Informing Sustainability Education in Academic Libraries Through Community Engagement: Evidence From a Rural Green Library in Indonesia
Bibliographic record
Abstract
Objective – This research investigates how a rural community library contributes to sustainability education by generating practice-based evidence promoting environmental literacy that is participatory, culturally grounded, and responsive to local contexts. The study focuses on Perpustakaan Alam Malabar in Mekarsari Village, West Java, Indonesia and examines how the library integrates ecopedagogical strategies to foster ecological awareness within the community. Methods – A qualitative single-case study design was applied. Data were gathered through semi-structured interviews, participant observation, and document analysis and were analyzed using the interactive model developed by Miles, Huberman, and Saldaña. The researchers took part in several community-based programs hosted by the library, such as mobile literacy sessions (melapak), environmental discussions, film screenings, gardening activities, and the annual Rawat Bumi Festival. Data reliability was strengthened through triangulation and member checking. Results – The findings indicate that Perpustakaan Alam Malabar has successfully redefined the library as a participatory learning hub that supports environmental literacy in everyday life. The library’s approach blends scientific insights with local wisdom and community-based action, creating an educational environment that stimulates cognitive, emotional, and behavioural engagement. Nonetheless, the model faces several constraints, including reduced local participation, a lack of institutional policy support, and the growing influence of external stakeholders. To navigate these challenges, the library has implemented adaptive strategies, including training local facilitators, fostering cross-sector partnerships, and promoting culturally responsive communication. Conclusion – The study demonstrates that community libraries—especially in rural settings—can serve as effective platforms for sustainability education. The Perpustakaan Alam Malabar model offers a replicable, evidence informed model that practitioners can adapt to align literacy initiatives with ecological values and local engagement. In addition to its empirical contributions, the study advances a conceptual perspective on libraries as inclusive, transformative, and community-driven spaces for ecological learning and advocacy.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".