A conceptual map model for developing intelligent tutoring systems
Computers & Education
Can e-learning replace classroom learning?
Communications of the ACM - New architectures for financial services
A blog-based dynamic learning map
Computers & Education
Dynamic question generation system for web-based testing using particle swarm optimization
Expert Systems with Applications: An International Journal
An adaptive testing system for supporting versatile educational assessment
Computers & Education
Evaluating background and prior knowledge: A case study on engineering graphics learning
Computers & Education
Computational Intelligence in Bioinformatics
Computational Intelligence in Bioinformatics
Automatic leveling system for e-learning examination pool using entropy-based decision tree
ICWL'05 Proceedings of the 4th international conference on Advances in Web-Based Learning
ANTS: agent-based navigational training system
ICWL'05 Proceedings of the 4th international conference on Advances in Web-Based Learning
A test-sheet-generating algorithm for multiple assessment requirements
IEEE Transactions on Education
Computers & Mathematics with Applications
Personlized English reading sequencing based on learning portfolio analysis
Information Sciences: an International Journal
A cloud-based learning environment for developing student reflection abilities
Computers in Human Behavior
Hi-index | 0.00 |
Students learn new instructions well by building on relevant prior knowledge, as it affects how instructors and students interact with the learning materials. Moreover, studies have found that good prior knowledge can enable students to attain better learning motivation, comprehension, and performance. This suggests it is important to assist students in obtaining the relevant prior knowledge, as this can enable them to engage meaningfully with the learning materials. Tests are often used to help instructors assess students' prior knowledge. Nevertheless, conventional testing approaches usually assign only a score to each student, and this may mean that students are unable to realize their own individual weaknesses. To address this problem, instructors can diagnose the test results to provide more detailed information to each student, but this is obviously a time-consuming process. Therefore, this study proposes a testing-based diagnosis system to assist instructors and students in diagnosing and strengthening prior knowledge before new instruction is undertaken. Furthermore, an experiment was conducted to evaluate the effectiveness of the proposed approach in an interdisciplinary course, since several studies have indicated that students learn more and better in such courses when applying relevant prior knowledge to what they are learning. The experimental results show that the developed system is able to effectively diagnose students' prior knowledge and enhance their learning motivation and performance on an interdisciplinary course. In addition, two diagnostic evaluations were also conducted to assess whether the diagnoses given by the system were consistent with the decisions of experts. The results demonstrate that the proposed system can effectively assist instructors and students in diagnosing and strengthening prior knowledge before new instruction is undertaken, since the diagnoses produced by the system were broadly consistent with those of experts.