Managing students' attitude, learning engagement, and stickiness towards e-learning post-COVID-19 in Australian universities: a perceived qualities perspective

Studies have been conducted on university students' acceptance of e-learning systems during COVID-19. However, less attention has been paid to students' use of e-learning post-pandemic. This research provides a more comprehensive framework to investigate the effects of e-learning students' various quality perceptions on attitude, learning engagement, and stickiness toward e-learning platforms. A survey-based quantitative method is adopted by this study in which sample data are collected from students in Australian universities. A total of 403 valid samples were analysed using covariance-based structural equation modelling. This study found that students' perceived educational quality, service quality, information quality, and technical system quality play different roles in their attitudes and behaviours towards e-learning. It expands the information system success model by comparing the effects of students' various perceived qualities on their ongoing commitment to e-learning. It provides insights to e-learning providers in pursuing better designs and more sustainable development of educational information systems.

E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review.

E-learning is fast becoming an integral part of the teaching- learning process, particularly after the outbreak of Covid-19 pandemic. Educational institutions across the globe are striving to enhance their e-learning instructional mechanism in accordance with the aspirations of present-day students who are widely using numerous technological tools - computers, tablets, mobiles, and Internet for educational purposes. In the wake of the evident incorporation of e-learning into the educational process, research related to the application of Educational Data Mining (EDM) techniques for enhancing e-learning systems has gained significance in recent times. The various data mining techniques applied by researchers to study hidden trends or patterns in educational data can provide valuable insights for educational institutions in terms of making the learning process adaptive to student needs. The insights can help the institutions achieve their ultimate goal of improving student academic performance in technology-assisted learning systems of the modern world. This review paper aims to comprehend EDM's role in enhancing e-learning environments with reference to commonly-used techniques, along with student performance prediction, the impact of Covid-19 pandemic on e-learning and priority e-learning focus areas in the future.

General Characteristics of the Assisted E-Learning System in Computer Sciences

Taking into consideration all the restrictions applied worldwide due to the Covid-19 pandemic in the recent couple of years, it is completely understandable why the educational system as well had to adapt and move all its activities online. Even though this kind of approach has turned out to have many advantages, there are certainly still things that could be improved and explored. The main objective of this paper is to highlight the importance and benefits of online learning tools which could assist students during their educational process, even under normal circumstances. Hence, we will analyse the characteristics of the current eLearning applications and what each one proposes for the automation of computer-assisted learning using the computer science field. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Understanding E-learning Adoption and Acceptance during the Covid 19 Pandemic: The Influence of Self Efficacy

The world wide outbreak of the COVID-19 pandemic reconfigured various landscapes in higher education as various institutions, lecturers and students were forced to adopt e-learning. However, the successful adoption and acceptance of e-learning by both lecturers and students involved has not been discussed and measured. This study seeks to investigate the influence of both the lecturer and student self efficacy on behavoral intention to use e-learning during the pandemic in the context of the Technology Acceptance Model (TAM). Lecturer Self-Efficacy (LSE) and Student Self-Efficacy (SSE) were hypothesized to have a correlation with the perceived usefullness and perceived ease of use of e-learning systems as well as the attitude towards using those e-learning systems which resultantly influence the behavoural intention to use e-learning systems. A total of 362 questionnaires were received from both students and lecturers in Zimbabwe's two universities and two polytechnics. Structural Equation Modelling was utilized to test the hypothesized conceptual model. Reliability and validity checks were done to the model instrument. Results indicated that both LSE and SSE have a positive influence on perceived ease of use but however, both LSE and SSE revealed a negative influence on perceived usefullness. Results also indicated that both LSE and SSE have a positive influence on attitude towards use of e-learning systems. The findings of the study contribute to the literature by highlighting the influence of LSE and SSE in the adoption and acceptance of e-learning systems in higher education. © 2022 IEEE.

Generic Laboratory Authoring Tool for Virtual and Remote Controlled Laboratories

Due to the impact of Covid-19, many students all over the world have faced some educational issues. Therefore, many educational institutes focused on shifting their learning process to E-learning system. To provide a complete E-learning system, the performing of virtual and remote Laboratory experiments is needed. In this paper, a generic and flexible online authoring tool for the Laboratory Learning System (LLS) is presented. The LLS system is a platform that provides teachers and students with a flexible environment for virtual and remote controlled labs using the proposed authoring tool. The heart of the LLS system is the authoring tool which facilities the ease and flexibility of designing various laboratory experiments which includes a number of pages, and each page has a number of steps with many draggable components. Furthermore, the proposed authoring tool is the first authoring tool that provides general and reusable virtual laboratory resource (VLR) for automatically managing laboratory software and hardware resources. To support the new VRL feature of the authoring tool, the LLS supports the ability to remotely control the laboratory equipment while performing laboratory experiments and also has the capability to run any type of simulation tool for virtually simulated labs. The proposed authoring tool is designed considering all the needed components with well-defined interfaces to achieve an effective and flexible Laboratory learning system. © 2022 IEEE.

System Characteristics in Predicting E-Learning Acceptance: An Extended Technology Acceptance Model (TAM) Study

Learning habits among students in higher institution, has radically changed over the last two decades, partially due to the features of the information and digital society, wide scale broadband internet access, proliferation of smart devices and consequently, available online mobile applications. Thus, in higher education, e-learning systems are essential, and the COVID-19 pandemic era has seen an increase in popularity of e-learning. Thus, it is critical to establish the extent to which students in higher education adopt e-learning. This paper focuses at developing a framework for e-learning technologies through the Technology Acceptance Model (TAM) by incorporating system characteristics as its' extended variable, which consists of three main constructs: system quality, content quality and information quality among university students in Malaysia. Regarding the system characteristics, the findings suggested that all three components that make up system characteristics had a significant positive influence on students' perceived ease of use of the e-learning system, whereas only system quality and information quality had a significant positive impact on students' perceived usefulness of the e-learning system. With respect to TAM, all relationships were found to be significant. © 2022 IEEE.

Evaluation of E- Learning in Engineering Education in Higher and Tertiary Education Institutions in Zimbabwe

The adoption of ICTs and e-learning tools in institutions of higher education provides several benefits including enhancing engineering education. The Covid 19 global pandemic forced most institutions to adopt e-learning in order to improve access and quality of education. In order to evaluate the e-learning in higher and tertiary institutions, a cross sectional survey comprising of 32 instructors from the 5 departments in the faculty of engineering at Chinhoyi University of Technology (CUT) was carried out. Data collected using a survey questionnaire was analyzed using IBM SPSS Grad Pack version 28.0 premium. On average 23.34 % of the instructors never practiced e-learning, 18.96 % practiced e-learning rarely, 15.84 % practiced e-learning moderately, 12.48 %practiced e-learning substantially and 26.66 % practiced e-learning extensively in their teaching and learning. The usage of virtual laboratories and online assessment was found to be extremely low at 11.4 % respectively. The study revealed that CUT has an official e-learning strategy embedded in the ICT policy. About 63 % of the respondents were satisfied with the e-learning systems and affirmed that their productivity and performance improved through the use of the e-learning system. The existence of a sound e-learning policy has a direct impact on educational delivery. Although instructors had computers 88 % had no access to web cameras for online teaching and learning. The most prevalent challenge was power failure. The study recommended the development of e-learning quality assurance standards to ensure consistency and uniformity in the conveyance of e-learning in engineering education. The output of this will provide useful insights on the current usage of e-learning and recommendation to address the challenges affecting the adoption of ICTs and e-learning in higher and tertiary education institutions in Zimbabwe. © 2022 IEEE.

Classifying the Students' Behavior on e-Learning System using Fine-Tuning K-NN Method

monitoring the student's behavior is challenging for teachers in online learning, which is crucial to solving. It is because, in this pandemic period, online learning is required to minimize the spreading of coronavirus. However, research in this domain is not much. This study provides an alternative to this problem by classifying students' behavior in the e-Learning system, where the k-NN is applied to mine the students' behavior. In addition, this paper also tests the proper parameters to improve the performance of k-NN: k and distance. The experimental result shows that the best performance on the cross-validation technique is reached by Euclidean distance and, on the percentage-split, is achieved by distance-Manhattan. These are indicated by the highest accuracy level obtained by neighbors of five and 20 fold, about 96.9% on the cross-validation technique. On the percentage split technique, the highest accuracy level, about 95.3%, is reached by neighbors of four and split 50%. In this best performance, four students are misclassified on the cross-validation and six on the percentage split. © 2022 IEEE.

Electrical Engineering E-learning Education during COVID-19 Pandemic: Pedagogical and Psychological Aspects

The aim of the paper is to discuss the online education experience of the students from Electrical Engineering. The study discusses the accumulation of information during pandemic by comparing the accumulation of online information to the system face to face from the personal perspective of the student, highlighting the benefits and difficulties. © 2022 IEEE.

The Need for E-Learning Standards for Online Laboratory Management Systems

E-Learning education, Massive Online Open Courses (MOOCs) and Small Private Online Courses (SPOCs) have been ex-panding in the last decade. However, it increased in giant strides during the COVID-19 pandemic when the schools and universities did not have another option than to use remote education. Having a general understanding of E-Learning technology is not enough to implement an engineering virtual classrooms and laboratories. E-Learning standards are needed in all areas of E-Learning Systems such as online educational web applications, Learning Management Systems, and online labs, among others to gain interoperability, scalability, sustainability, security, privacy, and safety. The main objective of this paper is to discuss in general the current standards and technologies applied to E-Learning systems and analyze the need for a specific standards for Online Laboratory Management Systems (OLMS). © 2022 IEEE.

Mental States and Cognitive Performance Monitoring for User-Centered e-Learning System: A Case Study

The unprecedented long-term online learning caused by COVID-19 has increased stress symptoms among students. The e-learning system reduces communications between teachers and students, making it difficult to observe student's mental issues and learning performance. This study aims to develop a non-intrusive method that can simultaneously monitor stress states and cognitive performance of student in the scenario of online education. Forty-three participants were recruited to perform a computer-based reading task under stressful and non-stressful conditions, and their eye-movement data were recorded. A tree ensemble machine learning model, named LightGBM (Light Gradient Boosting Machine), was utilized to predict stress states and reading performance of students with an accuracy of 0.825 and 0.793, respectively. An interpretable model, SHAP (SHapley Additive exPlanation), was used to identify the most important eye-movement indicators and their effects on stress and reading performance. The proposed model can serve as a foundation for further development of user-centred services in e-learning system. © 2022 The authors and IOS Press.

Learning in Project-Based Engineering Education: A Bibliometric Analysis

The events caused by the COVID-19 pandemic forced educators to transition to a fully online education system. Therefore, the implementation of project-based learning (PBL) in education is not an easy task. However, since PBL offers students many learning benefits, the aim of this paper is to conduct a bibliometric analysis to measure the performance of using PBL in engineering courses. Two computer tools have been used to carry out the analysis: a) Scopus as a performance analysis tool and b) SciMAT to carry out the bibliometric analysis of content from scientific maps. The results show that the topic with the highest performance for the period 2000-2015 corresponds to the topic of engineering educators, with a h-index of 19, 157 linked articles and, 4815 citations. However, the transition to digital teaching is shown in the period 2016-2021, where e-learning systems represent a cross-cutting theme in the field of research. Therefore, the close relationship of the PBL methodology with engineering educators and the transition to virtual education is shown. However, it requires the integration of e-learning platforms. This is closely related to the driving topics shown in the strategic map for the 2016-2021 period, such as: ensuring the quality of teamwork;properly monitor learning experiences;enhance the focus on engineering design;and work on planning the design of the curriculum, to involve all the activities and evaluations of the educational goals. © 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

University life has gone digital: influences of institutional mobile social network use during the COVID-19 emergency

Purpose Many universities implemented institutional social networking apps as an alternative to in-person social experiences during the COVID-19 pandemic. Therefore, this study aims to explore previously identified factors that influenced intentions to form collective actions, also known as we-intentions, on such social networking apps and their influence on student satisfaction with the app artifact. Design/methodology/approach Students from across a large university were invited to participate in a survey. Responses from 915 students who reported using the app were analyzed using a maximum likelihood covariance-based structural equation model. Analysis was conducted using the R programming language's psych, lavaan, and semTools packages. Findings The authors found that we-intentions are positively associated with recent app use and with student satisfaction with the app. Group norms were found to significantly influence the formation of we-intentions, while social identity is positively associated with both we-intentions and satisfaction. Originality/value The paper provides evidence that past research generalizes to the context of university mobile social networks and identifies a relationship between we-intentions and satisfaction in this context. It also provides practical insight into factors that influence we-intentions, and subsequently students' online education experience, in the context of a university's institutional mobile social network.

The Impact of Covid-19 Pandemic on Undergraduate Students: The Role of an Adaptive Situation-Aware Learning System

In the context of the emergency of COVID-19, students have experienced moments of strong emotional stress, with the risk of generating a state of frustration and discouraging them from studying. The proposed adaptive e-learning system, based on situational awareness, and remodeled teaching were essential in limiting this phenomenon. The system has been designed and developed according to the design principles of Situation Awareness. The feedback selection process, updated through the years to face the emergency situation, is driven by a Fuzzy Cognitive Map, implemented to identify the learners' situation, defined through their levels of engagement, motivation, and participation. The experimentation was conducted using the SAGAT methodology, involving students participating in classes during the courses held over the academic years 2018/2019, 2019/2020, and 2020/2021. The results show that the system is capable of increasing the level of situation awareness of the students even in a context of emergency. © 2022 IEEE.

The Impact of e-Learning Systems on Motivating Students and Enhancing Their Outcomes During COVID-19: A Mixed-Method Approach.

e-Learning is a key strategy in the course of higher education to improve the results of the educational process and stimulate student motivation. The COVID-19 pandemic imposed on Algerian universities to adopt e-Learning systems to search for effectiveness and efficiency of academic approaches. This paper seeks to remedy these problems by analyzing the impact of e-Learning systems on student motivation and outcomes. A mixed-method approach was used in the data analysis. We conducted the study as a survey, with data being gathered via questionnaires distributed to 398 students. The questionnaire includes open questions that were qualitatively analyzed using content analysis with Nvivo, besides Likert scale questions were quantitatively analyzed and modeled using Structural equation modeling (SEM) with Amos to accomplish the path analysis of the research model. The results of the study showed that student motivation (Attention, Relevance, Confidence, and Satisfaction) and student outcomes (knowledge, skills, and attitudes) are significantly affected by e-Learning systems (Technical and electronic requirements, personal requirements, perceived value, and credibility of e-Learning). The key findings are discussed, and they provide recommendations for future research.

An Interactive E-Learning Tool

Use of E-learning systems has surged immensely during the Covid-19 pandemic, which started around 2020. This research specifically conducted to introduce novel features with the purpose of enhancing traditional E Learning platforms. The suggested features are namely, avoid unauthorized users from accessing private video sessions using face recognition, manipulating 3D objects by hand gestures, analyzing student's attention using face landmarks, smart QAs using voice recognitions. These features will provide not only an enhancement for e-Learning platforms but also it will improve user experience, efficiency, and effectiveness of current tools up to a certain distinguishable level. © 2022 IEEE.

AI and Machine Learning Based E - Learning System For Secondary Education

One of the key functions directly shifted to online platforms under COVID-19 is education. The paper is about an E-learning system for secondary education in Sri Lanka. Learners and teachers can access information, resources, and tools through an E-Learning system, which is a Learning Management System that integrates a number of online activities. The main functions provided through the proposed system are chatbot, final grade prediction and weak area prediction of the students. Chatbots are becoming increasingly popular in a wide range of applications, especially in those that provide intelligence support to the user, according to recent research. So, in order to speed up the aid process, these systems are often integrated with Chatbots, which can quickly and accurately read the user's questions. This paper describes the implementation of a Chatbot prototype in the educational domain: a system for providing support to students. In the beginning, the goal was to design a special architecture and communication model that would help students get the proper answers. The final grade prediction component plays major role in the system. Because when the students are graded by their marks, they can review which areas that they have to improve and work on them. This is helpful for students as well as teachers. Weak area prediction also plays a significant role, because it can help to find out the weak areas of each subject and generate Individual Student Progress Plans to predict the students' weak subjects and the subject areas of the students. This motivates students to get higher marks easily because this part is mainly focused on weak areas of students and improve those weak areas by providing several learning activities. These are the major parts of this system to have a good E-learning system for both students and Teachers. © 2022 IEEE.

Factors Influencing University Students’ E-Learning Adoption in Bangladesh During COVID-19: An Empirical Study with Machine Learning

The present study investigates the factors that influence Bangladeshi university students’ behavior toward adopting the e-learning system during the COVID-19 emergency. A conceptual framework was developed by adopting the variables from several previously published studies to meet the aims of the study. The current study was conducted in the quantitative approach by performing a survey on 393 university students of Bangladesh. All the obtained data were analyzed by using SPSS, AMOS, and machine learning algorithms. The findings of the study indicate that facilitating condition, effort expectancy, performance expectancy, and social influence affect the behavioral intention of the students to adopt e-learning, and the current study provides both practical and theoretical contributions. Theoretically, it provides a research framework and the literature to analyze the factors that trigger the behavioral intention of Bangladeshi university students. Practically, the findings will assist the policymakers of the education industry in Bangladesh. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The Use of SCRUM Methodology for Final Year Undergraduate Project During Corona Pandemic

Scrum methodology is a traditional agile technology that uses sprints and various forms of meetings to problems and issues during software development and allow a student to practice learning a programming language during design and analysis phases, but it has become difficult to coordinate such physical meetings during teaching and learning in the undergraduate project. Software development team during the COVID- 19 pandemic facing difficult to arrange such meetings. In this paper, we will explain the reasons for the superiority of scrum over traditional methods and the extent of the impact of the Corona pandemic on product quality and customer and employee satisfaction. © 2022 IEEE.

Impact of Covid-19 on Education

The world is reeling in the midst of the novel corona virus pandemic with fear of rising toll due to the deadly virus. This situation caused complete lockdown in many countries thus posing one of the biggest challenges to educational institutions and academicians to continue the teaching learning process involving students. E-learning system is very important to ensure successful delivery, effective use, and positive impacts on learners. In order to engage learners while at home as well as to utilise their time and complete syllabi, the process of teaching-learning and assessment need to be streamlined. However, while doing so, the institution should keep in mind various skills related as well as infrastructure related constraints on the part of school, teacher, student and parents. But, in reality, majority of the institutions are conducting online classes in urgency regardless of skill and experiences of concerned teachers and students. It is even more challenging when teachers and academicians alike are not well trained at technological tools for virtual/online classes. Students at large are also not acquainted with technologies and much help can’t be expected from their parents in this regard. The goal of this chapter is to investigate students’ opinions for virtual classes focusing on their learning and behaviour during COVID-19. The said study is validated through the student satisfaction survey involving directly students from different institutions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.