Authentication of Students and Students’ Work in E-Learning : Report for the Development Bid of Academic Year 2010/11

Global e-learning market is projected to reach $107.3 billion by 2015 according to a new report by The Global Industry Analyst (Analyst 2010). The popularity and growth of the online programmes within the School of Computer Science obviously is in line with this projection. However, also on the rise are students’ dishonesty and cheating in the open and virtual environment of e-learning courses (Shepherd 2008). Institutions offering e-learning programmes are facing the challenges of deterring and detecting these misbehaviours by introducing security mechanisms to the current e-learning platforms. In particular, authenticating that a registered student indeed takes an online assessment, e.g., an exam or a coursework, is essential for the institutions to give the credit to the correct candidate. Authenticating a student is to ensure that a student is indeed who he says he is. Authenticating a student’s work goes one step further to ensure that an authenticated student indeed does the submitted work himself. This report is to investigate and compare current possible techniques and solutions for authenticating distance learning student and/or their work remotely for the elearning programmes. The report also aims to recommend some solutions that fit with UH StudyNet platform.Submitted Versio

Exploring the influence of facial verification software on student academic performance in online learning environments

In spite of the advances in technology in the e-learning field during the last decades, there is still a gap of software and tools that actually improve the assessment of this kind of education by preventing students from cheating when they perform their activities online. Currently, most learning management systems do not offer enough tools or characteristics to check that students are who they assure when they carry out their exercises or online tests. Facial verification software can be considered an interesting tool to answer this need. This facial software helps to verify the identity of the students when they perform their activities, with the intention of confirming whether they are who they claim to be. However, its use could modify the academic results of the students due to psychological factors (e.g. they could feel spied, ashamed or too controlled). The aim of this article is to investigate whether the utilization of facial verification software can modify the academic performance of students in their online activities. In this work, the grades of 70 master students were analyzed and the conclusions pointed out that the academic performance obtained by the students is similar for both groups: those who have used facial authentication and those who did not use it

E-Invigilator: A biometric-based supervision system for e-Assessments

The creation of Virtual Learning Environments (VLEs) have revolutionized the online delivery of learning materials, from traditional lectures slides through to podcasts, blogs and wikis. However, such advances in how we assess such learning have not evolved - with physical attendance at proctored exams still a necessity for formal assessments. This paper presents a novel model to enable remote and electronic invigilation of students during formal assessment. The approach utilizes transparent authentication to provide for a non-intrusive and continuous verification of the candidates identity throughout the examination timeframe. A prototype is developed and a technology evaluation of the platform demonstrates the feasibility of the approach

Portable and Efficient Fingerprint Authentication System Based on a Microcontroller

This paper presents the design of a fingerprint authentication system based on a simple microcontroller and the fingerprint sensor. The circuit diagram and details regarding the procedure are included. The system was programed in MPLAB and then embedded into the microcontroller. Communication between the PIC and sensor is by RS232 protocol. The results show that the system recognizes the fingerprint in less than 1 second. It is portable and there is no need for image processing. Furthermore, the system shows a high effectiveness when storing and verifying fingerprints

A technique for designing glossary activities with facial authentication

Nowadays, one of the key challenges for distance education is to be able to verify the students’ identity in order to check if they are actually who they claim to be when they are doing their online tasks and to avoid identity thief. This can be achieved through facial authentication software. In e-learning, thanks to this technology there is a way to confirm that the students are not committing fraud in their studies and besides to improve this kind of education by equaling its validity and prestige to traditional face-to-face education. The goal of this research is to avoid fake users that perform educational tasks on behalf of others in the Learning Management Systems (LMSs), and more specifically to develop a new technique to design activities with glossaries that properly allow control of the student learning process through facial authentication software. The presented technique is composed of several steps that guide instructors in the elaboration of this kind of activities. This work has used Moodle platform for the experimentation, and analyzes the experience of 67 students with the activities designed with the presented technique

Intelligent solution for automatic online exam monitoring

E-learning has shown significant growth in recent years due to its unavoidable benefits in unexpected situations such as the coronavirus disease 2019 (COVID-19) pandemic. Indeed, online exam is a very important component of an online learning program. It allows higher education institutions to assess student learning outcomes. However, cheating in exams is a widespread phenomenon worldwide, which creates several challenges in terms of integrity, reliability and security of online examinations. In this study, we propose a continuous authentication system for online exam. Our intelligent inference system based on machine learning algorithms and rules, detects continuously any inappropriate behavior in order to limit and prevent fraud. The proposed model includes several modules to enhance security, namely the registration module, the continuous students’ identity verification and control module, the live video stream and the end-to-end sessions recording

The new face of alternative assessment in accounting sciences - technology as an anthropomorphic stakeholder

Worldwide, more and more higher education institutions are making use of online or distance education, due to the increasing demand for tertiary education. In this article, the problem addressed relates to the importance of technology as a stakeholder in alternative assessments for undergraduate accounting sciences modules in an online, non-venue-based, technology-enhanced environment. The purpose of this article is to demonstrate how technology, due to its importance and impact, acts similarly as a human stakeholder and should be treated as an anthropomorphic stakeholder in an online technology-enhanced environment, considering its powerful role. A qualitative approach was followed, and action research was used to develop a conceptual framework. This conceptual framework demonstrates how stakeholder theory could ensure the legitimacy of qualifications through identity verification of students in an online environment through improved performance and innovation potential. These findings contribute to the body of knowledge and due to its importance, technology could be considered as an anthropomorphic stakeholder in the creation, improvement, or restructuring of assessments at online educational institutions

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

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

A proposal to improve the authentication process in m-health environments

Special Section: Mission Critical Public-Safety Communications: Architectures, Enabling Technologies, and Future Applications One of the challenges of mobile health is to provide a way of maintaining privacy in the access to the data. Especially, when using ICT for providing access to health services and information. In these scenarios, it is essential to determine and verify the identity of users to ensure the security of the network. A way of authenticating the identity of each patient, doctor or any stakeholder involved in the process is to use a software application that analyzes the face of them through the cams integrated in their devices. The selection of an appropriate facial authentication software application requires a fair comparison between alternatives through a common database of face images. Users usually carry out authentication with variations in their aspects while accessing to health services. This paper presents both 1) a database of facial images that combines the most common variations that can happen in the participants and 2) an algorithm that establishes different levels of access to the data based on data sensitivity levels and the accuracy of the authentication

Computer-based assessment system for e-learning applied to programming education

Tese de Mestrado Integrado. Engenharia Informática e Computação. Faculdade de Engemharia. Universidade do Porto. 201