Visions of Early Childhood Education in the 21ST Century : The Vygotsky`s Sociocultural Theory and Implication to Early Childhood Education : Dynamic assessment for young children
Bibliographic record
Abstract
This study was done to explore the central concepts of Vygotsky`s sociocultural theory. These concepts include the importance of social context, the sociocultural construction of knowledge, the role of language in development, the internalization of higher mental functioning and ZPD (zone of proximal development), and interaction of learning and development. Based on these critical reviews, this study was done also to seek implications applicable to early childhood educational practice dynamic assessment for young children. According to Vygotsky, social context influences learning more than attitudes and beliefs. It has a significant influence on how and what we think. Also, social context plays a central role in development. Like Piaget, Vygotsky believed that children construct their own understandings, and cognitive construction is always socially mediated : it is influenced by present and past social interactions. One of the most important concepts of Vygotsky` theory is ZPD. ZPD is a way of conceptualizing the relationship between learning and development. It is the dynamic zone of sensitivity in which learning and cognitive development occur. The role of education is to provide children with experiences that are in their ZPDs-activities that challenge children but that can be accomplished with sensitive adult guidance. One educational implication was suggested. Vygotsky expressed dissatisfaction with traditional ability and achievement tests as valid measures of children` s $quot;capacity to learn$quot;. In contrast to static assessment procedures, which emphasize previously acquired knowledge in terms of intelligence or achievement scores, dynamic assessment involves purposeful teaching within the testing situation. It attempts to distinguish a child` s apparent level of development, as might be measured by a standardized test, form the child` s potential level of development-the performance the child is capable of attaining with support. The difference between the two is child`s ZPD. To measure the breadth of the zone, dynamic assessment models use a pretesttraining-retest procedure. Feurestein`s, Budoff`s, and Campione and others` dynamic assessment models were reviewed and compared. Other educational implications and critiques of Vygotsky`s approach were also discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".