| dc.description.abstract | Be cognizant of things that individuals learn,
promotes individual learning and motivation. Acquiring
the skills and concepts based on understanding things
that teachers teach inside the classroom become
important. Gender, age, mindfulness, ability, interest,
anterior knowledge, learning style, motivation, locus of
control, self potency, and phenomenological beliefs
differentiates one learner from another. The
contribution of this research is to enhance the
proficiency of the instructors in preparing the learning
materials by considering the learning style of each
learner which displayed on students’ profile view of the
LMS. Referring to previously written research papers,
resulted in figuring out that most of the methodologies
that are used to detect learning styles are based on
advanced pattern recognition techniques which are
based on huge datasets. This study results that the use
of this inventing feature called fuzzy logic, can reduce
the complexity of learning style selection. Rather than
using complex algorithms to detect learning styles it
works similarly to human reasoning, any user can easily
understand the structure of Fuzzy Logic, it does not need
a large memory, algorithms can be easily described with
fewer data, and easily provides effective solutions to
problems that have high complexity and uncertainty
while be easily modify the rules in the FLS system. Trials
of the learning style selection feature will be tested as
the evaluation process. This refers to the process of
analyzing the survey results from students. A group of
students who knows their learning style via a
psychological session will be selected out of a University
and each student will be evaluated by a test regarding
their learning style as similar to LMS. Results will be
compared and find the probability of the truth of the
learning style selection feature. | en_US |
