Development and evaluation of a chemistry educational software for learning organic reactions using qualitative reasoning

Tang, A. and Zain, S. and Abdullah, R. (2010) Development and evaluation of a chemistry educational software for learning organic reactions using qualitative reasoning. International Journal of Education and Information Technologies, 4 (3). pp. 129-138.

[img] PDF
Restricted to Registered users only

Download (971kB) | Request a copy
Official URL:


In science education, it is believed that students should understand the qualitative principles that govern the subject including the cause-effect relationships in processes before they are immersed in complex problem solving. Traditional educational programs for teaching organic chemistry do not usually explain or justify an observed chemical phenomenon. These programs do not explain simply because the results are obtained through chaining the rules or by searching the reaction routes that have been pre-coded in software. This paper discusses the development techniques, simulation results, and student evaluation of a software tool that aimed to help chemistry students learn organic processes through the study of causal theories in a chemical system. Mastering the causal theories of physical phenomena can help students in answering fundamental questions in science education. The simulation technique used is qualitative reasoning that emphasizes the importance of conceptual knowledge and causal theories in education, particularly concerning predicting and reasoning about system behaviour. The results from a preliminary evaluation showed that the tool is effective in terms of its ability to promote students' understanding of organic reactions through the inspection of the explanations generated by the software, where students are seen as the recipients of knowledge delivered via the "explanation" pedagogy.

Item Type: Article
Uncontrolled Keywords: Evaluation, explanation, learning, organic reaction, qualitative reasoning.
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science & Information Technology > Department of Artificial Intelligence
Depositing User: Ms Maisarah Mohd Muksin
Date Deposited: 18 Mar 2013 02:07
Last Modified: 18 Mar 2013 02:07

Actions (login required)

View Item View Item