Abstract: This research is conducted in order to 1) study the result of applying “Active Learning” in general education subject to develop creativity 2) explore problems and obstacles in applying Active Learning in general education subject to improve the creativity in 1780 undergraduate students who registered this subject in the first semester 2013. The research is implemented by allocating the students into several groups of 10 -15 students and assigning them to design the activities for society under the four main conditions including 1) require no financial resources 2) practical 3) can be attended by every student 4) must be accomplished within 2 weeks. The researcher evaluated the creativity prior and after the study. Ultimately, the problems and obstacles from creating activity are evaluated from the open-ended questions in the questionnaires. The study result states that overall average scores on students’ ability increased significantly in terms of creativity, analytical ability and the synthesis, the complexity of working plan and team working. It can be inferred from the outcome that active learning is one of the most efficient methods in developing creativity in general education.
Abstract: Nowadays there are many methods for representing
knowledge such as semantic network, neural network, and conceptual
graphs. Nonetheless, these methods are not sufficiently efficient
when applied to perform and deduce on knowledge domains about
supporting in general education such as algebra, analysis or plane
geometry. This leads to the introduction of computational network
which is a useful tool for representation knowledge base, especially
for computational knowledge, especially knowledge domain about
general education. However, when dealing with a practical problem,
we often do not immediately find a new solution, but we search
related problems which have been solved before and then proposing
an appropriate solution for the problem. Besides that, when finding
related problems, we have to determine whether the result of them
can be used to solve the practical problem or not. In this paper, the
extension model of computational network has been presented. In this
model, Sample Problems, which are related problems, will be used
like the experience of human about practical problem, simulate the
way of human thinking, and give the good solution for the practical
problem faster and more effectively. This extension model is applied
to construct an automatic system for solving algebraic problems in
middle school.