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Central Agricultural University, College of Post Graduate Studies in Agricultural Sciences, Umiam

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20201
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Subject: Agricultural Extension × Author: Koyu, Bai × Thesis Type: Ph.D ×
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    ThesisItemOpen Access
    Modeling e-learning for climate-smart Horticulture on high value horticultural crops of Arunachal Pradesh: a quasi- experimental approach
    (College of Post Graduate Studies in Agricultural Sciences, CAU-Imphal, Umiam, 2020-07) Koyu, Bai; Singh, Rajkumar Josmee
    Increasing crop productivity in a climate-smart way requires continuous investment in developing human capital in agriculture and allied enterprises, through formal and informal learning and education. Learning derived through newer Information and Communication Technologies (ICTs) devices and formats enables both formal and informal learning and knowledge sharing at any time, place and at any pace. E-learning can provide fresh approaches that are learner-centric, engaging producers and their communities as partners and adult learners in designing and implementing the learning experience. Horticulture, which has been considered as the backbone and future of rural economy for the state of Arunachal Pradesh, is facing the threats of climate change leading to unsustainability of horticultural activities which needs immediate controlling measure. With this susceptible and disperse issues of global climate change, innovation to its adaptation in terms of farmers’ innovations towards Climate-Smart Horticulture (CSH) practices become inexorable for the sustenance of small as well as marginal farmers. CSH is an agrarian tactic that rationally intensifies productivity, adaptation and diminishes greenhouse gases. Keeping into consideration the above essentials, the present study was undergone with the following objectives viz., (1) Develop an e-learning module on Climate-Smart Horticulture on High Value Horticultural Crops; (2) To ascertain the extent of application of e-learning on CSH on High Value Horticultural Crops; and (3) To develop a structural equation modelling on application of e-learning on CSH on High Value Horticultural Crops. Two districts namely, Lower Subansiri and West Kameng were selected purposively; further from each district two Community and Rural Development blocks (CRDB) were selected based upon horticultural importance. Subsequently, two villages were selected from each identified CRDB, thereby, a total of 200 farmers have been finalized for the study. The study developed an asynchronous e-learning module by adapting the steps viz., Analyzing, Design, Development, Implementation and Evaluation using Adobe Captivate software. The research revealed that intervention of e-learning module could enhanced statiscally significant learning Climate-Smart Horticulture on High Value Horticultural Crops (Apple, Kiwi and Large Cardamom by respondents. The study unfolded that highest percentage of the respondents belonged to middle age group having high school level of education. Medium categories were observed in terms of Agricultural Land Holding, Annual Income, Mass Media Exposure, Cosmopoliteness, Knowledge Acquired on CSH and Behavioural Intention to Use (BIU) of the respondents. It could be further reported that it could be reported that there was a high extent of application of e-learning on CSH on High Value Horticultural Crops by respondents through application of e-learning module. On performing SEM, it could be concluded that the endogenous variable PEU had the R2 value of 0.16, indicating the 16% contribution by exogenous variable SE. Similarly, the endogenous variable BIU having R2 value of 0.62 indicated that the exogenous variables viz., PEU, ATT and FC had jointly explained and predicted 62% of accuracy on BIU in ELAM. Likewise, the endogenous variable PU having R2 value of 0.08 had indicated that the 8% of accuracy in estimating PU was contributed by the exogenous variables viz., PEU, SN and FC. Also, ATT with R2 value of 0.01 revealed that the exogenous variable PU had explained 1% of accuracy in estimating ATT. The SE was found to have positive influence on PEU @ p=0.001. The PEU was found to have positive significant influence on BIU @ p=0.01. The PEU was found to have significant negative influence on PU @ p=0.001. The FC was found to have positive significant influence on BIU at p=0.001. The study revealed that E-learning Acceptance Model is an efficient model to be used among farmers in an educational context. Asynchronous e-learning module imparts significant increase in knowledge level of farmers. E-learning Self-Efficacy, Perceived Ease of Use, Facilitating Condition, and are the most important attributes for the e- learning module to have significant influence on Behavioural Intention to Use. The study recommends that traditional extension and advisory services on CSH to farmers should be augmented with e-learning.