Exam Hall Research Articles

Using Video Surveillance for Cheating detection in Exam Hall

This review delves into the assessment of video surveillance technology's role in detecting cheating within the context of examination halls. In light of the escalating concerns surrounding academic dishonesty, educational institutions are progressively turning to advanced technological measures to uphold the integrity of their examination procedures. Video surveillance has emerged as a promising tool in this domain, offering a non-intrusive means of monitoring examinees during tests. This critical analysis assesses the effectiveness, advantages, and potential limitations of deploying video surveillance for the purpose of detecting cheating, shedding light on the ramifications for educational institutions and their students. Furthermore, it delves into the ethical and privacy issues associated with this technology and suggests possible avenues for addressing them. By presenting an overview of the current landscape of video surveillance in examination settings, this review intends to provide valuable insights for educators, administrators, and policymakers aiming to fortify the credibility of their assessment procedures.

Theory Exam Conductor and Management System

The Theory Exam Conductor and Management System is a software application designed to streamline the process of conducting theory exams and managing related administrative tasks. It aims to facilitate efficient exam administrative, Exam Co-ordinator, Staff, eliminate manual errors, and enhance overall productivity. The system provides a platform for administrators to create and manage exams, including setting exam schedules, assign exam hall to student, and assigning exam invigilators/staff. It allows for easy generation and distribution of exam hall and hall tickets to students. Students can access the system to check exam hall allotment and enter the PRN No. for downloading hall ticket. During the exam, staff can use the system to monitor and manage the exam process

A Smart Strategy for Prediction of Jahn-teller Distortion in Octahedral Complexes

This article describes the prediction of Jahn-Teller distortion in a smarter way just like a dial number method for electronic configurations d1 to d10 in the case of both high-spin (HS) and low-spin (LS) octahedral complexes of transition metal ions. These short tricks will help undergraduate chemistry students to solve problems associated with the prediction of Jahn-Teller distortion in the competitive examination, as it reduces the time in the exam hall. In addition, a few examples are explained based on smarter tricks for the prediction of Jahn-Teller distortion in octahedral complexes of transition metal ions.

Fingerprint based exam hall authentication

Fingerprint based exam hall authentication

Fingerprint Based Exam Hall Authentication

Abstract: This biometric security system is more accurate than the conventional password-based method and is focused on the needs of humans. Despite being one of the earliest biometric procedures, verification is still the most popular because to its ease of use and consistent accuracy. It is necessary to install fingerprint detection equipment in every exam room, office, and classroom. To signify their attendance in class or during the exam, pupils would have to swipe their finger across the sensor. The database contains the student records so they may be verified. When a pupil swipes their finger across the scanner, an assessment is conducted for them; the gadget scans the fingerprint module's finger patterns and compares the information with the data

Factors Affecting Cheating Behavior at Quetta- Pakistan

Cheating in examinations across the globe is an issue of growing concern. This study argues that the culture of cheating in exams in Balochistan has reduced the efficiency of human resource and has resulted in producing students with high qualifications but less potential in the province. Therefore, it is very importantto explore the factors contributing to cheating in exams and to suggest a course of action to mitigate the menace it poses. A quantitative research method was employed for this study. Similarly, statistical techniques such as correlation and logistic regression were conducted for statistical analysis and explanation of thestudy using SPSS. Theoretically, the study is inspired by rational choice theory. The findings of the study show a significant relationship between personal, institutional, and situational factors. Personal factors that contribute to cheating were found to be students’ desire to excel, low GPA, and slow learning. Institutional factors include the weak administrative role of institutions, poor academic policies, overload on students, and weak performance of the teachers. Situational factors such as the poor management strategy of the examiner, time pressure, and technological tools were found to be instigating students towards cheating. The study suggests that an appropriate exam hall setting, effective monitoring, concept-oriented exams, and a strong honor code can decrease cheating.

Automated Invigilation System Using MediaPipe and Haar Cascade Frontal Algorithm

Exams are the methods adopted by educational institutions to identify student’s knowledge. Students adopt various ways to cheat in exams like answer sheet exchanging, copying etc, students cheat their way into getting good grades. Detection of cheating manually may not be efficient to identify and prevent cheating during examinations. So, to avoid this the process of invigilation is made automatic. Automated invigilation offers the best method for keeping an eye on the kids and spotting instances of malpractice right away. The proposed work has three phases. In the first phase, the exam management does processes like publishing time table, allocating exam hall, allocating hall to staff etc. In the second phase the posture detection of the student present in the exam hall is done using Computer Vision and Media Pipe to detect whether the student has involved in the malpractice. In the third phase, the emotion analysis and face recognition of the student is done using the Haar Cascade Frontal Algorithm. The proposed work also helps to eliminate impersonation in the exam hall.

Malpractice Detection Using Machine Learning

Cheating during exam is unfair behaviour of the students. This becomes disadvantage for other students who do not cheat and work hard to study. This project is meant to detect the suspicious activities of the students who intend to cheat during exams. This project is useful in educational institutions where in invigilators are not able to detect the cheating done by students in the exam hall. This project has two phases namely, training phase and the testing phase. The dataset is a pre-recorded video of students which is captured in real time. This system works well with live web camera input also. The algorithm used is DenseNet121.This system predicts three kinds of activities such as turning around, passing of paper and a normal activity differentiated by RGB colours.

Automatic Exam Hall Allotment

Automatic Exam Hall Allotment

Running an Online Mathematics Examination with STACK

In this paper I discuss running an online examination with STACK for a year 1 "Introduction to Linear Algebra" course. The COVID pandemic has continued to disrupt teaching during 2021-22, and were are still not able to return to the examination hall for a traditional exam. Instead, our examinations were still "take home". Under these circumstances we wrote a fully automatically marked final test for the course. With over 800 students on the course in 2021-22, the paper-based examination was estimated to cost about 50 person-days to mark. Clearly, reducing this cost is an attractive prospect. However, important questions remain. To what extent can we write questions which cover the learning objectives of the course? How did the students do with the test? What recommendations can we offer for similar courses, and future years? In particular, do we need to return to the exam hall?

A Survey on Smart Education and Exam Hall Assistance using Voila Jones Algorithm and IoT

A Survey on Smart Education and Exam Hall Assistance using Voila Jones Algorithm and IoT

Authentication System for Exam Halls Using Face Biometrics by Artificial Intelligence

Authentication has consistently been the biggest difficulty during exams. Verifying candidates' test eligibility is a difficult process that takes time after typical candidate screening. The project's goal is to combat this by preventing impersonation by exploiting the candidate's facial biometric traits, which are recognized by the DCNN algorithm. The Exam Hall Authentication System Using Face Biometric is a cutting-edge solution designed to enhance the security and integrity of examination halls by utilizing facial recognition technology. Traditional methods of verifying the identity of individuals in exam halls, such as ID card checks or manual supervision, can be prone to human errors and fraudulent activities. This system aims to overcome these challenges by leveraging the unique characteristics of an individual's face for authentication purposes. The enrolment stage and the verification of identities phase are the system's two primary parts. Each exam participant's face characteristics are photographed and safely saved in a database throughout the enrolment step. High-resolution cameras are used in this procedure to take several pictures of the participant's face from different perspectives. The positioning of facial characteristics and particular contours of the face are then extracted from these photos via processing and analysis. In the authentication phase, when an individual enters the exam hall, their face is captured by the cameras installed at strategic locations. The captured image is compared with the enrolled images stored in the database. Advanced algorithms are employed to perform a comprehensive analysis of the facial features, ensuring accurate identification and authentication of the individual. If a match is found, the system grants access to the exam hall; otherwise, it denies entry and alerts the invigilators about the potential unauthorized presence. The Exam Hall Authentication System offers several advantages over traditional authentication methods. Firstly, it significantly reduces the risk of impersonation and cheating, as the system is capable of detecting attempts to use fake identities or masks. Secondly, it improves the efficiency and speed of the authentication process, eliminating the need for manual verification and reducing waiting times for exam participants. Thirdly, the system provides a reliable and audit able record of attendance, which can be crucial for ensuring the integrity of the examination process. In conclusion, the Exam Hall Authentication System Using Face Biometric is a robust and secure solution that enhances the security and efficiency of examination halls. By leveraging facial recognition technology, it provides reliable authentication, reduces the risk of fraud, and ensures a fair and transparent examination environment

The Design and Implementation of Online Examination Hall Allocation System for Students in Kaduna Polytechnic, Kaduna

The purpose of examination hall allocation process is to determine the venue of students who are candidates of examination in any given institutions and also be able to give first-hand information about any student who sat for the exam. The aim of the project is to design and implement online examination hall allocation system for students in Kaduna Polytechnic, Kaduna. The new system will be achieved using Structured System Analysis and Design Methodology. The software required to design the new system includes Adobe Dreamweaver, the programming language that will be used comprises of Hypertext Mark-up Language, JavaScript’s, Cascading Style Sheet and Hypertext Preprocessor (PHP), the website will be tested on a local web server “XAMPP” and Structured Query Language is used for the Database design. The project work covered all the necessary details involved in designing the Online exam hall allocation system. The web-based application is aimed at allocating halls only to students and keeping record in a database. The methodology focused on the study area, system design analysis, review of proposed system and architecture of the system. Other method of information generation adopted includes relevant literatures (such as textbooks.) and surfing the Internet, the concerned with presentation of the implementation, the different views of the scheduling on computer system. Therefore, this project if implemented will replace the manual method of exam hall allocation in department of computer science and enhance the process of hall allocation also, would address the problems of the existing system paper based outlined earlier.

Campus Routing Using QR Code

In today’s modernized world, proficiency is at a step forward expecting the man kind to be in advance. This elevation can be seen in various aspects of diversification which majorly include raising number of Smart cities around us. A smart city explains itself as the one, which consists of complex infrastructures, that takes help of communication technologies to increase operational efficiency. Increasing complexity in the infrastructure of institutions, organizations and even malls, make user more reliant on the navigation services. But these navigational services that are in use today are constrained to open areas. So, this Campus Routing using QR code is proposed, to provide better indoor navigation. It describes development of a web-based application that is designed for providing both outdoor and indoor routing to meet the user’s requirement and the same is extended to implement in exam halls for providing route pictures to students of different rooms. There are various solutions exist in the market for indoor navigation using NFC, Bluetooth, Wi-Fi, GPS, but their reliability at every situation is not ideal. Unlike previously proposed solutions this paper chose a different implementation technique by developing a full stack web application that helps in both indoor and outdoor navigation i.e., it involves creating a client interface at frontend and a server at backend. Maps used here are predefined using Auto-Cad tool, stored in database and are retrieved upon user’s request. These route pictures (Maps) can be accessed by the user through the mobile phone using QR code.

Design of Class Routine and Exam Hall Invigilation System based on Genetic Algorithm and Greedy Approach

A classroom routine is nothing more than a well-practiced respond to a teacher's instruction. Most universities handle this allocation process with a manual procedure. The manual procedure gives various challenges and is inclined to mistakes. A better approach to reliably schedule class routine is to utilize a computer assisted web-based system. Therefore, in this work, focus is given on creating automatic class routines with teacher’s requirements. This work mainly consists of two parts, named Admin panel and User panel. In admin panel, we get some information like courses information, teacher’s information, room’s information etc. We can Update, Delete & Add this information. A class routine is then created based on these fields. In user panel, we get all of information about courses, associated teacher and rooms. In this panel we can see all this information & routine. Routine can be constructed by days, teacher’s and semester wise. We create this application by utilizing genetic algorithm, and implemented by using Python language. Exam Hall Invigilation is another aspect which still most universities handle manually. Therefore, an automatic Exam Hall Invigilation Management System is also developed in this work. We propose an improved algorithm to achieve automatic examination arrangement for invigilator based on greedy method. The system can configure to allocate any numbers of invigilators in different examination halls in such a way that each invigilator will get equal number of duties. This algorithm has written and implemented in Java-script language.

Rapid Marking Attendance with Face Recognition

Marking attendance (MA) of students in the classroom and exam halls is not only a burdensome task for the instructors, but it is also time consuming. There is a growing need for efficient and autonomous techniques in AM. This article introduces an attendance system based on face recognition. The developed method detects the students exploiting their faces present in live camera images or in a given image through the Eigen Face Recognizer algorithm. After then, students are recognized and their attendance information recorded in an offline database. HAAR algorithm is used as a classifier in recognition process. In the experimental studies, it has been observed that the face recognition system works with an average accuracy of 79.31% in the real classroom environment. The obtained results showed that the designed system is promising for automatic authentication and marking attendance in classroom and exam sessions. It has been also shown that with the proposed system, marking, authentication and recording works can be completed in a much shorter time and with higher accuracy.

Design and Development of Enhanced Exam Hall Seating Arrangement Automation System

During exam period, it is very hectic task to find out the venue of the examination hall and which seat is allocated to a particular student. Students used to face many problems for finding the exam hall and their seats. Therefore, an exam hall seating arrangement system is needed to computerize the traditional way of preparing the examination hall allotment and generate the hall seating arrangement plan automatically for smooth conduction of exams. The proposed system will guide the students to find out their respective examination hall during their exams. This would also show the respective seat of a student in a particular row of their examination. The other objective of developing this system is to help the students to direct them to their respective examination hall without delays for going on searching for hall plan and their seat allotment. It contains the student, department, subject, staff details, examination hall and their seat allotment. This system will also send the hall number and seat allotted to a particular student through that student’s registered email id. The classifier algorithm is used for efficient generation of seating arrangement and Advanced Encryption System (AES) algorithm is used for password verification of registered users for ensuring high-level security.

Irritable Bowel Syndrome and Me: A Sworn Rivalry.

"Three more hours", I tell myself as I find my way to the exam hall. I see a bunch of my classmates cramming for the last minute, and here I am, in a corner, reminding myself that it's just three more hours till I get away from this horror. Irritable Bowel Syndrome is a gastrointestinal disorder in which there is dull achy lower abdominal pain associated with either diarrhea or constipation. Though it has high prevalence, it is still an underrated disease which can be easily missed in clinical settings.

Categorizing the Students’ Activities for Automated Exam Proctoring Using Proposed Deep L2-GraftNet CNN Network and ASO Based Feature Selection Approach

Exam proctoring is a hectic task i.e., the monitoring of students’ activities becomes difficult for supervisors in the examination rooms. It is a costly approach that requires much labor. Also, it is a difficult task for supervisors to keep an eye on all students at a time. Automatic exam activities recognition is therefore necessitating and a demanding field of research. In this research work, categorization of students’ activities during the exam is performed using a deep learning approach. A new deep CNN architecture with 46 layers is proposed which contains the characteristics of deep AlexNet and SqueezeNet. The model is engineered first with slight modifications in AlexNet. After then, the squeezed branch-like structure of SqueezeNet is grafted/embedded at two locations in the modified AlexNet architecture. The model is named as L2-GraftNet because of dual grafting blocks. The proposed model is first converted to a pre-trained model by performing its training with SoftMax classifier on the CIFAR-100 dataset. Afterwards, the features of the dataset prepared for exam activities categorization are extracted from the above-mentioned pre-trained model. The extracted features are then fed to the atom search optimization (ASO) approach for features optimization. The optimized features are passed to different variants of SVM and KNN classifiers. The best performance results attained are on the Fine KNN classifier with an accuracy of 93.88%. The satisfactory results prove the robustness of the proposed framework. Also, the proposed categorization provides a base for automated exam proctoring without the need for proctors in the exam halls.

Article I. Design of Patch Antenna for Identification of Mal Practicing in Examination

Malpractice is one of the serious issues faced in examination hall. The candidates will be examined thoroughly in the entrance itself. If they are found with possessing the electronic devices, the PGD (Paper Gadget Detector) will detect it. LCD (Liquid Crystal Display) displays the values and an alarm system will be used to give a warning to them. The proposed system is to search the candidates who are carrying the hidden written paper to the exam hall. The searching of hidden written paper can be obtained from Rectangular Microstrip Patch Antenna (RMPA). Here RMPA acts as a sensor which is used to detect the hidden material. This sensor can detect the target based on the permittivity value of each material. The sensors used in this study can be adjusted according to the values of blank paper and also to identify something written in the paper with different densities. The designed antenna has been simulated using Advanced Design System (ADS). The designed antenna (single element and 4 elements) has been compared in terms of various parameters like Gain, Efficiency, Directivity and Radiation Pattern etc.