Ethnobotany as Development Pedagogy: Integrating Indigenous Plant Knowledge into Transdisciplinary Education
Bibliographic record
Abstract
In the present context, ethnobotany is considered a development pedagogy by examining how Indigenous plant knowledge can be integrated into transdisciplinary education to promote sustainable development, cultural continuity, and community empowerment. Ethnobotany, as the study of relationships between people and plants, offers a dynamic framework that bridges natural sciences, social sciences, health studies, environmental education, and cultural studies. Positioning ethnobotany within a development-oriented pedagogical approach enables education systems to move beyond disciplinary silos and incorporate locally grounded knowledge systems into formal curricula. The study argues that Indigenous plant knowledge-encompassing medicinal uses, agricultural practices, ecological conservation strategies, and spiritual meanings-constitutes a valuable epistemological resource for addressing contemporary global challenges such as biodiversity loss, climate change, food insecurity, and public health. Integrating this knowledge into transdisciplinary education fosters experiential learning, place-based pedagogy, and community participation, while validating Indigenous epistemologies often marginalized in mainstream education. A critical and participatory framework, the paper highlights how ethnobotanical learning enhances ecological literacy, intercultural dialogue and awareness of sustainable livelihoods. It further emphasizes the ethical dimensions of knowledge integration, including intellectual property rights, community consent, and equitable benefit-sharing. By re-conceptualising ethnobotany as a developmental pedagogy, the study proposes an educational model that supports resilience, sustainability, and inclusive knowledge production. The present study was conducted in the Mouli Para village of Birbhum District, West Bengal. The indigenous people, the Mahali, inhabited the said village, and their knowledge of indigenous plants encourages educational upliftment for first-generation learners, while ethnobotany serves as a developmental pedagogy. Ultimately, the integration of Indigenous plant knowledge into trans-disciplinary education not only enriches academic inquiry but also contributes to socially responsive and culturally rooted development pathways.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".