Abstract:
The research work in this dissertation seeks to explore how to improve farmers' satisfaction and
adoption of e-leaming. In the dissertation, two research frameworks are developed based on
previous studies for farmers’ e-leaming satisfaction and farmers’ e-learning adoption and outcome.
The frameworks are then evaluated using survey research methodology. Based on 230 useful
responses, the frameworks are evaluated using structural equation modeling and path analysis. The
framework with twelve proposed determinants of farmers’ e-learning satisfaction and a framework
integrated with Technology Acceptance Model (TAM) and DeLone and McLean’s IS success
model (D&M IS) success model with twelve proposed determinants of farmers’-learning adoption
and outcome have been examined. The dissertation provides a number of new insights for both
researchers and practitioners. In particular, the dissertation specifies a practical solution to deal
with the disruptive effects which keeps the use of e-learning away from the farmers. Further, the
research identifies several key factors driving e- learning satisfaction and adoption in agriculture
settings. In theory, this study achieved significant progress towards developing a general
instrument for measuring farmers’ satisfaction with e-learning systems. The validated 12-factor e-
Iearning satisfaction instrument is specified for farmers whereas some factors have not been tested
by previous research. Furthermore, this instrument can be used for testing e-leaming satisfaction
among different target groups similar to the farmers. Further the study investigated how TAM
variables influence e-learning usage behavior and e-learning outcomes. Most of the prior studies
only investigated the adoption and use of e-learning systems. This study develops a framework for
investigating e-learning adoption and e-learning adoption outcomes by integrating e-leaming
adoption determinants, e-learning adoption behaviors, and e-leaming adoption outcomes combined
together. The framework has been developed specifically for e-learning context for farmers and
can be used as the starting point for building research models for investigating e-leaming adoption
and outcomes for users in different professions. The study indicated the alignment of e-leaming
systems with farmers, in the form of fanners’ job performance and fanners’ individual learning
needs, by relying on strengths in their learning performances. This validation will help to facilitate
the design of e-learning for fanners’ self-directed learning in their workplaces. Practically, the
results will help institutions investing in e- learning systems to give knowledge and information
for farmers, and theoretically, the clarification facilitates the further advancement of the TAM and
IS success model.