Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia

Research Article

Development of Mobile Learning Framework for Vegetable Farming in Indonesia

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  • @INPROCEEDINGS{10.4108/eai.12-10-2019.2296503,
        author={Erlangga  Erlangga},
        title={Development of Mobile Learning Framework for Vegetable Farming in Indonesia},
        proceedings={Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia},
        publisher={EAI},
        proceedings_a={MSCEIS},
        year={2020},
        month={7},
        keywords={mobile learning mobile learning framework mobile learning agriculture design science research methodology (dsrm) instructional systems design (isd) addie (analysis design development implementation evaluation)},
        doi={10.4108/eai.12-10-2019.2296503}
    }
    
  • Erlangga Erlangga
    Year: 2020
    Development of Mobile Learning Framework for Vegetable Farming in Indonesia
    MSCEIS
    EAI
    DOI: 10.4108/eai.12-10-2019.2296503
Erlangga Erlangga1,*
  • 1: Department Computer Science Education – Faculty of Mathematical, Science, and Education Universitas Pendidikan Indonesia Indonesia
*Contact email: erlangga@upi.edu

Abstract

Farmers face many problems related to seeds, pest and disease control, commodity prices, and marketing of produces. With the better penetration of the Internet to the villages and the wide availability of inexpensive mobile devices, mobile learning provides a good solution. This study is aimed to create a mobile learning framework that provides information and interactive communication about vegetable production. The method used was the Science Research Design Methodology (DSRM) with a framework approach to the instructional design of ADDIE (Analysis, Design, Development, Implementation, and Evaluation). Usability surveys of the proposed prototype to farmers, extension agents (field technical assistants), and researchers result in 79.4%, 87.3%, and 87% satisfaction rates, respectively, in information needs fulfillment. Based on the assessment by experts, 87.3% of them agreed that the mobile learning framework for vegetable farming could provide learning information about vegetable production.