Opportunities and Barriers to the Delivery of Place-based Environmental Education During Emergency and Non-emergency Teaching: An Information and Communication Technology Approach
Bibliographic record
Abstract
Place-based environmental education (PBEE) can enrich environmental education outcomes for youth through direct contact with nature. However, PBEE in K-12 can face barriers, some of which have been exacerbated during emergency teaching protocols, as observed during the COVID-19 pandemic. This research investigates K-12 teachers' perspectives on the potential of leveraging information and communication technology (ICT) to support PBEE during emergency and non-emergency teaching. Survey (n=122) and focus group (n=24) findings identify barriers and opportunities to PBEE before and after emergency protocols and how teachers view the use of ICT in PBEE. There was a negative association between PBEE frequency and grade level taught. The emergency protocols decreased time availability to plan for PBEE due to other work responsibilities. There were more references about potential positive aspects of ICT in PBEE than negative. Nevertheless, teachers emphasized that ICT use should be intentional and limited to allow students to engage thoroughly with the environment.
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 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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".