Security Considerations and Recommendations in Computer-Based Testing

Al-Saleem, Saleh M.; Ullah, Hanif

doi:10.1155/2014/562787

Cited by 33 publications

(21 citation statements)

References 17 publications

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“…Al-Saleem and Ullah [17] mitigated the threat associated with computer-based testing application for online examination. The system is a hybridization of the conventional username/password verification structure with palm-based biometric authentication was implemented.…”

Section: Related Workmentioning

confidence: 99%

“…1) uses passive methods such as CCTV and human invigilators to monitor and detect impersonators during examination by physically moving from one system to the other in an examination hall to confirm the students' faces against their pictures on their respective system dashboard which takes so much time and effort and at the end of the day only very little or nothing is achieved due to the large crowd and the peculiar examination environment; many students still impersonate without being detected. However, this paper seeks to address the problem of examination impersonation associated with the existing online examination platforms, which are on the increase as observed by [6], [17] using machine learning technique. Fig.…”

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confidence: 99%

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An Implementation of K-NN Classification Algorithm for Detecting Impersonators in Online Examination Environment

Izu-Okpara

Nwokonkwo

John-Otumu

2021

J Adv Comp. Commun. Inform. Technol.

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The online examination platforms also known as computer-based testing (CBT) platforms for conducting mass-driven examinations over computer networks to eliminate certain issues such as delay in marking, misplacement of scripts, monitoring, etc., associated with the conventional Pen and Paper Type (PPT) of examination have also been bedeviled with the issue of impersonation commonly associated with the PPT system. The existing online examination platforms rely on passive mechanisms such as the CCTV system and the human invigilators for monitoring the examination halls against cheating and impersonation. The proposed model integrates some level of intelligence into existing online examination prototype by designing and developing an intelligent agent service that could assess students against impersonation threat in an online examination environment using the K-Nearest Neighbor (K-NN) machine learning classification technique considering the level of accuracy and response time in answering the questions. A total of 3,083 dataset was downloaded from an online repository; 80% (2,466) of the dataset was used for training the model, while 20% (617) dataset was used in testing the model to enable the model detect unseen data correctly. Results showed that the developed model has a 99.99% accuracy rate, precision, recall and f-score.

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Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

An Implementation of K-NN Classification Algorithm for Detecting Impersonators in Online Examination Environment

Izu-Okpara

Nwokonkwo

John-Otumu

2021

J Adv Comp. Commun. Inform. Technol.

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“…This may help the organisations to check the authenticity of the examinee by checking his identity using ID card and also ensuring that no cheating is going on during the exam. But due to the enormous advantages of computer-based testing over the traditional paper-and-pencil based testing, most of the organisations are now moving towards CBT, Saleh et al [3].…”

Section: Overview Of Cbt Systemmentioning

confidence: 99%

Computer Based Testing (CBT) System for GST Exams in Adamawa State University, Mubi

Suleiman

Nachandiya

2018

AJRCoS

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The examination is one of the most broadly used strategies for assessing learning and capacity of a student. Adamawa State University is engulfed in a lot of irregularities during examination and also delays of results after the examination. These and another manual method of processing results give room for errors during results compilation. The utilisation of Information and Communication Technology in directing examinations can enhance proficiency and decrease the delay of student's result after examination. A Computer Based Testing System (CBT) was designed and implemented to diminish the delay of student's examination result. The CBTS was designed using the Agile model of the Software Development Life Cycle (SDLC). Implementation was done utilising the open source technologies, like XAMPP server, MySQL, PhP, JavaScript, Cascading Style Sheet and Hypertext Markup Language. The CBT presents notice of student's outcome quickly in the wake of taking the examination, enable the student to retake the exam (where necessary), and furthermore give diverse kinds of questions. The utilisation of CBT system can enhance the productivity and gainfulness of scholarly establishments as it diminishes the cost of stationeries and work associated with conducting examination manually. This by implication can reduce the cost of buying examination materials (papers, printers, turners etc) and students can have their results immediately after the examination. The developed system proved to be efficient and can be enhanced by adding other forms of questions like diagrammatic question to make the test address more diverse areas.

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“…Similarly, the student can cheat via other existing colleague instead of him. To overcome this problem, a continuous monitoring system should be implemented so that it gives opportunity to track and check student during e-exam or e-assessment throughout the exam [14,23].…”

Section: Security Concerns and Issuesmentioning

confidence: 99%

A Novel Authentication Scheme for E-assessments Based on Student Behavior over E-learning Platform

Khlifi

El-Sabagh

2017

Int. J. Emerg. Technol. Learn.

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Abstract-E-Learning and distance education have become common choices for academic institutions. Based on advances in information technology systems, educational institutions have enabled the employment of e-learning systems as teaching courses and evaluation students. However, security issues related to e-learning systems have been raised by e-learning environment stakeholders which including faculty members, and students as well as data. In addition, e-learning opponents argue that incapability of e-learning environment to authenticate examination takers is one of the major challenges. E-assessment is an important element of LMS based e-courses, and student authentication is mostly realized as one of the major concerns for e-assessments. For this reason, the main challenge facing the security of e-assessment and the e-learning environment is how to authenticate students because unauthorized persons can access and manage information. In this work, we propose a novel security scheme that contributes in resolving this vital issue by introducing an efficient secure model for supervising online evaluation including e-assessment or e-exam. The scheme addresses this imperative problem by proposing a novel approach that integrates available databases authentication technologies in conjunction with elearning environments for controlling unethical behavior during e-assessment process. Moreover, the proposed scheme considers the continuous random authentication using students' information stored previously in the databases that guarantee identity and authentication. To validate our proposal, and evaluate its performances and effectiveness, an extensive simulation work is conducted over e-learning platform similar to Desire to learn (D2L).Keywords-e-learning platform; e-learning security; presence and identity authentication; e-assessment and e-exam. 62

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Security Considerations and Recommendations in Computer-Based Testing

Cited by 33 publications

References 17 publications

An Implementation of K-NN Classification Algorithm for Detecting Impersonators in Online Examination Environment

An Implementation of K-NN Classification Algorithm for Detecting Impersonators in Online Examination Environment

Computer Based Testing (CBT) System for GST Exams in Adamawa State University, Mubi

A Novel Authentication Scheme for E-assessments Based on Student Behavior over E-learning Platform

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