投资建模用于可扩展的农业学习
Norman Peter Reeves1, Rebecca Pietrelli2, Ian Brooks3
1Sumaq Life LLC, Lansing, Michigan, United States of America.
PloS one
|March 10, 2026
概括
使用数字工具进行可扩展的农业培训在经济上是可行的,即使是少数民族语言. 成功的关键因素包括每位农民的成本,采用率和收入改善.
科学领域:
- 农业扩展 农业扩展
- 信息和通信技术促进发展 (ICTD)
- 经济影响评估 经济影响评估
背景情况:
- 当地化农民培训面临着可扩展性挑战.
- 可扩展的农业学习计划的经济价值未被充分探索.
- 数字技术为改变培训提供提供了机会.
研究的目的:
- 制定一个评估可扩展农业学习经济影响的总体框架.
- 确定影响这些举措回报的关键驱动因素.
- 评估使用多语言动画和YouTube用于农民教育的经济可行性.
主要方法:
- 系统建模用于模拟潜在的经济回报.
- 进行了敏感性分析,以确定影响的关键驱动因素.
- 该研究估计了经济可行性所需的农民数量.
主要成果:
- 经济回报最敏感的是向农民提供信息的成本,采用率和收入增长.
- 通过调整现有内容并延长其使用寿命,可以在更少的农民中实现经济可行性.
- 在这些条件下,对少数民族语言的语言适应在经济上变得可行.
结论:
- 可扩展的农业学习计划可以在经济上是可行的,特别是当使用可适应和持久的数字内容时.
- 系统建模是优先考虑高影响力农业解决方案的有价值工具.
- 将经济模型定制为特定的环境对于准确的影响估计至关重要.
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