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Perceptions of AR4D Researchers on Documentation of Agricultural Indigenous Knowledge in Uganda

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Abstract

This paper reports preliminary findings from a Doctoral study on Agricultural Indigenous Knowledge (AIK) in Agricultural Research for Development (AR4D) Organizations. AIK is increasingly recognized as an important resource that should be harnessed for agricultural development. However, lack of formal documentation of AIK poses a great risk of its possible extinction. There is also lack of interest in AIK by AR4D researchers [1,2,3] which could be due to negative perceptions. However, no study has explored AR4D researchers’ perceptions of AIK and how they influence their attitude towards AIK documentation. The study therefore examined the relationship between perceptions and AIK documentation among AR4D researchers in AR4D organizations in Uganda. A mixed methods approach with a cross-sectional survey design was employed to collect data across all nine Zonal Agricultural Research and Development Institutes (ZARDIs). The population was 149 from which a sample of 103 was determined based on Krejcie and Morgan (see pg.4). Of the 103 respondents randomly selected to participate in the survey, so far, 78 had filled the online questionnaire giving a response rate of 76%. Of 9 Research Directors purposively selected to participate in face-to-face interviews, 4 had been obtained. Survey data was analyzed using SPSS while interview data content analysis was done. Preliminary results revealed a positive attitude towards AIK among Research Directors while majority AR4D researchers showed less interest in AIK. Correlations between perceptions and AIK documentation were significant implying that perceptions of AIK determine attitude towards AIK documentation.

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Correspondence to Christine Kiconco .

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Kiconco, C., Okello-Obura, C. (2020). Perceptions of AR4D Researchers on Documentation of Agricultural Indigenous Knowledge in Uganda. In: Sundqvist, A., Berget, G., Nolin, J., Skjerdingstad, K. (eds) Sustainable Digital Communities. iConference 2020. Lecture Notes in Computer Science(), vol 12051. Springer, Cham. https://doi.org/10.1007/978-3-030-43687-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-43687-2_6

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