An evaluation of level of knowledge, behaviour and attitude towards environmental footprint in secondary school students in Libya
Bibliographic record
Abstract
Abstract The indications of the impact of activities of people on environment are called footprints. Footprints are targeting various concerns related with environment and they quantify resource appropriation or waste generation, or both. Knowledge on protecting environment is one of the important factor that may affect environment adversely, because knowledge determines attitudes and behaviours of someone to environment. This study aimed to assess knowledge, attitudes and behaviours of Libyan secondary schools students towards environmental footprint. A quantitative research employing a questionnaire including questions on demographic characteristics of students and 35 questions on student’s knowledge, attitudes and behaviours of students towards environment was carried out. Data were collected from 400 students in the last quarter of 2018 in four secondary schools located in Tripoli. Data were analysed using Statistical Package for Social Sciences, SPSS vs. 21, employing both descriptive and inferential statistical techniques. Majority of students (91.8%) were observed as having high knowledge on environmental footprint. A higher proportion of students were having moderate levels of attitudes (76.0%) and behaviours (65.8%) towards environment. When the impact of demographic characteristics on level of knowledge, attitudes and behaviours was studied using t-test, it was found that students whose fathers were graduated from master or PhD had significantly greater knowledge level compared to others. It is important to implement programmes for improving knowledge of different parts of population by both empowering school curriculum and involving public and private sectors for involving in policies and programmes for both improving knowledge of different population groups and encouraging them to safe behaviours towards environment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".