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An adaptive e-assessment to estimate examinees' ability based on neural network approach.


Azmi Murad, Masrah Azrifah and Kazemi, A. (2013) An adaptive e-assessment to estimate examinees' ability based on neural network approach. In: International Conference on Engineering Education 2013, 22-25 Dec. 2013, Madinah, Kingdom of Saudi Arabia. (pp. 356-361).


The advancements in computer-based assessment provide the technological foundation for e-assessment in measuring students’ learning. The knowledge of a student (also known as an examinee) is measured through exams. A key purpose of using an exam is to determine the proficiency level of each examinee based on his/her responses to the administered test. The main problem of traditional test is that the asked questions did not match the actual ability of examinees and did not measure examinee’s proficiency accurately. Therefore, Computer Adaptive Testing (CAT) has been developed to address this issue. In CAT, each examinee has to answer the questions that are tailored to his/her ability level. It uses models of proficiency estimation such as Item Response Theory (IRT). IRT model relates the response of an examinee to a specific item to his/her ability level and characteristics of the item. However, in IRT model, the relationship between items characteristics and person’s skill are very complex and nonlinear. In this work, we proposed a neural network model to estimate examinees’ ability for small sample size and based on the experiments, we obtained a low mean square error (MSE) compared to IRT model.

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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
Notes: Full text are available at Special Collection Division Office.
Keywords: Computer adaptive testing; E-assessment; Examinee ability; Item response theory; Neural network; Mean square error.
Depositing User: Erni Suraya Abdul Aziz
Date Deposited: 12 Jun 2014 08:05
Last Modified: 25 Jun 2014 02:42
URI: http://psasir.upm.edu.my/id/eprint/26840
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