Applying Adaptive Collaborative Management for Social Learning

Publication Information
Title: 
Applying Adaptive Collaborative Management for Social Learning: A Case Study of Community Forestry in Nepal
Authors: 
Chiranjeewee Khadka
Authors: 
Harald Vacik
Pages: 
8
Publisher: 
I-KNOW and I-MEDIA
Synopsis: 

This contribution promotes the application of an adaptive collaborative management (ACM) approach for social learning in the context of Nepal's community forestry program. We highlight the principles of the ACM process, the problems, potentials and limitations of the approach especially to demonstrate social and collaborative learning for sustainable community forest management. Researchers and local facilitators were involved in a deliberative planning process and community forest users groups developed a common understanding of how to apply the ACM approach. In a joint learning process the users tested assumptions built upon their experiences and knowledge which allowed them to achieve the goals of the local community in a sustainable manner. Evidence of the combined application of the ACM process and social learning are presented from six case studies on community forestry in Nepal using a broader range of the knowledge management activities. Community forest management provides a participatory environment to achieve conservation and poverty reduction. In particular, the current status, challenges, and opportunities for future improvement as seen from the perspective of social learning are highlighted. Conclusions and policy suggestions are made as contribution for the development of a common understanding in which an ACM approach can be practiced to transform a knowledge management organization towards a learning environment.

Citation: 

Khadka C., Vacik H. (2008): Applying Adaptive collaborative management for social learning: A case study of community forestry in Nepal. In: Maurer et al. [Eds.], Proceedings of I-Know 08 and I-Media 08 - International Conferences on Knowledge Management and New Media Technology, Journal of Universal Computer Science (J.UCS), p. 101 - 108; ISSN 0948-6968

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