ABSTRACT
The college entrance examination is vital for program admission. Typically, entrance examinations are conducted onsite using paper and pens. When the COVID-19 pandemic hit, the entrance examination was lifted and physical gatherings were prohibited. Since many schools cannot offer an online admissions exam, they rely on grades and interviews to admit and qualify students for degree programs. However, academic standards differ between schools, and grades may not be enough to assess students' capacity. Thus, this study aims to develop an Online Proctored Entrance Examination System (OPEES) with Degree Program Recommender for colleges and universities to help institutions administer onsite or online entrance tests and generate course suggestions using a rulebased algorithm. The study employed the scrum methodology in software development. OPEES allows applicants to submit applications online, and institutions can manage user accounts, tailor exams and degree programs' criteria, manage exam dates, and assign proctors. Online proctoring using Jitsi, an opensource multiplatform voice, video, and instant messaging tool with end-to-end encryption, ensures exam integrity. The system's features were evaluated by 102 respondents, comprised of end-users (students and school personnel) and IT professionals, using the FURPS (Functionality, Usability, Reliability, Performance, and Supportability) software quality model. In the software evaluation, the overall system proved to be functional as perceived by the respondents, as manifested by the mean rating of 4.61. In conclusion, the system's architecture was deemed feasible and offers a better way to streamline admission examinations and determine a student's applicable degree program by enabling institutions to customize their exams and degree program requirements. It will be beneficial to look into recommendation system algorithms and historical enrollment data to improve the system's use case. © 2022 IEEE.
ABSTRACT
The requirement for remote examination had emerged along with remote learning during the COVID-19 pandemic as the unprecedented situation had brought the world to halt. The pandemic had forced many educational institutions to move towards the online mode of assessment to assess the caliber of the students. This paper focuses on the ways that an online examination system can be prepared and can be used for conducting exams remotely in a secure way. It also emphasizes on various test cases that are essential for an efficient and useful examination system that can benefit both students and faculty by saving them time and effort. Due to the challenges in the existing mode of online assessment such as the use of digital forms that are usually used for conducting surveys, scanning and uploading answer sheets using phone with poor camera quality, the problem of engaging in the different kinds of misconduct, it was important to understand the user requirements at an examiner and examinee level and prepare a web application that addresses them and makes it convenient to conduct and attempt. We propose different methodologies that can be implemented in a Python based web application with the help of JavaScript such as switching the browser window to full-screen in order to restrict access to other applications, limited exits from full-screen, easy management of examiner and candidate data along with visualization of exam data that help to better understand and draw quick conclusions at the time of exam. It is also focused on the continuously evolving distance education system and finding the best software solution possible for online examinations. Additionally, an automated grading system may help to reduce human error and declare results easily reducing fatigue. © 2022 IEEE.
ABSTRACT
An examination is an essential aspect of learning. The traditional method of examination is when the exam taker takes an assessment in a room or a huge space with other candidates while being supervised by the exam monitor. Although the term 'Online Examination' has existed for a while, however, it has been taking off recently due to the global nation closing as a precautionary measure to prevent the spreading of the Covid-19 virus. Many institutions have their way of conducting online examinations, which prompt many responses from the exam takers. While it is undeniable that online examination could increase efficiency in conducting an examination, multiple factors could influence the success of conducting a smooth online examination. Hence, this paper will study exam taker's sentiments towards online examinations based on the current online exam implementation in their institutions. A questionnaire survey was conducted throughout 67 exam takers above the age of 18, where their responses are gathered and analyzed in identifying their concerns and obstacles when taking an online examination. The results would be helpful for institutions to formulate a method for creating an online examination method that would be both efficient and convenient for both students, lecturers, and staff of the institution. © 2022 IEEE.
ABSTRACT
COVID pandemic has brought many changes in day to day working of almost every profession. Education is one such arena where switching to online mode of teaching and assessment was received by many educators as a paradigm shift in pedagogy. Conducting classes online was not a satisfying experience for many but was recognized as the need of the hour. But when it came to online assessment of work, the bright window of light generated an array of questions. Conducting online assessments using live online proctored test, or submissions of assessment sheets has become a new-normal. Many technology platforms provide solutions for online face-to-face meetings, Artificial intelligence based proctored examinations and online objective type assessment sheets with pre-assigned rubrics for marks and evaluation. Since there was a situation where the proctor needs to be present and observe the behaviour of the student, their movements and also the application is to check the face to be recognised with the data already entered, if there is any noise or if someone else if present in the room or not.All these features had made the online examination system little efficient and effective for the universities to conduct the exam hassle free and from remote access. This paper presents a study of various online assessment tools presented by technology companies for smooth conduct of examinations. This study also presents a comparative analysis of features of these tools and their utilization in different domains. © 2022 IEEE.
ABSTRACT
This paper reports a case study of creating a prediction model of English placement test scores for proficiency-based English language classes for incoming first-year students. Since the English placement test could not be administered in FY2020 due to the COVID-19 pandemic, we used data from the past five years to create a random forest regression model was created using data from the past five years. Since the variables that could be used were limited to fixed information at the time of admission, the number of variables was minor, such as the type of entrance examination and high school types. Although the performance metrics of the model were not perfect, it was judged to be practical for using the prediction results, namely, class placement. In the following year, 2021, the English placement test could be administered, so the prediction model created in 2020 was used to verify the prediction results and actual performance. As a result, it was confirmed that the performance evaluation index tended to decrease. However, the performance was judged to be within the practical range, and the generalization performance of the forecasting model was confirmed. In addition, when the importance of the variables used in the prediction model was checked, the importance of the recommended entrance examination system was high. This suggests that the difference in English proficiency at the time of entrance is mainly due to the entrance examination system and the future that devise a countermeasure is necessary such as remedial education. © 2021 IEEE.
ABSTRACT
In recent years with the rising popularity of MOOCs and due to the coronavirus outbreak, the need and demand of online examination solutions has increased tremendously. Online examination posed various challenges of security and fairness. Despite a wide range of research, there exist multiple loopholes in the existing implementation for online based examination systems. This paper aims to implement a reliable mobile based at-home examination system utilising deep learning for cheating detection via object detection models. This paper aims to implement a bluetooth camera device that captures full body images and sends them over HTTPS for cheating detection. © 2022 IEEE.
ABSTRACT
Online methods such as e-learning, e-business, online shopping, online payment, and so on have gained in popularity around the world as a result of the COVID 19 pandemic. Education sectors use emergency tele-learning, online learning platforms to persist in this circumstance and exams are conducted as online exams. This research highly focused on visually impaired students who are unable to read the questions displayed on the computer screen in this online examination system. They missed their braille system which is more familiar to read and write more easily. This is high time to build a proper voice-based online examination system for visually impaired students. This system should read the question that is displayed on the screen and obtain the student's response via voice commands. It can only lead students through the online exam using voice, and students can only provide the system answers and navigation orders using voice. The proposed system major goals are to read questions to students, obtain answers from them and effectively navigate students through the system using voice instructions. It builds a comfortable environment for the visually impaired students to write the exam and it helps to improve their personality when they are facing the exam. © 2022 IEEE.
ABSTRACT
The covid-19 global pandemic brought about a drastic change to how the world approaches education. The world bank noted that at the peak of the pandemic, 45 countries in Europe and Asia closed schools. A separate source also noted that over 250 million primary and secondary school children were out of school due to the lockdown of schools worldwide. Albeit temporarily, the severity of the pandemic transitioned the method of teaching for most schools from physical to virtual. This paper aims to address one of the limitations that arose due to this transition: online examination security. Examination malpractice was noticed to spike for examinations taken online, even with trained proctors watching test-takers via video conference platforms such as Zoom or Microsoft Teams. Within this research analysis is a planned iris movement tracking system to add another layer of security to online examination systems. This system uses a three-tier style structure. Tier 1 is verification that it is indeed a registered student taking the examination. This will be achieved using facial recognition. Tier 2 involves the storage and protection of facial data of students. The last tier involves the continuous use of webcams to detect the iris movement of students and alert proctors if a student looks away from the screen for a significant amount of time. This paper mainly focuses on tier 3. © 2021 IEEE.