STRATEGIES OF MEMORIZATION AND THEIR INFLUENCE ON THE LEARNING PROCESS AMONG INDIVIDUALS WITH BORDERLINE INTELLECTUAL FUNCTIONING
Bibliographic record
Abstract
Borderline Intellectual Functioning (BIF), or borderline intelligence, is defined as an intelligence quotient from 1.01 to 2.00 standard deviations below average, that is, a level between average intelligence and intellectual impairment.This level of mental functioning may still belong to a broadly understood norm.The purpose of the present study is to present the current state of knowledge on the subject of memory-related processes in persons with BIF, and in particular schoolchildren.Children with borderline intelligence are at risk for chronic educational failure, absence from school, repetition of grades, and dropout or expulsion from school.We have concentrated primarily on discussing the relationship between me mo ry-related processes and the characteristic thought processes of these individuals, including a preference for operating with concrete material, rigid and insufficiently critical thinking, and difficulties in organizing and generalizing knowledge, all of which cause serious deficits in academic achievement and effective learning.The article begins with an introduction to the problems of borderline intelligence, including the differential diagnosis, classification, and cognitive functioning of these persons.Then, based on the results of national and international research, we discuss the deficits of short-term and working memory that cause difficulties in processing and organizing, impair the effectiveness of long term memory, and thus cause specific learning strategies to be adopted.Pupils with BIF most often master their school knowledge by using rote memory, the functioning of which is discussed at the end of the article.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".