Astono, Putri Tansa Trisna
(2024)
Effects Of Machine-learning
Programming Simulator On
Performance, Engagement And
Perceived Motivation Of University
Students In Learning Programming.
PhD thesis, Universiti Sains Malaysia.
Abstract
Since information systems are used to support people in many aspects of their
life, programming is essential. But compared to other nations, Indonesia has a very
low graduation rate for science, technology, engineering, and mathematics (STEM).
The modern environment is making programming abilities more and more necessary
for students. Programming skills are highly valued in many areas, including software
development, banking, healthcare, and even entertainment. Using a quasiexperimental
design, the study set out to design, develop, and examine the effects of
the persuasive multimedia learning application programming simulator on university
students' performance, engagement, and perceived motivation towards the learning
material. The two technologies—Machine Learning Programming Simulator (MLProgramming
Simulator) and Non Machine Learning Programming Simulator
(NoML-Programming Simulator)—were the independent variable in this study.
Students' performance, engagement, and perceived motivation with regard to the
course material were the dependent variables. Students' study streams, which are
divided by students anxiety, served as the moderator variable. In all, the study involved
one university students from the public university in Indonesia. The ANOVA test, a
descriptive and inferential statistical technique, was employed to analyze the study's
data. The study's findings indicate that, in terms of engagement, performance, and
perceived motivation for the subject matter, students who utilized the ML Programming Simulator outperformed those who used the NoML Programming
Simulator. According to this study, university students' performance, engagement, and
perceived motivation toward the course material have all increased as a result of the
programming simulator application in the classroom environment. In addition, the
creation of the ML Programming Simulator for this research helped to expand the pool
of mobile and web applications that enhance the effectiveness of the programming
course classroom.
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