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This paper details the most recent developments that were performed in the online platform BeA (Blended e-Assessment) in order to increase its usefulness and utility within the new prominent learning contexts that appeared in the year 2020 as a consequence of the COVID-19 pandemic. Due to safety recommendations such as social distancing, in-person exams need to be performed under strict restrictions, and remote exams have increased in popularity as a way to evaluate students without them leaving their home. The new BeA features allow students to directly upload pictures of their answers to the platform, circumventing the need for the exams to be scanned by the teacher. This both minimizes physical contact during in-person exams and allows students to submit their answers from home in remote exams. These new features were tested during remote exams in the 2019/2020 academic year, garnering an overall positive reception by students.

We compared two E-assessment platforms and we evaluated the impact of online versus on-site examination by analysing students’ outcomes and classifying them into performance groups. Two groups of 480 (G1/2019) and 527 (G2/2020) 2nd year medical students were included. G1 was assessed by using E-School Exam Module on-site, while G2 used FlexiQuiz assessment platform online. G2 received 3 partial examinations during the semester while G1 was evaluated by o single final exam at the end of the semester. Students were classified in four performance categories as high (8-10, HPG), medium (6-7.99, MPG), low (5-5.99, LPG) and fail (less than 4, FPG) based on final grade. The analysis was applied for both theoretical and practical exams. A significant increase of HPG (79% vs 4% for theory and 42% vs 16% for practice) was noted for G2 compared with G1. MPG remained relatively the same between groups while LPG decreased for G2 compared with G1 (22% vs 1% for theory, 25% vs 4% for practice). The G2-FPG significantly decreased but remained higher for practical exam. HGP, LPG, FPG were strongly influenced by applying different assessment methods while MPG remained similar for G1 and G2. Factors influencing these variations will be discussed here.

Electronic examinations provide numerous advantages over traditional examination carried out on paper, such as more streamlined logistic and savings of cost, manpower and time. However, when solving examination problems in the field of engineering, the use of pencil and paper is frequently preferred to using the most common computer input devices, the mouse and the keyboard. The traditional paper approach offers the students flexibility in expressing their thoughts in a free form, experimenting and visualizing their approaches while working out their solutions. The focus of this work, which is in progress, is to modify and adapt certain aspects of traditional engineering exam problems to make them more suitable for electronic examinations. This allows the students to continue use the traditional tools of pencil and paper, but the electronic exam will extract the information needed for automatic grading, combining the best of both methods.

Outcome Based Assessment (OBA) is one of the recent educational phenomenon that is being increased use especially in high education. This approach applied to improve the learning, increase student mobility and achieve lifelong learning either in traditional learning or in e-learning systems. This study will describe the effectiveness and efficiency of the various outcome based assessment models and will conduct a detailed and comparative analysis of them from different criteria to identify the strengths and limitations of every model. Different factors and criteria will be discussed to evaluate and compare between existing models.

Recently, Problem-based learning has been increasingly used, and with those practices, self and peer evaluation tasks have gained more importance. This method of learning assists learners in the acquisition of skills and competencies. In order to support self and peer evaluation tasks, there are some different software offers in the market. The ease use of them is demanded since these tasks are an important part of evaluation. With the literature emphasis on the importance of assessment and critical spirit, it arises the possibility to implement formulas to increase the efficiency on the methodology applied and satisfaction of students and teachers. This paper introduces formulation problems about marks weighting in self and peer evaluation. It presents the advantages and disadvantages of different solutions for the formulation and suggestions of adapting them among tools, feedback surveys, and teacher’s methods of evaluation. It is also expected that the formulation, which was implemented in the software tool WEBAVALIA, has a great impact on feedback, improving user experience, and both efficiency and flexibility.

Assessment is an important component of teaching and learning as lecturers are able to gauge through assessments whether learning has taken place. Higher Education Institutions (HEIs) are striving to implement Electronic Assessment (e-assessment) as an alternative to the traditional assessment method, which is pen and paper, however, e-assessments have many advantages as well as challenges. This paper investigated the experiences of a group of strategic tutors responsible for administering the e-assessment tool to assess the contents of the End User Computing (EUC) module at the University of Johannesburg (UJ). A short questionnaire was employed to collect the data. Data was analysed manually because of the small number of respondents. The results of the investigation highlighted the various challenges experienced with this particular e-assessment tool.

The e-assessment is a crucial process that allows to validate the previous state of knowledge acquired by the student, as well as to monitor his/her progress and/or validate the level of knowledge obtained by him/her at the end of the learning process. The aim of this paper is to propose a fuzzy inference model for determining the difficulty level of e-assessment questions within adaptive instructional systems, thus allowing to integrate and analyze key features of the questions properly matching with the student's cognitive profile for an appropriate question selection. In order to validate the model a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of the proposed fuzzy inference model for adaptive e-assessment instructional systems.

Despite the intensive dissemination of remote learning, it is surrounded by dangerous problems related to much lower completion and retention rates and higher dropout level in comparison with the full-time form of study. This research inspects the reasons for failures and dissatisfaction and their connection with e-assessment. The steps are offered aiming to improve knowledge delivery and acquisition for the disciplines conducted in the remote learning manner. Four main sides of e-assessment are discussed throughout the paper: general setup, assessment content preparation, conduction of evaluation, and grading. The prototype of the new educational arrangement has been piloted with students enrolled in remote education. Results are compared with the full-time study in Department of Power Electrical Engineering and Mechatronics of Tallinn University of Technology.

Although a variety of e-assessment systems has been developed during the last fifteen years, yet most of them lack several desirable features which facilitate the process. In this paper the development of an online platform for the e-assessment of higher education courses is presented. The proposed system enables instructors to automatically generate tests using pre-written questions stored in a Database, as well as, automatically grade the tests right after submission. Some additional features include the support of a question types variety, test scheduling scheduling and a timer.

Assessment can be defined as the interpretation of a student’s work performed. It can be the guiding as well as decision making point for various stakeholders. It checks the learner on three pillars as to how student represent knowledge, how to develop competence and how to draw influence from the topic. Assessment is the best way to identify what the student wants as in support to increase his/her knowledge base. It encourages the desire in the learner to excel in various fields and progress further. Assessment is sometimes mistaken as evaluation but they are different in many perspective such as: Assessment is to evaluate the effectiveness of the teaching done, the process of appraising something, to check the level of performance whereas evaluation is judging the learner based on the standards, to determine to which degree the goals are satisfied. From the reference of all the assessment, we can propose m-assessment in which the practice tests and enhancement of the topic related questions can be uploaded and be assessed frequently and immediately.

Engineering examinations are frequently based on solving problems that are best done with pencil and paper. Electronic examination systems, which offer advantages in reduced administration improved efficiency, but may not be well suited for the above type of problems, are increasingly adopted by educational institutions. This paper explores approaches to combine these methods, where students may still have the freedom to solve their examination problems on paper but their results will be entered into the electronic system for reduced time and work effort during grading.

The evaluation of students' knowledge, skills and performance is one of inseparable parts in education process. Except of various teaching approaches, the history brought also various, more or less effective assessment methods. Nowadays, thanks to the learning management systems, the e-assessment methods become more available and widespread across education institutions. The heterogeneity in usage of various assessment methods at our faculty, as well as involvement of natural subjective factors, forced us to search for the solution that can be applicable and acceptable in all study programs, courses and examinations. Furthermore, the system should be secure, intuitive and available for all teachers and their students. In this paper, we describe main principles and methodology of e-Assessment management system we implemented into the medical education for automatic assessment of students' knowledge and competences at the Faculty of Medicine in Kosice, Slovakia.

This article describes an infrastructure that is being deployed across a university to enable teachers to conduct online exams for their courses. Two examination experiences are described, one corresponding to an open book examination on the University's computers and the other corresponding to an examination involving the use of software on students' computers. The performance of the students from the first experiment is analyzed to evaluate the impact of the online format compared to the paper format. The opinions of the students of the second experiment are collected to analyze their feelings regarding the BYOD format. The results provide significant and interesting indications for the development of eassessment.

In this paper, a system to support professors in the assessment process for the paper-based examination procedure is presented. The aim of this contribution is to provide professors with tools that can help them in their assessing of the knowledge acquired by the students on the basis of the outcomes of the written exams. The platform covers all stages involved in the process including the creation and grading of those exams. The system has three main repositories: (i) an educational objects cards repository composed by a set of cards, which are used for recommending educational contents to a specific student; (ii) an exam questions repository composed by a set of questions previously used in past exams; and (iii) an explanatory objects repository composed by a set of objects that are used by the professor to explain to the student the mistake made in an exam question together with an educational content recommendation. The platform also has two assistant modules, one for the creation of the exams, and the other one to assist the assessment process (this last one including an educational content recommender).

E-assessment and tailored feedback are explored in this contribution as a means of encouraging deeper learning and increasing the effectiveness of chemical engineering education within the context of increasing larger cohort sizes in a UK Russel group institution. The results presented here indicate the benefits of both approaches to student learning, detail the implementation aspects and highlight the challenges that remain to be addressed. In addition, the results of a recent iTeach project on evaluating the effectiveness of teaching are discussed from the view point of the methods of assessment currently used. This contribution should therefore be valuable to any (engineering) higher education practitioner wishing to introduce (or extend the use of) either e-assessment or self-reflective tailored feedback in their own practice.

Learning Management Systems provide us quizzes for assessment of students' knowledge, and also a statistic report of those quizzes. Our aim was to use statistic reports as a tool for quality assessment of the five quizzes, during two academic years 2015/2016 and 2016/2017. The experiment covered five Moodle quizzes, 80 questions, and 55 students. We examined the reliability of the quizzes as they are an important part of learning and teaching process. Item analysis of the quiz is observed as the one step in learning analytics cycle. We also discuss the connection between question type and students' results on quizzes.

This paper features a software system called ∞Exarns (InfinityExams) which supports (primarily in higher education) paper-based examination and makes it easier, more comfortable and speeds up the whole process while keeping every single positive attribute of it but also reducing the number of negative aspects. The approach significantly differs from the ones used in the previous 10+ years which were implemented in such a way that they could not reproduce and replace the traditional paper-based examination model. The heart of the article relies on the most important element of the software which is the image processing flow.

The common approaches to academic integrity in the e-learning environment are resource-intensive and require technology and/or dedicated invigilation staff to monitor assessment activities. These approaches are observational and often external to the learning spaces where the majority of the instructional content resides. Authentic assessments such as discussions, projects and portfolios may not always undergo the same scrutiny as high-stakes examinations and therefore differ in the level of identity and authorship assurance they provide. In this paper, we propose an integrated approach to enhancing academic integrity of e-assessments. The approach is based on behavioral biometrics and aided by machine-learning techniques. It provides continuous identity and authorship assurance throughout the learning activities within the existing learning space. It can be applied to measure the degree of learner collaboration with peers and interaction with the course content, concurrently verifying learner identity and validating authorship of the academic artifacts. We present the preliminary results and discuss future directions.

ICTs (Information and Communication Technologies) have been used for supporting the learning process (for both distance and in-person learning) over the last years. A key part of the in-person learning process is the assessment of the students through written exams. Several years ago, BeA (Blended e-Assessment) system has been used for addressing this kind of assessment process. BeA supports the whole process of assessing through traditional written exams using ICTs. This paper introduces the facilities available in BeA to allow student-professor communication. These facilities allow the students to know at every time the state of their exams, to access the contents of those exams and the professor's reviews, and to communicate directly with the professor to solve any issue.

Eighty five nursing students of College of HealthSciences (CHS), Bahrain, taking Social and behavioral sciences course SBS126 participated in this study. Participants took an online open book formative quiz outside the class setting followed by a summative formal test covering the content in the formative quiz (condition 2). Their marks in the summative test were compared with marks obtained in an earlier summative test (condition 1) in the same course which was preceded by a formative conventional class quiz. It was hypothesized that the participants will perform better in the second condition. Results indicate that participants performed considerably better when the summative test was preceded byan online formative assessment.

Assessment is an important part of the learning process. The instructor should be able to evaluate whether a learner has acquired the knowledge and competences provided in the course. Moreover, assessment activities also help a learner to check his level of expertise. Typically, the assessment model and assessment activities of subjects in official programmes are the same for all the learners, since they should be evaluated having the same opportunities and conditions. However, when the learner is evaluated by means of a continuous assessment model, he is proving on each activity his knowledge and proficiency level and, at the same time, his reputation could be also built based on the actions he is performing within the course. Therefore, the assessment model can be adapted based on this information. In this paper, we present a general system to adapt the assessment based on different evidences gathered from the learning process of the learner.

Currently, there are many problems of the application development of E-Assessment such as the difficulty to use the assessment object from a platform to another one. In addition, the domain model reuse rate is very low in various application systems, and hardness to guarantee the consistency between designs and codes. Therefore, to resolve these problems, we need an approach aiming to automate the modeling and coding processes in e-assessment system. The present study describes an approach, based on service cloud computing, for integrating e-assessment functionalities of candidate LMS systems into a generalized e-assessment process. The proposed approach is based on three steps. The first step consists on development of generic e-assessment process based on reverse engineering. The second step describes a set mapping rules to adapt this generic e-assessment process on the learning profiles. To ensure more flexibility in the generated e-assessment process, we create a composite cloud service that's defining the mapping rules. The third step consists of defining the resulting e-assessment process as a composite cloud service allowing flexibility and interoperability between any LMS e-assessment.

After introducing e-assessment into laboratory and seminar teaching of physics in a biomedical university study program the improved final practical exam passing rate was observed. The final practical exam passing rate increased from approximately 60% to more than 80%. Encouraged by these results, in this paper we will try to show a correlation between the results of e-assessments collected during continuous monitoring of student performance and their success in final tests using neural networks as modeling method. The models will be built using various sets of data collected during three academic years. Aside from the impact on the final practical exam passing rate, the models should help us in dealing with the missing data problems. Some data are missing due to technical problems and some due to errors in student handling of e-application. In this paper we have observed data collected by two types of e-assessment. The first type of e-assessment is carried out during laboratory exercises and it influences the formation of the final grade. The second type of e-assessment is performed during seminars and has no impact on the final grade.

Constant repetition is one of the ways to improve students' knowledge of mathematics. Even Komenský said that “repetition is the mother of wisdom”, which was a revolutionary claim at the time. The use of the adaptive testing system can improve students' knowledge and make the entire education process more effective. This paper aims to introduce the basic principles of computerized adaptive testing and the possibilities of its use in the study modes.

Introducing e-assessment in high-level cognitive courses is still a difficult issue, especially when adapting theoretical models and systems to real courses. One of the challenges is that most of the e-assessment tools offer simple types of questions such as Multiple Choice Questions (MCQ), which does not allow proper assessment for skills. Another challenge is to find an appropriate way to offer formative assessment in this type of courses through both practice and assessment facilities with personalized feedback. In this paper, a general e-assessment system and a formative e-assessment model for high-level cognitive courses are presented. They allow going beyond MCQ type of questions, and an easy adaptation to different learning scenarios. The model and the system are applied into an actual high-level cognitive course, a Logic course of a Computer Science degree program in a fully online learning environment. As a result, it showed that students' participation in the continuous assessment has increased. Overall when comparing students' results before and after the introduction of the e-assessment system, it shows that with the introduction of the system, students' performance, in terms of students' marks had improved.

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Over the last decade, information security has been considered a key issue in e-Learning design. Although security requirements can be met with advanced technological approaches and these solutions offer feasible methods in many e-Learning scenarios, on-line assessment activities usually show specific issues that cannot be solved with technology alone. In addition, security vulnerabilities in on-line assessment impede the development of an overall model devoted to manage secure on-line assessment. In this paper, we propose an innovative approach to enhance technological security solutions with trustworthiness. To this end, we endow previous trustworthiness models with prediction features by composing trustworthiness modeling and assessment, normalization methods, history sequences, and neural network-based approaches. In order to validate our approach, we present a peer-to-peer on-line assessment model carried out in a real online course.

In this paper we propose an intelligent modelling of the students' knowledge collected from the e-Learning and e-Assessment processes of a particular course. The paper is focused on proposing a methodology for extracting the students' knowledge from the e-Learning activities, which we refer to as Profiling, then modifying it in compliance with their e-Assessment results and eventually, using it to model the probability distributions of the students Profiles that have passed and of those that have failed the course. The probability distributions of the students Profiles are then applied in the Bayes' theorem to perform binary classification analysis, i.e., to classify the students, pass or fail. The purpose of the proposed methodology is to simulate a real teacher, more precisely, to observe the activities of the particular student during the whole course in order to derive a decision of his or hers overall success.

ICT can contribute to the development and efficiency of education management and administration. Efforts to introduce ICT in teaching, learning and assessment aim to help meet a wide variety of goals in the education sector. This paper is based on a research project that was carried out in Strathmore University by @iLabAfrica, funded by the Kenya Education Network (KENET). The research was driven by challenges facing traditional assessment of large classes. It aimed at identifying e-assessment tools, evaluating if differences existed between performances of students examined with traditional assessment and those examined with e-assessment and investigating the feasibility of implementing e-assessment to complement eLeaming in the University. Findings revealed that a variety of tools existed and that e-assessment was better than traditional assessment in terms of students' performance, management of large classes, flexibility and cost effectiveness.

The process of assessment grading does not end on publishing the grades and assessment results. Often, discussions about single grades arise in post-exam reviews. While in traditional teaching and smaller online classes this can be handled on a per-user based approach, in Massive Open Online Courses (MOOCs) with thousands of e-assessment submissions this approach cannot be followed without investing huge resources. Therefore, a new approach of handling re-gradings is needed. In this paper, we will discuss the experience on re-gradings based on six courses offered on openHPI. We will introduce our concept of automated re-grading following an approach of fairness and demonstrate the importance of transparent communication. This paper provides a blueprint for handling re-grading issues in large scale learning environments.

This paper describes the development of a scalable and elastic e-Assessment solution deployed on the OpenStack open source cloud. The solution activates virtual machine instances with a particular size for each assessment according to the number of students that should be assessed, in order to achieve sustainable performance.

Assessment is crucial to any learning environment. Traditional methods are via tests and examinations that hold limitations presently giving way to more effective assessment tools such as Computer Based Testing (CBT). Nonetheless, contemporary CBT implementation in Saudi Arabia suffers from several drawbacks. These and two determinant factors uncovered by our research are presented in some detail. Based on these observations, future research into the development of a specific CBT framework is recommended.

This paper presents the comparison study of different multiple-choice web-based formative assessment, namely peer driven assessment module of the web-based assessment and test analysis system (PDA-WATA), one of the most recent web-based assessment system, web-based quiz-game-like formative assessment system, named GAM-WATA, and Formative Assessment Module of WATA system FAM-WATA with traditionaly normal web-based assessment and paper and pencil assessment. The major purpose of this study is to highlight the different strategies used in these system and effectiveness of each system in e-learning environment. In overall, the features and different strategies of systems is analyzed. It is found that PDA-WATA adopts more self-regulated learning strategies than the other systems in facilitating learners use of self-regulatory learning behavoir in e-learning environment. More studies are required based on different self regulatory strategies used to improving learning effectiveness, attracting learners take participation of web-based formative assessment.

This paper presents an innovative process to improve the quality of e-Assessment test creation and delivery. It aims to automatically generate a bank of items based on semantic and formal knowledge model. The OAT process is based on the three tools (1) OVACS to validate ontologies seamlessly and without technical skills. (2) AIGLE to generate a bank of QTI items thanks to semantic inference and (3) TAO, an e-Assessment platform, to deliver the produced items to the test-takers.

A case study about the validity of e-assessment and self-assessment in Electrical and Electronics Engineering studies is presented. The results show that the students are able to assess and grade their own work in a quite similar way than instructors do: high correlation coefficients, low differences between their marks and the instructors' marks comparable to those found among different instructors, no statistically different means and standard deviations, and comparable effect sizes with respect to those found among instructors. However, a relatively large number of students took advantage of the process and over marked their work. This group of students obtained surprisingly high scores in a series of e-assessed tests delivered by a learning management system. So an additional control is necessary to avoid this unfair behavior.

The article describes the implementation of a computerized testing system for the fluid power field. The system will be integrated in a e-learning platform for training the employees from the fluid power field in order to increase their competencies and performance. The computerized testing system comprises a database, a test application and an application for introducing and editing questions in the database.

Since 2005 assessment in many core engineering courses at Silesian University of Technology, Gliwice, Poland, is performed in the electronic manner. Every year the method is modified, based on teachers' experience and students' feedback [1]. Recently, the approach to e-assessment has been thoroughly revised, based on Bloom's taxonomy of students outcomes and Kolb's learning cycle [2,3]. In particular, the authors focused on the proper balance and order of the questions, corresponding to the lower level (knowledge, understanding) and the medium level (application, analysis) of Bloom's taxonomy. A new category of assessment, called “formative towards summative” (FTS) has been designed and introduced in the 2011/2012 autumn semester.

This paper presents a theoretical model for summative e-assessment in distance learning for the future, where exams can be conducted distantly, e.g. at home. This model aims to provide e-learning systems with an authentication approach that guarantees cheating-free summative e-assessment. It utilizes a combination of live video monitoring and a bimodal biometrics approach. Together they form a robust and highly secure model to ensure that the examinee is the correct person throughout the e-assessment period without a need for a proctor. Advanced techniques of image and video processing and feature extraction are required to implement this model.

This paper describes the TESLA authoring tool for creating scoring variables in the domain of complex problem solving. Its principles and high-end features will be demonstrated.