Looping Images and Sounds

 

Looping Images and Sounds

Evoke Deep Learning Promise

Rotating Comic Characters

Offer

Deep Learning Practice

 

Current psychological research relates that over-dependence on device/computer screens can lead to short attention spans, with our visual speed crushing our inherent listening capability.  Yet, we still rely heavily on multiple screens for our daily pursuits.

How can we maintain our exposure to the myriad of screen images, with multiple details on split visual fields, and yet use them even further to benefit and escalate us? 

Although our visual memory can dominate with this screen adhesion, our auditory memory (listening) then suffers, out-of- sync.  Unable to integrate auditory, we can only focus on singular image-memory intake. One-item-at-a-time; primarily, visually.

 However, we can remedy this imbalance, and put laborious visual screen intake to our advantage. But, that is, if we agree to undertake the needed effort required; admitting that a better focused, integrated, memory spans has personal value. 

Question:  Why do I need Deep Learning rehearsal looping practice to obtain higher memory spans? I have plenty to do with my screen life as it is, and there are many simple brain games available.

Answer:  Because most jobs now require procedural training with an eye for detail, management acumen. Everyday life demands require fast organizational self-management. Furthermore, our daily life and work productivity could suffer, especially if procedural listening and instructions are required.

 Change needed.

Call in comic characters to the rescue -- inanimate 3D objects become activated

Looping images and sounds can strengthen our minds. Continuous rehearsal segments will affect the frontal brain cortex for improved working memory [1] required to quickly learn procedures. Okay, what will comprise these segments?

 Looping comic characters.

Five specific characters, in a researched and practiced program, entered the rehearsal paradigm stage.  Although they varied in gender, appearance, personality, and temperament, nonetheless, remained non-distracting, timed objects.

But, soon they went to work, becoming free to loop repetively with interplay.[2] Their assignment was mental skill sequencing practice, fundamental to following oral and written directions and procedures.

The looped motion interaction evolves into its own reinforced learning [3] for the participant. Each spoken entity creates a visual and sound unit to reinforce the preceding segment, as Leonardo noted in the early 1500s, Renaissance. [4]

The visual facial patterns become oriented in space-time creating their own local motion/sound/visual energy.[5]

Question. How will these objects create auditory memory integration with Deep Learning features? 
Answer: Through 5^th Dimension counter point, [6] or parallel thought [7]

Question:  What is the 5^th Dimension aspect? Is it strictly an assumption?
Answer:  The 5^th D formulates as a result of combining the first four dimensions that had decades of scientifically documented mechanisms. The three common dimensions now create four and five added complex dimensions into one serial, cumulative, conception.

All five progressive dimensions each had years of scientific, well-documented, authenticated research and practice. [8]

1st Dimension – flat objects

2^nd Dimension – cartoons

3^rd Dimension – cubism, 3-D

4^th Dimension – 4D - quantum sound and image sounds, into higher memory span loops over time and space distances (complex segmented layers in a smooth flow field). [9]

5^th Dimension – 5D - layers of looped thought creates Counterpoint known as parallel thinking[10]. The constant looping span rehearsal formulates Deep Learning practice.

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[1]  Kandel, E. R. (2012). The age of insight. New York: Random House.

[2]  Hofstader, D. (1979). Gödel, Escher, Bach: The eternal golden braid. New York: Basic Books. p. 239.

[3] Wayner. P. (Sept. 5, 2022). What is Reinforcement Learning?  How AI Trains Itself. MetaTech Online Events.

[4] Shlain, L. (1991). Art and physics: Parallel visions in space time, light. New York: William Morrow. p. 433.

[5] Adelman E. H. (August 1991). Mechanisms for Motion Perception.  Optics and Photonics News, pp. 24-30.

[6] Rumelhart, D. E., McClelland, J. and the PDP Research Group. (1986).  Parallel distributed processing:  Explorations in the micro structure of cognition.  Cambridge, MA: MIT Press

[7]  Erland, J. K. Erland, (February 4, 1986; copyright TXu 225 862). Contrapuntal Thinking and Definition of Sweeping Thoughts.

[8] Erland, J. K. (Fall 2000). Brain-Based Longitudinal Study Reveals Subsequent High Academic Achievement Gain for Low-Achieving, Low Cognitive Skills, Fourth Grade Students. Journal of Accelerated Learning and Teaching. 25, (3&4) pp.5-48. ERIC ED # 453-553. & # CS 510 558. https://Books.Google.com/jankuypererland page 41,

[9] Learning Visual Groups from Co-occurrences in Space and Time. (2016). Isola, P., Zoran, D., Krishnan, K., Adelson, E. H., International Conference on Learning Representations, workshop paper. Abstract PDF

[10]  Erland, J. K. (1986), (February 4, 1986; copyright TXu 225 862). Contrapuntal Thinking and Definition of Sweeping Thoughts.

 

Deep Learning Practice Resolves Retention Issues

 This article expands on my recent January “Content Timing Process Realized” and March 2022 blogs on “Deep Learning Applied” findings, to elucidate on how learning retention can be actualized through applied parallel thought (Erland, J. K. February 4, 1986); Rumelhart. D. E. McClelland, J. 1986), and neurological codes, (Hinton, G. 2006). Looping, puppetry dramatization becomes a key deep memory element for re-training career and academic skill retention (Erland, J. K. 1980).

 A highly skilled workforce is a requirement in today’s demanding technological economy. Business and industry now grapple how to create upskilling training that retains and advances eager workers in need of procedural learning. Many have ingrained lack of focus creating erratic behavior and follow-through with written and oral directions that underlie all procedural details.

 Working memory becomes the impetus for activating layered segmented chunks, rotating in spans or units, known as “Deep Learning”, earlier referenced as “Contrapuntal, Sweeping, or Parallel Thinking”© (Erland, Janis L., 1986) in my early writings. This innovative Deep Learning, cognitive process is a vitally needed retention component for up-skilling and re-skilling training. Deep Learning offers a critical component for planning, making coherent decisions, and expressing newly learned skills.

 As a conduit to create the procedural system outcome, are “Deep Learning” practice sessions. Art, science, and computational skills are provided by innovative ventriloquist, prosody speaking, puppets. The participant assumes the role of detecting new patterns and systems.

 The Bridge to Achievement’s (BTA)™ mental agility, a cognitive, span-expansion coding process, has been documented through serial published, juried, award-winning, longitudinal experimental research for academic and career achievement. Outstanding outcomes were documented in math, reading and language skills.

Additionally, the extensive longitudinal data research revealed new mental strength will sustain the enhanced skills over time, when applied consistently. The BTA™ Deep Learning practice becomes a valued supplemental front engine for all reading, math, and language programs, or used independently as a “stand alone, mental jump-starter”. Subsequently, the intense, Deep Learning rehearsal process creates a new, higher functioning, and more optimistic, empowered individual.

 The unique BTA content elements cement learning retention in multiple ways:

 -     Brief, timed, self-paced lessons. Mental focus maintained through ongoing fixed, focal interest.

-     Original, one-of-a-kind, phonetic and coding practice lessons.

      -     Lessons increase gradually in complexity with locked, timing, pacing.

      -     Fourteen to thirty minute short, segmented, daily lessons offer less time involvement.

      -     Whole-brain, peers and puppets, modeling rehearsal regimen (Erland, J. K.  1980).

      -     Authentic, Hollywood Golden Age ventriloquist puppets applied as adjacent role models.

      -     Thirteen choreographed character positions rotate in loops over 800 unique segments.

      -     Solid, verified, data-based published results with multiple 3^rd party reviewers (Erland, J. K. Fall 2000).

_____________________ 

Erland, J. K. (1980). Vicarious modeling using peers and puppets with learning disabled adolescents in following oral directions. The University of Kansas, Lawrence, Kansas.

Erland, Janis L. (February 4, 1986; copyright TXu 225 862). Contrapuntal Thinking and Definition of Sweeping Thoughts.

Erland J. K. (c 1989), Hierarchy of Thinking. Mem-ExSpan, Inc.

Erland, J. K. (Fall, 1998). Cognitive skills and accelerated learning memory training using interactive media improves academic performance in reading and math.  Journal of Accelerative Learning and Teaching,  23, (3 & 4), 3-57.

Erland, J. K. (Fall 2000). Brain-Based Longitudinal Study Reveals Subsequent High Academic Achievement Gain for Low-Achieving, Low Cognitive Skills, Fourth Grade Students. Journal of Accelerated Learning and Teaching. 25, (3&4) pp.5-48. ERIC ED # 453-553. & # CS 510 558. https://Books.Google.com/jankuypererland page 41.

Erland, J. K. (© 2008). Downloadable, unpublished report. Five Generations, 27-years of iterative Brain-Based Accelerative Learning Experimentation Demonstrate Cognitive Skill Improvement Enhances Academic and Career Goals. (https://memspan/jalt).

Hinton, G. (2006). Deep Learning and the recipient of the 2001 Rumelhart Deep Learning Prize.

Rumelhart, D. E., McClelland, J. and the PDP Research Group. (1986).  Parallel distributed processing:  Explorations in the micro structure of cognition. Cambridge, MA: MIT Press.      

 

The New Reality of Personal Development

 

Personalized Development, as we have always known it, is being revamped, morphed, into new online realities. Training departments have ceased to exist as the new reality is online learning. If an internal course requires quick internal learning, a staff member is selected to produce a PowerPoint lesson, quickly, and spend a couple of off hours to present it.

 In the educational world, routine, online, personal development is required by both the state and many school districts. The business world now focuses on re-skill and up-skill learning.  Advanced training becomes the new workforce status requirement, as there is a large shortage of technical workers who can successfully follow procedures quickly and accurately. New information must be imparted, but how? And, if created, will there be enough gained subject matter retention to make training time practical and worthwhile?

 Many companies and schools can not incorporate new learning applications during assigned work hours, as there is already highly scheduled job responsibilities.

 Yet, new online applications must be instilled quickly to create the much needed, proficient workforce. Not to mention that eager course sign-ups following a days’ work, may be hard to come by. Subsequently, an employee must see additional personal benefits for the extra time involvement.

 Some work employees or school teachers can elect to take up-skilling training during personal breaks, if the app fits into the allocated break time framework.

 Okay, how will this much-needed learning practice come about? Several factors must be in place:

 - The applicant must determine long, lasting personal benefits, at low, or no personal cost

-  Enhances job certification

-  Online training must be fast, easy, and in short time blocks

-  No guidebook, manuals, or homework should be necessary

-  Lessons begins with short, easy, steps to gain confidence and momentum

-  Improvement is recognizable to the participant and team members

-  The new process app can be added to existing dashboards

- Recognition that a new app enhances further development, promotional options  and advanced job roles

     And finally, any new product must have a data-backed success rate to ensure the trainee that the process is worth the time involvement spent.

Clinical Deep Learning Practice Applied

 No Magic Bullet or Quick Fix:  

Procedural Learning Objectives

 

Jan Kuyper Erland

 

 Summative Observations of a Data-Driven Framework:

Continuous anecdotal data science applications created some interesting observations. With perplexing longitudinal results with all ages showing gains of various cognitive functioning levels, I began to investigate these differences between individuals and yet, the results had mysteriously maintained not only post years latently through diagnostic follow up assessments, but maintained for decades, as evidenced by continuing circumstantial reports of impressive, continuing high career status.

 Yet, these data phenomena, under certain application-environmental provisions, would be routinely expected.

 Many of the following factors are routinely studied post treatment and verified by cognitive scientists, and should be under continued review at this juncture.

 Clinical anecdotal records revealed the following objectives initially and in subsequent years:

Both performance and mental attitude changed positively for many, not only during the course, but following due, most in all probability, to neuronal rapid, continued flexibility.

Results showed steady growth with all learning levels, but varied among individual subjects.

Results revealed larger growth by treatment groups than a gifted control groups and alternate media activity control groups.

Results were one-two years latent with challenging conditions, and these learners required immediate and semi-annual on-going refreshers.

 Average profiles varied in the outcome results. Some appeared to be suddenly “popped to the very high levels”, while others waxed according to their current brain’s proficiency wiring reflecting daily mental habits.

 As my master thesis indicated; puppets had the same “star” modeling influence power as did peer- team mates.[i]

 Long term memory transfer bridging to critical thought was the most difficult to improve, and required more intense, continuing working memory practice and, with reading and higher order thinking.

Results maintained when eagerly adopted and accepted by the client through the modeling routines.

Peer team models are the important factor for not only overall program acceptance, but for rehearsal spoken timing and pacing.

The deep phonological rehearsal verbal training may have affected the generalization outcomes reported in the research and published higher reading and math scores. [ii]

Intense verbal practice while viewing rotating, timed images and sounds impact working short term sequential memory leading to auditory-visual integration; a requirement for reading comprehension.

Subsequently, the reader must have a fundamental understanding, at the contextual level, for comprehending rigorous texts. To meet the top criteria of the Hierarchy of Thinking Model’s Critical Thought, [iii] this layer must be in place.

 

 

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[i]  Erland, J. K. (1980, October) Vicarious Modeling Using Peers and Puppets with Learning Disabled Adolescents. © 1980. The University of Kansas. Lawrence, Kansas.

[ii]  Erland, J. K. (1999, Fall) Brain-Based Accelerated Learning and Cognitive Skills Training Using Interactive Media Expedites High Academic Achievement. The Journal of Accelrerated Learning and Teaching. 24, 3&4.

[iii]  Erland, Hierarchy of Thinking. Published in 1999 International Alliance of Learning’s monograph. Brain-Based Accelerated Learning and Cognitive Skills Training Using Interactive Media Expedites High Academic Achievement. 24, 3&4. pp.12-14.