MétaCan
Menu
Back to cohort
Record W4307097056 · doi:10.5430/jct.v11n7p31

Encouraging Awareness among Secondary School Students on Air Pollution in Supporting Environmental Protection

2022· article· en· W4307097056 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Curriculum and Teaching · 2022
Typearticle
Languageen
FieldComputer Science
TopicEnvironmental Engineering and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSimple random sampleVulnerability (computing)Sample (material)StatisticMathematics educationTest (biology)Environmental educationEnvironmental pollutionSignificant differenceComputer scienceMedical educationPsychologyGeographyPedagogyMathematicsStatisticsEnvironmental healthEnvironmental protectionMedicineComputer securityPopulation

Abstract

fetched live from OpenAlex

Understanding the vulnerability of our environment and the significance of its protection is known as environmental awareness. Promoting environmental awareness is a simple method to protect the environment and help shape a better future for our generation. The study's aim is to look at secondary school pupils' understanding of the environment. The research used a survey method with multiple-choice questions to examine secondary pupils' environmental awareness. Five secondary schools from Sekolah Menengah Kebangsaan Datuk Sulaiman in Batu Pahat, Johor, were used as a sample for this study. These samples were selected by the researches using simple random sampling technique. There are five questions that students need to answer correctly. The data were collected and analyses using Statistic Package for Science Sciences Software (SPSS V21.0). As a result, it shows a significant difference in frequency and percentage of students gets the correct answer in the post-test. Based on the result its show positive feedback of video-based learning from the students. Hence, education through Information and Communication Technology more effective and interesting than used traditional method.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.183
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.223
Teacher spread0.217 · 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