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Record W2587144071 · doi:10.5539/jel.v6n2p196

The Impact of Gender and Reading Level on: Student Perception, Academic Practice, and Student Enjoyment

2017· article· en· W2587144071 on OpenAlexvenueno aff
Chris Sclafani, Dennis Wickes

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMultivariate analysis of variancePerceptionReading (process)Likert scaleGrade levelInclusion (mineral)Scale (ratio)Mathematics educationSocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Much research has been conducted on reading levels of elementary school students. Teachers search for learning experiences that lend inclusion to all genders and levels. How does this all lay out for the students? The initial trial of the study looks into the impact and differences of gender and/or reading level on areas such as school enjoyment, self-perception, and academic practice in the lives of 59, fifth grade, suburban students. A subsequent study was done with identical goals in the following school year as well. This newer study (trial two) included 103 students from grades two through five in the same suburban area school. These students were given surveys that allowed scores to be ascertained in the aforementioned areas of concern. Surveys were given out and scored on a Likert-type scale ranging from 1-5 (1=most negative, 5=most positive). The data was entered into SPSS where various tests such as MANOVA, correlations, Levene’s, and t-tests were performed. While a great deal of the areas were not initially identified as statistically significant in trial one, the area of gender and its relationship with enjoyment did appear to be significant at the p<.05 level. The larger, more recent trial, found gender’s impact on school enjoyment, self-perception, and academic practice time. This study could give educators introspective into the way their students think about school.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.472
Teacher spread0.404 · 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 teacher head, not a consensus.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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