Language natural acquisition and learning would motivate a psychological meaning of feedback as the knowledge of behavior result that modifies further performance (Webster’s Encyclopedic Dictionary of the English Language, 1989). Whereas knowledge of result may correspond with returning of output, the human entity might encourage a revision on feedback as return to part own input. Knowledge can be understood as insight gained via experience or book study; as pursuit of patterns for behavioral validity, natural language acquisition is language learning. Closed-loop capability to become affirmed for all stages of human ontogeny, a feedback strategy may be proposed.
2.1. Language within program perspectives
Linguistic studies have noted on a tendency to position speech and language within perspectives for human “programming” of behavior, own or by another organism. Wiktor Jassem presents an indication by Paul Postal (1987):
“…a language is an infinite set of sentences which are triplets of phonetic, syntactic, and semantic properties generated by a finite abstract project, or grammar, which consists of sets of partially independent elements called rules and a lexicon or dictionary. Such grammars are represented in human neural systems and provide implicit knowledge of the language they define. A grammar is thus in certain ways analogous to a computer program in that it is a formal system partially determining the behaviour of a physical system (…)”
Language to “program” behavior would belong with a different scope of inquiry, also as deniable. Feedback to remain the focus of the present work, two prominent approaches to language development can be quoted.
The nativist party posit that humans are born with DNA-encoded language universals. Nativist tenets emphasize that environmental variables are insufficient, whereas generative universals are discerned for unrelated languages. Noam Chomsky has yet stated for his language acquisition device to depend on experience as releaser, and further exposure for perfection (Akmajian et al., 1985).
Cognitive linguists insist, mind capabilities precede language refinement, yet intellectual progress is contingent on brain maturity (ibidem). The cognitivist sense for noetic advancement praises the human ability to extract from experience and build heuristics. The approach places language learning in context with problem solving.
The present argument selectively does adopt neoconnectionist postulations for human memory: attempts to declare a singular brain locale have been failure without exception. A guideline by Bruce Derwing (in Jassem, 1987) that “no other, special mechanisms or secret abilities are necessary for learning language than learning anything else”, is the principium of the inquiry.
2.2. The closed-loop process of neural network forming
Brain biological maturation alone does not explain language development, though connectivity increase does enhance neural specificity (Vander at al., 1985). Learners may never attain linguistic finesse without favorable exposure to standard spoken and written resources as in libraries and media. Two major orientations toward human learning, behaviorism and connectionism, differ fundamentally.
Ivan Pavlov claimed that brain reflexes depended on temporal co-occurrence of events, and thus circumstanced learning. His approach, often misjudged for an associationist venture (Szewczuk, 1984), was opposed by American connectionists, who insisted on competence, in recognition of result or response. By Edward Lee Thorndike, the laws of learning were those of exercise, readiness, and effect.
The laws compare with relevant neuro-motor pattern forming. Respectively, exercise would increase pathway use; effect affirming or denying validity, neural readiness would encourage rehearsal of paths to have produced agreeable consequents. Literature in psychology has emphasized the neural “labels” for affect, owing to the role in path priority (Goleman, 1997).
Clark Leonard Hull (1940, in Szewczuk, 1984) defined need as a negative balance between the human and his or her setting. Hull’s signaling value would target the individual, either to accommodate the inner equilibrium or to threaten it, allowing for induced co-occurrence of events and forced response as well. Concomitant conditions came to be stressed by Edwin Ray Guthrie (1935, ibidem).
Neural schemata are basic biological forms for natural language (Puppel, 1992), learning yet observably favors objects where thought is neither plain emotion nor sheer contingency. By standard, recognition between an impulse or mere presence is in a language learner individual. Already at neural path formative stages, signal objective incidence is unlikely to prevail over signal favored qualities, especially for language fluent styles, where personal coherence is a predominant motive.
Neural actuation would feed back for affective congruity and desist at disadvantage, yet the affective component never is emotion alone. In acquisition of speech sounds, the person is aware of purpose as select qualities of language. The awareness necessarily involves perception, memory, and consciousness.
Figure 2. Human closed-loop neural patterning for language, a general model. S — Signal; A — Affective congruity; S1 — Signal perception and reference in memory; S2 — Signal inner representation; R1 — Response within schemata; R2 — Result.
Figure 2 is to connote actual neural connections, as “mathematical” or “purely functional” significs are not inherent to biological systems (Szewczuk, 1984). The necessary generalization is not to commend a simplistic view to human neural links. Human neural network intermediate connectivity escapes monitoring, owing to continual, compound, and intricate dynamics; hence the name “hidden layers”. Figure 2 constituent nodes are to symbolize multi-layered structures able to act as indicated in figure 3.
Figure 3. Human neural network multilayered model (Puppel, 1992).
Human biochemical affinity and specificity may account for memory only in a proportion. Neural relative hyperactivity to ensue with synergisms among existent schemata is a strong theory on memory path validation (Szewczuk, 1984). Figure four is a diagram for synergistic adjustment as neural reinforcer, where reference is made to response as of figure two.
Figure 4. Memory synergistic reinforcement. S — Signal, R1 — Response within schemata; S — Synergistic adjustment (cf. Szewczuk, 1984).
Human neural ability allows plural network capability at the same task, as well as singular connectivity adeptness at multiple commitments.
■More:
2.3. Network feedback competence; 2.4. Circular reactions in child development; 2.5. The executive controls theory by Robbie Case; 2.6. Feedback exercise in child language learning; 2.7. The closed-loop behavior of egocentric language; 2.8.The generally feedback pattern in human learning and skill; 2.9. Conclusions.
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