  Learning of advanced physics, requires a combination of empirical, conceptual
and theoretical understanding. Students use a combination of these approaches
to learn new material. Each student has different prior knowledge and will
master new material at a different pace. However, conventional classroom
teaching usually does not accommodate the different learning paces of students.
To both, study and address this issue, we developed an iterative Online
Learning Machine (iOLM), which provides new learning content to each student
based on their individual learning pace and tracks their progress individually.
The iOLM learning module was implemented using server side web software (php)
to supplement the undergraduate course in electromagnetic waves for majors in
physics in their second year. This approach follows the hybrid online learning
model. Students had to complete a section of the course using iOLM, which was
only presented online. The data obtained for this class showed a wide spread of
learning paces, ranging from 0.1 to 0.5, where 1 is the maximum pace allowed by
iOLM and 0 the lowest. The mean was mu=0.25, with a standard deviation of
sigma=0.12. While the pretest showed a positive correlation between the
student's pace and performance, the postest had zero correlation, indicating
that giving more time and content to weaker students allows them to catch up.
