2. The role of feedback in language learning

Natural language acquisition and learning does motivate a psychological meaning for feedback competence, defined as the knowledge behavior result to influence further activity (after Webster’s Encyclopedic Dictionary of the English Language, 1989). Knowledge to be understood as insight gained via living experience or book study, the thesis information processing framework is capable of the psychological reference.

As a pursuit of patterns for behavioral validity, acquisition of natural language is learning, where knowledge of result may correspond with returning of output, human individuality yet would motivate a revision on feedback as a return to part own input. Closed-loop capability to become affirmed for all stages of human ontogenetic progression, a term as human feedback strategy shall be proposed.

2.1. Language within a program perspective

Linguistic studies have noted on a tendency to position speech and language within a perspective 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 (…)”

Property by language to “program” behavior would belong with a different scope of inquiry, also as deniable. Feedback to be 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 not sufficient, and natural, generative universals are discerned for unrelated languages. Noam Chomsky has yet stated for the language acquisition device to depend on experience as releaser and further exposure for perfection (Akmajian et al., 1985).

Cognitive linguists insist, mind capacities precede language refinement (ibidem); intellectual progress is contingent on brain biogenetic maturity together with personal intellection, the cognitivist sense for noetic advancement to praise ability to extract from experience and build heuristics. The approach places language learning in context with problem solving.

Both positions imply intrinsic feedback. The present argument selectively does adopt neoconnectionist memory models: 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 specificity increase does enhance neural integrity (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 learning was substantiated by brain reflexes to depend on temporal co-occurrence of events. His approach, often misjudged for an associationist venture (Szewczuk, 1984), was opposed by American connectionists, who insisted on personal recognition of result or response as a competence of intrinsic quality. The laws of learning by Edward Lee Thorndike were those of exercise, readiness, and effect.

Neural schemata are basic biological forms for natural language (Puppel, 1992), and Thorndike laws compare with relevant pattern forming. Respectively, exercise would increase pathway use; effect affirming or denying path validity, neural readiness would encourage rehearsal of connections to have produced agreeable consequents. Literature in psychology has furthered augmented attention to 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 signaling value would target the individual, either to accommodate the inner equilibrium or to threaten it, induced co-occurrence of events and forced response admitted as well. The role of concomitant conditions came to be stressed also by Edwin Ray Guthrie (1935, in Szewczuk, 1984).

Neural learning for language yet observably favors fulfillment where the object of thought is neither plain emotion nor sheer contingency. By standard, recognition between an impulse or mere presence is by and large individual. At neural path formative stages as well, signal objective incidence is unlikely to prevail over favored signaling qualities, especially for fluent language styles, where personal coherence is the predominant motive.

With an undesirable objective or failing at acceptable skill, neural actuation would feed back for affective congruity and desist at disadvantage, but the affective component never is emotion alone. Awareness of purpose and thus orientation towards goal, as necessary already in acquisition of speech sounds, may only come with memory reflection on select qualities of language. Of factors able to influence perception, emotion and experience have been named along with personality (Vander et al., 1985), yet natural standard does not require personality profiling.

Figure 2. A general, closed-loop model for language neural patterning. S — Signal; A — Inner actuation state to embrace affective congruity; S1 — Memory reflection on signal; S2 — Processed signal inner representation; R1 — Response; R2 — Result.

Figure 2 is to connote actual neural connectivity, as concepts on “purely functional” or “mathematical significs” do not build natural, biological systems (Szewczuk, 1984). The necessary generalization is not to commend a simplistic view of human neural links. Human neural network intermediate layers escape monitoring owing to continual, compound, and intricate dynamics. Figure 2 constituent nodes are to symbolize multi-layered structures able to act as generally indicated in Figure 3 (Puppel, 1992).

Figure 2 notes on memory reflection for signal within a general model, whereas there are no memory precedents for novel phenomena. Standard language competence does yet afford verbally to define new percepts, and allows new perspectives for familiar phenomena as well.

Biochemical affinity and specificity may account for encoding processes only in a proportion. Neural relative hyperactivity to ensue with synergisms among existent schemata, is a strong theory on memory path validation (Szewczuk, 1984). The process to rely on intrinsic feedback, it might also account for idiosyncratic memories or even sleep imagery. Figure 4 is to present a generalization for synergistic adjustment as pattern reinforcer.

Figure 4. Memory synergistic reinforcement. S — Signal, R — Response within the neural network, S — Synergistic adjustment (compare Szewczuk, 1984).

Networks are conventional forms in biology, also cytoskeletal or endoplasmic. Humans are potentially unique in relying on individuality effects within network standard function.

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.