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Record W7065281170

Dificultades de aprendizaje y el rendimiento escolar en la asignatura de ciencias naturales de octavo, noveno y décimos años de educación general básica de la unidad educativa Vicente Anda Aguirre, sección diurna La Dolorosa, durante el año lectivo 2010 - 2011. Propuesta alternativa

2019· article· en· W7065281170 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsNinthGeneral educationBasic educationSubject (documents)Quarter (Canadian coin)Section (typography)Perspective (graphical)School teachers
DOInot available

Abstract

fetched live from OpenAlex

This study was conducted in the Canton Loja capital of the province of Loja, with students of Eighth, Ninth and say years of Basic General Education School "La Dolorosa" during the school year between the first and second quarter the year 2010 to 2011. The research question is: What is the impact of learning difficulties in school performance in the subject of Natural Sciences of the eighth, ninth and tenth years of General Basic Education Educational Unit "Anda Vicente Aguirre" daytime section "La Dolorosa" during the school year 2010- 2011 ?, generating research objective: to analyze how learning disabilities affect academic performance in the subject of Natural Sciences Eighth, Ninth and say years of Basic Education General Education Unit Anda Vicente Aguirre , the Sorrowful section daytime during the school year 2010 - 2011 The research is exploratory and descriptive. For information processing of text, and Deductive Method was used for the collection and analysis of field data, the Inductive Method will be used as a tool for analysis from a particular perspective generalize results. To fulfill the objectives of the observation techniques and the Survey, mainly be used. Research techniques were supported by test, index cards, tokens and field data collection instruments and tabulation. There were three types of surveys: one aimed at students, teachers and parents. The total universe was represented by ninety-two teachers and 1072 students, of which 482 belong to the basic general education, and there are 7 teachers CCNN To calculate the sample 72 students, a percentage that corresponds to 15% of the total universe, which students following results were reached: The techniques of learning most used in the process of learning of NPPs are: reading comprehension, group work and the use of graphic organizers, but the mechanical memory, verbalista type is used and oriented \nlearning concepts rather than processes. Little use of ICT as a form of evidence really supports teaching; and laboratory practices CCNN They are biased. Pedagogical recovery aims to improve the skills and not the skills development with performance criterion, indicating that teachers NPP Recovery processes focus only on improving averages and not the process development and the acquisition of skills with performance criterion. It is recommended to explore the fact that the teaching styles of teachers not engage the learning styles of students, which negatively influences the development of the SAP and channel a study to determine the reasons why not apply ICT in the learning of NPPs

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.253
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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