Designing a Web Agricultural Information Quality Evaluation Tool for the Maize Industry
Despite the necessity of ensuring that reliable and recent information for economic development, particularly agriculture, is accessed and shared, the information found on websites related to agricultural topics requires assessment to ensure that only accurate information is shared with stakeholders within the maize industry in Tanzania. A rigorous tool for assessing the quality, accuracy, reproducibility, value, and use of agricultural information on the web is needed to ensure that web agriculture information can be meaningful to users. This study was undertaken to design a tool that can be used to assess the quality of agricultural information on the web.
This study employed an interpretive qualitative case study design. The qualitative data collection involved the design of the Web Agricultural Information Quality Evaluation Tool, in which data was collected through literature analysis and interviews.
Thematic analysis was the main method of data analysis, where a literature review and data from interviews were used to identify themes that may be included in quality information evaluation tools for the maize industry in Tanzania.
The Web Agricultural Information Quality Evaluation Tool has two main parts. Part A is the fundamental information quality criteria, which include authority and timeliness. Part B relates to the relevancy and completeness of the agricultural information on the web.
The findings revealed that authority, timeliness, relevancy, and completeness are the key information quality criteria for assessing the quality of web agricultural information related to the maize industry.
The value of the Web Agricultural Information Quality Evaluation Tool is that it assists stakeholders involved in the agriculture value chain to assess the quality of information available on the web to ensure that timely, trustworthy, and accurate information is used to ensure the sustainability of the maize industry.
The research is based on the first three components of the analysis, design, development, and evaluation framework (ADDIE) model. Further research on the implementation and evaluation is needed to assess the relevance of the tool, specifically related to the maize industry and other agricultural sectors.
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