Development of a Community-Based Non-formal Education Model to Enhance Participation in Upper Wang River Basin Management

Abstract

This research aimed to: 1) to examine the community context and the current state of community participation in the management of the Upper Wang River Basin; and 2) to develop a community-based non-formal education model to enhance community participation in the management of the basin. This study utilized a mixed-methods research design. Data collection instruments included observation forms, in-depth interviews, focus group discussions, a five-step learning process, data recording forms, and model evaluation forms. The population and sample consisted of 80 individuals. Data were analyzed using content analysis synthesized according to the research themes, as well as mean and standard deviation. The research findings are presented in a descriptive format.

The research findings revealed that: 1) The geographical context of the Upper Wang River Basin is characterized by high-slope terrain. Three primary challenges were identified: (a) seasonal water scarcity during the dry season, (b) impacts from flash floods, and (c) redundancies in river basin management. Community participation was prominent in physical activities but lacked substantial decision-making power. 2) The developed model comprises six key components: (a) Principles and Background, (b) Objectives, (c) Learning Content, (d) Learning Process, (e) Learning Resources and Venues, and (f) Model Evaluation. This model utilizes a five-stage Participatory Action Research (PAR) framework, consisting of: (1) Problem Analysis, (2) Corrective Action Analysis, (3) Action Planning, (4) Implementation, and (5) Reflection/Lesson Learned. 3) Expert evaluation results indicated that the developed model is highly valuable and significant, possesses theoretical and methodological soundness, and is practical for local implementation. The model effectively promotes sustainable learning and problem-solving within the river basin, achieving an overall suitability mean score of 4.60 with a standard deviation of 0.35, thereby surpassing the acceptance criteria across all components.