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A New Automated Forms Generation Algorithm for Online Assessment.

Authors :
Albazar, Hussein
Source :
Journal of Information & Knowledge Management; Mar2020, Vol. 19 Issue 1, pN.PAG-N.PAG, 15p, 1 Black and White Photograph, 2 Charts
Publication Year :
2020

Abstract

Modern learning techniques require technologies to be embedded within the process. The assessment strategy of testing students has been developed through the past few decades and have presented online computer-based examination systems as a replacement for the conventional paper-based testing. However, a major challenge that is still faced by those examination systems is that there is no any guarantee that students sitting adjacently will have different questions or forms, and the questions of exams' form are not duplicated for any adjacent students within a lab. In fact, this can influence the reliability pertaining to the online examination systems. Consequently, a new algorithm is proposed in this paper for an online examination system that is capable of effectively generating several exam forms with minimal similarity for the constitutional questions, and that guarantees that two adjacent student's terminals will not have the same forms. Further, the paper provides an explanation for the proposed algorithm and provides a real-life case for the implementation pertaining to the produced algorithm in a conducted experiment. It is found to be proven from the obtained results that the implementation, which is related to the produced form generation algorithm within this research reveals an evidence that is in line with the research assumptions in which an online system's assessment reliability can be improved based on eliminating adjacent locations of a form similarity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02196492
Volume :
19
Issue :
1
Database :
Complementary Index
Journal :
Journal of Information & Knowledge Management
Publication Type :
Academic Journal
Accession number :
143177507
Full Text :
https://doi.org/10.1142/S0219649220400080