Integration of Context-Based Learning with Informative Chatbot for Grassroots Farmers

A. Nokkaew, Suparat Chuechote, T. Poonpaiboonpipat, Wanintorn Poonpaiboonpipat
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Abstract

With frustrating environmental changes, many farmers struggle with their productivity and quality of their crops. As they were tempted to use chemicals to their farms, they were required to update their knowledge and skills in order to achieve proper use and safety for their crops, their lands and their lives. This study was a part of a rice farmer training project which aimed to achieve effective training program that could enhance farmers’ knowledge in rice farming when the chemicals were inevitable for some areas. An explorative study was conducted to investigate insight and needs of knowledge of chemical usage. Then the insight was used in designing and developing an active lesson with informative chatbot, so called ‘Smart Farmer’. This chatbot has served as a knowledge-based agent to facilitate the active lesson with Reflect-Connect-Apply context-based approach for the grassroots farmers in Thailand. The in-dept interview and questionnaire were conducted after the context-based lesson. The results show that a considerate design with most to least frequent rankings of chemicals usage and farming troubles should be incorporated in the context of class instructive flow of the training program as well as in the design of chatbot and other instructive materials.
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面向基层农民的情境学习与信息聊天机器人的整合
由于令人沮丧的环境变化,许多农民都在努力提高他们的生产力和作物质量。由于他们被诱使在他们的农场使用化学品,他们被要求更新他们的知识和技能,以实现他们的作物、土地和生命的正确使用和安全。本研究是稻农培训项目的一部分,该项目旨在实现有效的培训计划,以提高农民在某些地区不可避免使用化学品的水稻种植知识。进行了一项探索性研究,以调查化学品使用知识的洞察力和需求。然后,这种见解被用于设计和开发一个具有信息聊天机器人的主动课程,即所谓的“智能农民”。这个聊天机器人作为一个基于知识的代理,为泰国的基层农民提供基于上下文的反思-连接-应用方法的主动课程。在情境课结束后进行深度访谈和问卷调查。结果表明,在培训计划的课堂指导流程以及聊天机器人和其他指导材料的设计中,应考虑将化学品使用和耕作问题的最频繁到最不频繁排序。
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