mobile device development, particularly on the iPad (Pro), which would have formerly only existed in richly-resourced study and research learning and development environments, and tracing even further back, in static image renders, of the calculations involved, and even further than that, in people’s imaginations. At some point, the technology falls back in time, in to philosophical codices, with the basis and need for the science of neurology being a pursuit, study, and investigation of what comprises the mind, itself, and it’s functioning, at the most critical points of investigation and discovery that could be had. What works? What doesn’t? What is the most effective cause and effect cycle and premise? Which types of decisions and behaviors are harmful, or wasteful? These sorts of questions could be proven, to as best the researcher could prove, to the scientific community, whom, in turn, would be capable of producing the same results, in a lab setting, thus validating the discovery. 

Within the app itself, as I’d mentioned earlier, there are only several parameter objects and icon type tools, or actions and feedback mechanisms, in other words, of the interface. The interface, in and of itself, is a node-based class of workflow environment.

The Neuronify app interface, on a 2020 model iPad Pro.

Here, then are the various user interface tools of the app:

Leaky excitatory neuron

Adaptive excitatory neuron

Leaky inhibitory neuron

Adaptive inhibitory neuron

Voltmeter

Spike detector

Firing rate plot

Loudspeaker

DC current source

AC current source

Irregular spike generator

Regular spike generator

Visual input 

Touch activator

Note

My hypotheses:

Premise 1: innovative skills arise out of need, as well as out of rote. 

Some findings and observations, upon that basis:

• Needful skills could only possibly attend to the problem which arises. In this case, I’m choosing productivity as the title of merit. Takin time to discern and decipher, as well as determine that the problem is resolved, and move forth, is hampered by products of neural activity that could rely on lesser or greater electrical pulses, at a more accommodating timing, if the problem at hand were capably handled by a more singular and fluid, unique mind, rather than a mind of more randomness. Electrical efficiency is the requisite object of attainment.
• My preference, for deciphering that engaged and interactive learning, for example, is the superior backdrop to a greater productivity, is that the problems are being resolved in an engaging, real-time environment. Calculations happen quicker through methods gained in using hand-eye coordination types of skill sets - gestural and procedural industriousness, of various other enterprises of life, which pertain to economics, could be translated over in to the argument for an active learning environment basis to a more capable and effective problem-solving style, compared to a “flash card” setting, of completely randomized data sets, this being the cards. 
• The goal of this hypothesis would be to employ certain scientific control environments of my own study, ask individuals for their input, and analyze their statements and claims, as well as their preferences, and discover, within the control environment, whether or not they find similarity, or comparability, in their input received, when calculated against my personal findings. On one hand, it takes a high Intelligence Quotient (IQ) to discern valid mathematical truths about a visual environment, of an insightful nature, yet - I would assert that we, as intelligent and rational creatures, would pursue and develop upon gainful, rational, formal structures, rather than something more founded upon chance, randomness, (even within a finite series of choices), memory - which would alter the resonant section, even, of the brain, itself - a costly transformation; I would say more so, than if the knowledge were understood by an actively engaged mind, of rote discipline, and familiarity, set about in a workflow and industrious setting and environment. 

I’ll pause here, in writing, because I’ve arrived at my destination, of where I’m going, for this part of the day.

Update: 02/09/2023

Hello, I apologize for the abandoned blog article, here - ha ha… a silly way for me to appear, in front of others in the scientific community, but I had abandoned this blog article, due to ongoing challenges in my personal life, which still persist. Aside from that, the app no longer loads on my device; I believe that the app is no longer available for iPadOS, for that matter.