Panel and Open Dialogue: Green Teacher Diploma in Environmental Education
Bibliographic record
Abstract
The purpose of the mini workshop proposed during the PCF4 is to present the CEE-COL experience of developing and launching the Green Teacher Course as well as discuss the process of digitizing the GT course in to an on-line course for use internationally. Participants who are teacher educators or educational administrators concerned about incorporating environment education in the school curriculum will be invited to the mini workshop. Green Teacher is a one-year ‘Diploma in Environmental Education’ for teachers and educators developed and designed by CEE India in partnership with the COL, Canada. Offered through the distance mode, this course is the first of its kind in India. The course is designed with the objective to enable teacher-learners to effectively take up environmental concerns and issues in the classroom, and engage their students in practical, action-oriented Environmental Education (EE) activities and projects. Thus Green teacher is a continuing learning opportunity in EE for practicing teachers. The goal of the Green Teacher curriculum is to empower educators with knowledge, ideas and skills which can help in greening their teachings. Specifically, the four Course Modules aim to enable learners (practicing teachers): To strengthen their understanding of Ecology and provide them with ideas for transacting ecology concepts in interactive ways. To appreciate the complexities of environment-development issues by equipping them with the ability to view a problem from a variety of perspectives and selecting a plausible solution in a given context. To explore the ‘practice’ of communicating the contents in a variety of ways that could enrich and enhance the traditional/tried and tested textbook and chalk and talk methods To explore a range of resources and opportunities available for conducting EE in schools and to enable them acquire an ability to see and make use of opportunities available within the school system—text books, local visits, nature camps, using available media, etc. Given that training in EE has a greater focus on ‘skills the process of curriculum development and design for the Green Teacher distance education programme was a challenging task for the course team. The Green Course attempts at two sets of overall objectives—one dealing with knowledge component, and the other one dealing primarily with skill building for effective transaction of EE.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.049 | 0.015 |
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".