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This study examines learner satisfaction and success as mechanisms through which online learning quality translates into learners’ continuous intentions of use by extending DeLone and McLean’s information system success model. It also examines the moderating effect of perceived supervisory support and learners’ self-regulation on online learning quality in Higher Education Institutions.

Survey data were obtained from 540 students in both private and public higher institutions of learning in Ghana. The Partial Least Squares – Structural Equations Modelling (PLS-SEM) technique was used to test the hypothesised relationships.

The results revealed that system quality emerged as the single most important variable in the DeLone and McLean model, that influences learner success and satisfaction. Further, learner satisfaction has a significant positive effect on learner attitudes, whilst self-regulation was found to moderate the relationship between online learning quality and learner success as well as learner satisfaction.

The study appears to be among the first to explore the inter-relationship among online learning environment quality and learner attitudes and moderating factors perceived supervisory support and self-regulation. The study highlights insightful practical implications for students, faculty and administrators of higher institutions.

Career preparedness is critical to successfully transitioning from college to a full-time work environment. Being prepared means students have the technical and non-technical skills to help an organization meet its strategic goals. In many instances, students lack the requisite career competencies and collaborative skills. This study proposes designing an instructor-led, career-driven quasi-virtual internship to address this issue and improve students’ preparedness and teamwork.

Our research integrates and expands the four-step processes outlined in instructional and course redesign theories, including analysis, design and development, implementation and evaluation. In the evaluation phase, a survey is used to collect data, and natural language processing is applied to identify the emerging themes. The sample included 104 undergraduate students enrolled in an information systems degree program, which resulted in a digital corpus of 40,744 words for analysis.

Results indicate that the implementation of instructor-led quasi-virtual internships offered a comprehensive career experience comparable to an onsite or virtual company-sponsored internship in five notable areas: (1) application of technical knowledge, (2) critical thinking, (3) time management, (4) application of IT project management and (5) collaborative skills.

Our study only evaluated participants in our treatment group. Future research should examine the differences between students who complete sponsored versus instructor-led quasi-virtual internships. Researchers can add a control group of students who receive a theoretically based capstone course. Future research can simulate randomized controlled trials (RCT) (Chalmers et al., 1981) to measure the effectiveness of quasi-virtual internships. A benefit of this research is that an open-ended survey allows for collecting rich, multifaceted primary data. The second limitation is that the study included only single-item questions. Future authors can create and validate a survey instrument based on the themes and concepts emanating from our investigation. For example, they can operationalize team dynamics and career preparedness using a reflective model in which the underlying construct drives the indicators, requiring multiple items to examine each construct (Coltman et al., 2008). Third, the sample size in the study was relatively small. We can increase the sample size using a time-series dataset with multiple measurement periods. The fourth limitation is context; this study was conducted at a public university; other institutions may have varied teaching approaches, student demographics and resources. By expanding our study using a multi-site approach (Ballantyne et al., 2012), we can increase cross-sectional sample sizes and improve the generalizability of the study’s results.

This study provides several practical insights for educators by examining quasi-virtual internships. Academic institutions that want to offer internships but struggle to establish industry partners can implement the quasi-internship model as an alternative approach. The study highlights that students gain critical insight into their future careers during these internships by being familiar with industry concepts and tools. We also provide insights into engaging students in “meaningful collaboration.” We suggest the instructor provide some time during the class sessions for group work to improve coordination and introduce industry-level tools that provide a more applied approach to IS education.

The National Survey of College Internships (NSCI) 2021 indicates that underrepresented and first-generation students were less likely to participate in internships. Our research may positively impact diverse communities since the quasi-virtual internship allows all students to participate once they are enrolled in a capstone class.

To our knowledge, this study is the first to utilize latent semantic analysis to analyze students’ feedback to improve course design, career preparedness and team dynamics.

Sustainability and accessibility of education are the main purposes of educational institutions. Higher education institutions (HEIs) have been addressing these concerns through their distance education departments for years. Especially during and after the COVID-19 pandemic, HEIs encountered challenges related to productivity, escalating costs and decreasing user satisfaction with distance education. This study proposes the integration of new and suitable information technologies (ITs) into the steps of lean management (LM) implementation. It suggests that this approach will be highly effective and beneficial, providing solutions to the problems above in higher education (HE) field. The study aims to highlight the effectiveness and benefits of incorporating new and suitable ITs into the application stages of LM principles. Sample applications in HE will be provided to enhance understanding.

A model is introduced for researching new ITs and incorporating appropriate ones in the application steps of LM. This model has been applied and analyzed in two case studies at Gazi University for a more comprehensive understanding.

When examining periodic surveys and usage statistics from case studies, it becomes evident that implementing LM with the support of ITs reduces waste and enhances the quality of existing work. The success observed in the case studies was notably influenced by managers’ proficiency in business processes, experience in ITs, managerial skills and support from senior management.

This case study provides a roadmap and step-by-step implementation of LM with IT support for HEIs. The implementation process and results will also be guiding for other sectors.

There is a notable absence of significant studies on integrating ITs, which have become crucial in today’s context in the stages of LM implementation. This study is envisioned as a pioneering endeavor to address this gap in the literature. Notably, challenges exist in applying LM principles outside production sectors, and limited research has been conducted. This study aims to pave the way for further research in diverse fields by conducting a comprehensive case study in the realm of HE.

A new Chatbot system is implemented to provide both voice-based and textual-based communication to address student queries without any delay. Initially, the input texts are gathered from the chat and then the gathered text is fed to pre-processing techniques like tokenization, stemming of words and removal of stop words. Then, the pre-processed data are given to the Natural Learning Process (NLP) for extracting the features, where the XLnet and Bidirectional Encoder Representations from Transformers (BERT) are utilized to extract the features. From these extracted features, the target-based fused feature pools are obtained. Then, the intent detection is carried out to extract the answers related to the user queries via Enhanced 1D-Convolutional Neural Networks with Long Short Term Memory (E1DCNN-LSTM) where the parameters are optimized using Position Averaging of Binary Emperor Penguin Optimizer with Colony Predation Algorithm (PA-BEPOCPA). Finally, the answers are extracted based on the intent of a particular student’s teaching materials like video, image or text. The implementation results are analyzed through different recently developed Chatbot detection models to validate the effectiveness of the newly developed model.

A smart model for the NLP is developed to help education-related institutions for an easy way of interaction between students and teachers with high prediction of accurate data for the given query. This research work aims to design a new educational Chatbot to assist the teaching-learning process with the NLP. The input data are gathered from the user through chats and given to the pre-processing stage, where tokenization, steaming of words and removal of stop words are used. The output data from the pre-processing stage is given to the feature extraction phase where XLnet and BERT are used. In this feature extraction, the optimal features are extracted using hybrid PA-BEPOCPA to maximize the correlation coefficient. The features from XLnet and features from BERT were given to target-based features fused pool to produce optimal features. Here, the best features are optimally selected using developed PA-BEPOCPA for maximizing the correlation among coefficients. The output of selected features is given to E1DCNN-LSTM for implementation of educational Chatbot with high accuracy and precision.

The investigation result shows that the implemented model achieves maximum accuracy of 57% more than Bidirectional long short-term memory (BiLSTM), 58% more than One Dimansional Convolutional Neural Network (1DCNN), 59% more than LSTM and 62% more than Ensemble for the given dataset.

The prediction accuracy was high in this proposed deep learning-based educational Chatbot system when compared with various baseline works.

The purpose of this paper is to articulate how the user experience (UX) approach was initiated and integrated into the centre’s scope of operations with the objective of improving the e-learning layout on the D2L learning management system (LMS). One of the most effective ways to collect user feedback has historically been to evaluate user interfaces using strategies from user testing. The integration of a UX approach by the Centre for ODL Experiences (COLE) at Wawasan Open University has led to a more user-oriented design of FlexLearn by conducting user testing on students as the target users of the platform and gathering course leaders’ (CLs) feedback after the presentation of the new template.

Since the process of design and development is a looping process, the first user testing methods employed were observation and interviews, which were conducted over the course of numerous sessions. The data collection used a mixed-methods approach, combining quantitative demographic and background data with qualitative feedback from open-ended questions and real-time interview responses. A standardized questionnaire gathered demographic information, while questions for feedback forms and interviews were adjusted based on specific tasks to explore usability and user interactions comprehensively.

The findings revealed overall positive feedback, with some concerns highlighted by the students who claimed to have trouble navigating the courses during the initial prototype. In addition to the qualitative data from the user testing session, a quantitative method based on an online questionnaire was also utilised for the CLs after the presentation of the final layout. Positive responses were received from the CLs, and constructive suggestions were considered for FlexLearn 3.0.

This paper is among the first that articulates the process of initiating and integrating user-centred design in an effort to improve the user experience of online and ODL platforms and LMSs. It will contribute to a dialogue on investigating and prioritising learners’ ODL experiences to ensure education equity across all levels or categories of students, which aligns with the United Nations Sustainable Development Goals.

The integration of UX and user testing allows us to better identify what users like, their concerns and their needs. We gain important input on how easy or difficult it is to use the system, move around it and how much they enjoy using it. This feedback helps us make changes to the design so that the final product is more in line with what users want. It also allows us to discover problems before they become major, saving time and effort later on. Finally, integrating user input improves the LMS, delivering a more fun and successful learning experience for everyone.

User-friendly systems arise as institutions prioritise user-centred design, breaking down barriers for various learners. This develops an innovative culture, improving present learning experiences and setting a precedent for future generations. The emphasis on user demands helps to create a more accessible, adaptive and egalitarian educational landscape by connecting education with current technological trends. As education becomes more inclusive, the broader community benefits, emphasising the beneficial social impact of LMS user testing.

By articulating the process of integrating user testing on an LMS/e-learning prototype, helps us understand what users like, where they face problems and what needs improvement. By involving users in testing, we get valuable feedback on how easy it is to use the system, navigate around and overall, how much they enjoy using it. Case studies like this also offer universities concrete examples of real-world challenges and successes.

Service quality in academics is imperatively crucial. Therefore, the purpose of the current research is to examine the effect of academic service quality factors in higher education institutions which mainly focuses on students' satisfaction and the extent of recommending the same institution to other students.

This research evaluated the effect of service quality on student satisfaction and word of mouth (WOM). Data were collected from 200 respondents from various business schools, and hypotheses were tested through a quantitative method using partial least square-structural equation modelling (PLS-SEM) with the help of SmartPLS to validate the measurement model.

The findings of the current research revealed that all three components of service quality including information quality, teaching quality and service efficiency have a significant impact on student satisfaction. Results also indicated that student satisfaction is significantly linked with WOM which means satisfied students spread positive WOM and recommend the same institution to other students.

This research provides an extension towards the body of knowledge on the issue, which will be used in future detailed and critical examinations. The focus of the research was on SERVQUAL and how, when and why business schools may spot possible applications that can have an influence on their admissions by WOM.

Small-to-medium-sized enterprises (SMEs) in e-commerce often invest in information technology (IT) to stay competitive. However, whether and how IT capability (ITC) translates into financial performance requires further research. This paper examines the role of ITC in enabling value proposition innovation (VPI) as an important mechanism that improves financial performance for Chinese e-commerce SMEs during the COVID-19 pandemic. We argue that ITC is critical for enabling innovation because it elevates SMEs’ understanding of changing customer needs, especially when SMEs operate on multiple e-commerce platforms (multihome).

We used partial least squares structural equation modeling (PLS-SEM) and tested the hypotheses that ITC mediated by VPI and moderated by multihoming increases the financial performance of e-commerce SMEs through a survey among 206 Chinese SMEs operating on Taobao.

We find that not only higher levels of ITC lead to better financial performance, but also that the effect is fully mediated by VPI. Moreover, the effect of ITC on innovation is enhanced when vendors operate on multiple platforms.

The study identifies VPI as an important mechanism through which SMEs can leverage their ITC to adapt, innovate and thrive in competition. Our work suggests that using technology to develop innovative ideas and identify opportunities (which are reflected in VPI) is key to success and that doing so is more likely when vendors multihome. Thus, this study contributes to the innovation literature by explicating a concrete link between ITC, multihoming, VPI and increased financial performance. Different e-commerce stakeholders, including SME owners, IT and service providers and e-commerce platforms, can benefit from the findings of this work.

The purpose of this paper is to provide an overview of the trends and challenges relating to research into the human aspects of ransomware.

A systematic mapping study was carried out to investigate the trends in studies into the human aspects of ransomware, identify challenges encountered by researchers and propose directions for future research. For each of the identified papers from this study, the authors mapped the year of publication, the type of paper, research strategy and data generation method, types of participants included, theories incorporated and lastly, the authors mapped the challenges encountered by the researchers.

Fifty-nine papers published between 2006 and 2022 are included in the study. The findings indicate that literature on the human aspects of ransomware was scarce prior to 2016. The most-used participant groups in this area are students and cybersecurity professionals, and most studies rely on a survey strategy using the questionnaire to collect data. In addition, many papers did not use theories for their research, but from those that did, game theory was used most often. Furthermore, the most reported challenge is that being hit with ransomware is a sensitive topic, which results in individuals and organisations being reluctant to share their experiences.

This mapping study reveals that the body of literature in the area of human aspects of ransomware has increased over the past couple of years. The findings highlight that being transparent about ransomware attacks, when possible, can help others. Moreover, senior management plays an important role in shaping the information security culture of an organisation, whether to have a culture of transparency or of secrecy.

This study is the first of its kind of systematic mapping studies contributing to the body of knowledge on the human aspects of ransomware.

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.

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.

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.

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.

Alexa’s integration in rural primary schools has improved the pedagogy and has created an engaging and objective learning environment. This study investigates the integration, with a specific focus on exploring its various aspects. The impact of Alexa’s on students' English vocabulary, comprehension and public speaking are examined. This study aims to provide insights the teachers and highlight the potential of artificial intelligence (AI) in rural education.

This content analysis study explores the use of Alexa in primary education in rural areas of India. The study focuses on the types of the questions asked by the students and examines the pedagogical implications of these interactions. By analyzing the use of Alexa in rural educational settings, this study aims to contribute to our understanding of how voice assistants are utilized as educational tools in underprivileged areas.

Alexa significantly improved students' English vocabulary, comprehension and public speaking confidence. Alexa increased school enrollment and retention. Virtual voice assistants like Alexa may improve pedagogy and help India’s rural education. This study shows AI improves rural education.

The study only covers rural India. Self-reported data and observations may bias the study. The small sample size may underrepresent rural educational institutions in India.

Alexa is used to study rural India’s primary education. Voice assistants in rural education are understudied. The study examines Alexa’s classroom use, student questions, and policy and teacher education implications. AI’s education transformation potential addresses UNESCO’s teacher shortage. This novel study examines how AI can improve rural education outcomes and access.