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Innovations in e-Agricultural Extension Technology (e-AET): diffusion and adoption of agri-expert systems among extension professionals in Kerala

By: Modem Ravikishore.
Contributor(s): Allah Thomas (Guide).
Material type: materialTypeLabelBookPublisher: Vellayani Department of Agricultural Extension, College of Agriculture 2014Description: 166p.Subject(s): Agricultural ExtensionDDC classification: 630.71 Online resources: Click here to access online Dissertation note: MSc Abstract: The present study entitled 'Innovations in e-Agricultural Extension Technology (e-AET): Diffusion and adoption of agri-expert systems among extension professionals in Kerala' was conducted at Thiruvananthapuram district during 2012-2014 covering 100 extension professionals. Expert systems allows the use and application of information technology and communications technology (lCT's) to access and obtain information related to agricultural production, marketing, distribution, and prices, and the results of agricultural research, innovations, to raise the level of agricultural production and benefit the farming community. The present study, therefore, is with the objective to conduct a systematic appraisal of existing expert systems in agriculture vis a vis their diffusion among the extension professionals. The findings demonstrate that most of the extension professionals either in State Department, NGO or University have positive attitudes towards expert system. Age, training, innovativeness, retrievability, relevancy, format clarity, information content, availability, accuracy and timeliness affect extension professionals' attitudes. Based on respondent's stage in the adopter categorisation with reference to expert systems, it was found that 10 per cent of the sampled respondents belonged to innovators category, 19 per cent respondents belonged to early adopters' category, 32 per cent respondents belonged to early majority category, 24 per cent respondents belonged to late majority category and 15 per cent respondents belonged to laggards' category. Effectiveness index of expert system applications was worked out using seven statements and the results showed that pedagogy (as a means to effective learning through expert system) having highest effectiveness index. The findings demonstrate that most of the respondents belonged to middle age category, holding with master degrees; attended training on lCT. It was also found that most of the respondents having high innovativeness and accessibility, forinat clarity and information content of the expert system perceived as high. Availability, retrievability, relevancy, timeliness, accuracy and effectiveness index of expert system perceived as medium by the respondents. Hence, the study undoubtedly exhibited affirmative reaction from all three categories of respondents on the applications of expert systems in the field of agriculture, because local information resource centers are gaining importance with computers carrying expert systems to help fanners to make decisions.
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MSc

The present study entitled 'Innovations in e-Agricultural Extension
Technology (e-AET): Diffusion and adoption of agri-expert systems among
extension professionals in Kerala' was conducted at Thiruvananthapuram district
during 2012-2014 covering 100 extension professionals. Expert systems allows
the use and application of information technology and communications
technology (lCT's) to access and obtain information related to agricultural
production, marketing, distribution, and prices, and the results of agricultural
research, innovations, to raise the level of agricultural production and benefit the
farming community. The present study, therefore, is with the objective to conduct
a systematic appraisal of existing expert systems in agriculture vis a vis their
diffusion among the extension professionals.
The findings demonstrate that most of the extension professionals either in
State Department, NGO or University have positive attitudes towards expert system.
Age, training, innovativeness, retrievability, relevancy, format clarity, information
content, availability, accuracy and timeliness affect extension professionals' attitudes.
Based on respondent's stage in the adopter categorisation with reference to expert
systems, it was found that 10 per cent of the sampled respondents belonged to
innovators category, 19 per cent respondents belonged to early adopters' category, 32
per cent respondents belonged to early majority category, 24 per cent respondents
belonged to late majority category and 15 per cent respondents belonged to laggards'
category. Effectiveness index of expert system applications was worked out using
seven statements and the results showed that pedagogy (as a means to effective
learning through expert system) having highest effectiveness index. The findings
demonstrate that most of the respondents belonged to middle age category, holding
with master degrees; attended training on lCT. It was also found that most of the
respondents having high innovativeness and accessibility, forinat clarity and

information content of the expert system perceived as high. Availability,
retrievability, relevancy, timeliness, accuracy and effectiveness index of expert
system perceived as medium by the respondents.
Hence, the study undoubtedly exhibited affirmative reaction from all three
categories of respondents on the applications of expert systems in the field of
agriculture, because local information resource centers are gaining importance with
computers carrying expert systems to help fanners to make decisions.

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