Evaluation - Advances in Personalized Web-Based Education - page 96

the appropriateness or necessity of the returns to a domain concept, which was
considered as learner and/or assimilated, in order to revise it. In addition, learners'
performance in a final test was measured and compared for two groups (group A:
the group of students which used the presented programming tutoring system, and
group B: the group of students which used a similar programming tutoring system
with the same organized content, in which the learner chooses if s/he will return
to revise the concept that the system indicates her/him and/or if s/he will read or
not the suggested concept each time). Furthermore, the percentage of times that a
learner needed finally to read a domain concept that the system had advised her/
him not to read was measured.

The questionnaires A, E and F (Appendix B) were given to the students after their
participation in the training program. However, the learners were asked to com-
plete the questionnaires B, C and D (Appendix B), after, almost, 2 years of their
participation in the training program. The reason for that is the fact that the evalu-
ation of the changes on learners' behavior and thoughts and of training program's
results on learners' further studies (which correspond to the evaluation levels of
behavior and results of the Kirkpatrick's model) need at least a two-year evalua-
tion period (Jeremi ´ et al. 2009). Furthermore, the Questionnaires B and C were,
also, given to participants before the use of the systems, in order to compare the
answers before and after their participation in the training program.

4.2.4 The Evaluation Population

For the experiment two groups of students were used. Learners of both groups
were students of a postgraduate conversion course program in the field of infor-
matics at the University of Piraeus. They had different ages, varying from 22 to
50, and backgrounds. Examples of such backgrounds are physics, mathematics,
computer science, education, human and social science. The number of students,
which belong to either each age category or background category, is the same for
both groups (Table 4.1 ). The reason for this is the fact that the homogeneity of the
experiment's samples simplifies the experiment's performing. Furthermore, 40 %
of the learners of the group A had a prior knowledge on computer programming.
The learners of group B that knew already a programming language were 45.74 %.
The distribution of students' knowledge on other languages for both groups is
depicted in Table 4.2 .

Table 4.1 Distribution of students' ages and backgrounds
Ages

22-30 31-40 41-50

68.57 % 22.86 % 8.57 %

Background Arts Science (other than computers) Computer science related

34.29 % 28.57 % 37.14 %