Enhancing farmers’ capacity for botanical pesticide innovation through video-mediated learning in Bangladesh
Notice bibliographique
Résumé
AbstractDespite the general success of farmer-capacity-building methods such as Farmer Field School in promoting pest management innovations, only those farmers directly involved benefit. How can agricultural extension enable farmer-to-farmer learning about botanical pesticides beyond such schools? We wanted to know how different learning methods, such as video shows and workshops, change farmers' knowledge, attitudes and practices about botanical pesticides. This paper explains how video engages men and women farmers in spreading botanical pesticides across 12 villages in Bogra District, north-western Bangladesh. We conducted ex ante and ex post surveys among farmers from November 2009 to September 2010. For data analysis, we used t-test and McNemer and Wilcoxon sign rank tests. Our findings suggest that video improves the ability of both male and female farmers to communicate about pest management among themselves and with other stakeholders, as 'intricate ethno-agricultural practices'. Video-mediated learning sessions are more effective than conventional workshop training in enhancing farmers' knowledge about botanical pesticides, changing their attitude and finally taking a decision to adopt these methods. In other words, video is capable of communicating complex issues such as the biological and physical processes that underlie pest management innovations. From our case, we conclude that agricultural extension is more effective with the use of facilitated video learning and that this process clarifies complex agro-ecological principles, bias and normative perceptions of the learners. Also, video-mediated learning is not only transferable across villages, but also works well in combination with other media, such as radio, television and mobile phones.Keywords: botanical pesticidefarmers' learningvideoparticipatory researchlocal innovationBangladesh AcknowledgementsThe authors are grateful to the farmers of Kamarpara who helped develop the video and people from RDA, farmers' organizations and participant farmers for their assistance during the fieldwork of this study. The paper is based on the first author's doctoral work supported by the Austrian Agency for International Cooperation in Education and Research (OeAD). The Social Science and Humanities Research Council of Canada (SSHRC) is also acknowledged for the post-doctoral fellowship which benefitted the author to complete the final draft.Disclosure statementNo potential conflict of interest was reported by the authors.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».