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The research is focused on a comprehensive analysis of digitalization as a prerequisite for higher education modernization. The authors of this article consider the digital divide as a component of information inequality, which has a technological nature and presupposes unequal opportunities for access, use, and production of information and knowledge or new technologies for their effective use in practice. The authors determined the digital divide is intensifying under pandemic and quarantine restrictions when the preference is given to blended learning technologies, collaborative learning, integrated learning, flipped classroom technology, storytelling, inquiry based learning (IBL), and project based learning (PBL). The research result is a unified information and communication ecosystem developed, which unites the scientific, technological, and educational potential of the network educational digital environment. The ecosystem also provides for the transformation from a lineal to a cluster model of competence cultivation, the formation of digital skills, growth in the volume of information, and creation of digital products.

Digital and information literacy skills are necessary to succeed in today's knowledge economy but for the millions of people in the world without internet access, a frustratingCatch-22 exists: How can they develop digital literacy skills without internet access? When they get access, what good is the internet to them if they don't have the skills to use it productively? One answer is an offline digital library called SolarSPELL. This report from the field describes a series of instructional videos the author created to foster digital and information literacy skills among novice SolarSPELL users.

Many studies have recently focused on the importance of the effective integration of Information and Communication Technology (ICT) tools in science education and the need for science teachers to receive adequate training and support to use them effectively. This paper aims to explore the Albanian science teachers' perceptions and use of ICTs in teaching processes. The study provides an interpretative analysis of the opinions of science teachers teaching in the middle and high schools of several Albanian regions expressed in an online survey. Overall, the results suggest that the use of ICT by science teachers in Albania is limited by a lack of proper infrastructure, limited access to technology, and training of teachers on integrating technology. However, there are indications that the adoption of ICT in science education may increase in the future, particularly after the boost from the COVID-19 pandemic emergency.

Open and distance learning (ODL) activities aim to meet the expectations and needs of different individuals, societies, and systems by ensuring the continuation of learning with a lifelong learning philosophy and an egalitarian policy for everyone, regardless of time and place. Support services, which address the differentiated expectations and needs in all learning-related activities, serve the learning processes and the various stakeholders involved. Therefore, technical support services are included in support activities that require the use of technology as a tool, mediator, or technique in learning processes. In this study, ODL systems that are situated in digital space are examined within the scope of technical support services in line with the threats and dangers of the developing and expanding digital space. The aim is to create a technical support service model based on Herbert Simon's Bounded Rationality Theory and Otto Peters' Industrialization Theory, to ensure cybersecurity in ODL systems. In this study, which adopted a case study as one of the qualitative research methods, documents in the literature were examined first. Considering the literature, the opinions of eight field experts were gathered by ten interview questions. After the semi-structured interviews were transcribed, the data obtained were divided into codes and themes through thematic analysis. The findings stressed the importance of institutional culture, distribution of tasks and responsibilities, administrative support, institutional awareness, cybersecurity training, and the use of different technologies to ensure cybersecurity in ODL systems. Additionally, the experts emphasized a common view that smart systems should be used in the provision and maintenance of cybersecurity.

Data transfer between isolated clusters is imperative for cybersecurity education, research, and testing. Such techniques facilitate hands-on cybersecurity learning in isolated clusters, allow cybersecurity students to practice with various hacking tools, and develop professional cybersecurity technical skills. Educators often use these remote learning environments for research as well. Researchers and students use these isolated environments to test sophisticated hardware, software, and procedures using full-fledged operating systems, networks, and applications. Virus and malware researchers may wish to release suspected malicious software in a controlled environment to observe their behavior better or gain the information needed to assist their reverse engineering processes. The isolation prevents harm to networked systems. However, there are times when the data is required to move in such quantities or speeds that it makes downloading onto an intermediate device untenable. This study proposes a novel turnstile model, a mechanism for one-way file transfer from one enterprise system to another without allowing data leakage. This system protects data integrity and security by connecting the isolated environment to the external network via a locked-down interconnection. Using medium-security isolated clusters, the researchers successfully developed a unidirectional file transfer system that acts as a one-way "turnstile" for secure file transfer between systems not connected to the internet or other external networks. The Turnstile system (source code available at github.com/monnin/turnstile) provides unidirectional file transfer between two computer systems. The solution enabled data to be transferred from a source system to a destination system without allowing any data to be transferred back in the opposite direction. The researchers found an automated process of transferring external files to isolated clusters optimized the transfer speed of external files to isolated clusters using Linux distributions and commands.

This paper investigates the integration of blockchain technology into core systems within institutions of higher education, utilizing the National Institute of Standards and Technology's (NIST) Cybersecurity Framework as a guiding framework. It supplies definitions of key terminology including blockchain, consensus mechanisms, decentralized identity, and smart contracts, and examines the application of secure blockchain across various educational functions such as enrollment management, degree auditing, and award processing. Each facet of the NIST Framework is utilized to explore the integration of blockchain technology and address persistent security concerns. The paper contributes to the literature by defining blockchain technology applications and opportunities within the education sector.

The cyber security education market has grownup exponentially, with a CAGR of 13.9 % as reported by Data Intelo. The report published by the World Economic Forum 2023 indicates a shortfall of 2.27 million cyber security experts in 2021 across different roles and hence manifest that Skill-based cyber security education is the need of the hour. Cybersecurity as a field has evolved as a multi-discipline, multi-stakeholder and multi-role discipline. Therefore, the need to address formal education with an outcome-based philosophy is imperative to address for a wider audience with varied past training in their formal education. With the Internet becoming an essential part of human life, providing security of data passed over the Internet is becoming increasingly crucial. Therefore, the role in the organization which is quite demanding is to have expertise in handling and configuring network security, a subdomain of cyber security as a priority area. The rapid increase in the network attack landscape is constantly demanding monitoring of network attacks as well as a need to promote collaborative R&D and education in the sphere of cyber security due to a shortage of skilled resources. Platform-based education is a potential direction to achieve the objective and address the skill gap required in cyber security. The present research proposes a comprehensive web-based platform that can be used to communicate, collaborate and practice various use cases in the domain of network intrusion detection tools using machine learning algorithms and to evaluate user experience. The proposed platform CySecLearn is a collection of various functionalities and features that ensure experiential learning, will help the learner to develop critical thinking and expertise in network security and promote digital literacy in the domain of cyber security.

An organization's infrastructure rests upon the premise that cybersecurity professionals have specific knowledge in administrating and protecting it against outside threats. Without this expertise, sensitive information could be leaked to malicious actors and cause damage to critical systems. In order to facilitate this process, the presented work addresses the use of Infrastructure as Code (IaC) and DevOps to automate the deployment of cyber ranges. An approach closely related to virtualization and containerization as the code's underlying infrastructure helps lay down this burden. Notably, placing emphasis on using IaC tools like Ansible eases the process of configuration management and provisioning of a network. Lastly, several up-to-date vulnerabilities that are constantly messing with the lives of individuals and organizations are explored, most related to Privilege Escalation, Remote Code Execution attacks, and Incident Forensics, allowing the improvement of skills concerning Red team and Blue team scenarios. In short, one of the key takeaways of this work is contributing to better prepare specialists in ensuring that the principles of the National Institute of Standards and Technology (NIST) Cybersecurity Framework hold, namely: prevent, detect, mitigate, and recover.

The digitalisation and datafication of education has raised profound questions about the changing role of teachers' educational expertise and agency, as automated processes, data-driven analytics and accountability regimes produce new forms of knowledge and governance. Increasingly, research is paying greater attention to the significant role of digital intermediaries, 'in-between' edtech or State authorities and the classroom itself, in educational transformations. School data infrastructures, understood as comprising diverse sociomaterial elements including teachers, data, software, standards and pedagogical practices, is one such intermediary through which teacher expertise and agency is reconfigured. In this paper, I focus on teachers' involvement in processes of data infrastructuring in which people, platforms, systems and tools come together to create, enable and maintain data flows. Drawing on a sociomaterial ethnography of a secondary school in England, I analyse the work of a school data office in the behind-the-scenes work of data infrastructuring. The findings detail the significant labour and expertise involved in data infrastructuring, the dynamic, expanding and bespoke nature of the school data infrastructures that emerged, and processes of decontextualising and recontextualising numbers. The paper argues that the work of data infrastructuring undertaken by and through the school data office was an intermediary process which worked to both de-professionalise and re-professionalise teachers in new ways. In the process, this created new kinds of educational data experts and expertise, who gained significant influence and power within and beyond the school, both challenging and reinforcing existing organisational and governing power flows.

Simulation-based learning (SBL) offers an extensive variety of chances to practice complex computer and networking skills in higher education and to implement diverse kinds of platforms to facilitate effective learning. Utilizing visualization and computer network simulation tools in teaching computer networking courses has been found to be useful for both teachers and learners. However, little effort has been made to assess the status of this research area and investigate the factors that influence students' perceptions and intentions to use simulation-based learning. Therefore, this study performed a Systemic Literature Review (SLR) to analyze studies of simulation-based learning and utilized a factor derivation method to recognize and categorize the factors derived from students' perceptions of simulation tools in education. Moreover, this study conducted bibliometric techniques to investigate SBL by analyzing scientific publications, the geographical distribution of articles, the co-occurrence of authors' keywords, and the Cite score per year for each article. The study considered Scopus-indexed SBL articles published between 2012 and April 2023. VOSviewer software and PRISMA protocol were employed for bibliometric descriptive analysis and data analysis. The results obtained from the SLR indicate that Cisco Packet Tracer is the most commonly used tool in simulation-based learning for teaching computer networks. Furthermore, the results demonstrate that perceived ease of use, perceived usefulness, and behavioral intention, are among the most indicated factors from the review which influence students' perception of simulation-based learning tools. The bibliometric analysis revealed that the USA is the leading country in SBL. Additionally, simulation-based learning was the most frequently used keyword in the abstract, keywords, and literature. This study provides the theoretical groundwork for forthcoming empirical studies and helps to understand the advantages of using simulation-based learning tools in teaching and learning.

Effective research data management (RDM) is essential to modern scientific investigations. As the volume and complexity of research data increase, researchers, research institutions, and countries are pressured to improve data management practices to ensure transparency, reproducibility, sharing, and reuse of their findings. Researchers and institutions in Kenya, like those in many other developing countries, have begun to adopt the practice. This review examines the early indicators of improved research data management practices in Kenya to identify leaders who would drive the culture of RDM and thus improve research output.

This paper introduces a Patron Counting and Analysis (PCA) system that leverages Wi-Fi-connection data to monitor space utilization and analyze visitor patterns in academic libraries. The PCA system offers real-time crowding information to the public and a comprehensive visitor analysis dashboard for library administrators. The system's development was driven by the need for occupancy restrictions during the pandemic, ensuring a spacious environment for library visitors as well as balancing between efficient utilization and adhering to social distancing regulations. Traditional methods of patron behavior performance and library spatial analysis, such as manual head counting or card-swiping systems, often incur additional costs for labor, hardware installation, or software subscription. The PCA system, however, utilizes existing Wi-Fi-connection data, providing a cost-effective solution to represent patron demographics and spatial usage. Limitations may arise when patrons do not carry Wi-Fi-enabled devices or during periods of low Wi-Fi service functionality. Implemented in Node.js and integrated with Python Flask framework and related libraries, the PCA system was piloted at the King Library in Miami University, successfully demonstrating a high validity compared to manually collected data. It filters out noise and redundancy, visualizes the occupancy index meter in real time, and generates statistical reports by linking user IDs with demographic information. The PCA system's reliability was validated through manually head counting data collected at the King Library in Miami University, establishing it as a reliable tool for library space management and patron analysis.

The Internet of Things (IoT) is a network of objects that can exchange data with other devices also connected to the Internet. One of the most common consumer examples of IoT is home automation, as a variety of smart devices, including doorbells, lightbulbs, thermostats, and refrigerators are now available which users can control remotely using mobile apps or smart speakers. In this hands-on activity, students will apply their basic skills in accessing wireless networks and using mobile devices to connect an Amazon Echo smart speaker to a home network, configure smart plugs to communicate with the Echo, and develop routines to interact with the smart plugs, smartphones, and other smart devices.

Individuals with intellectual and developmental disabilities (IDD) continue to experience disparities in health and well-being despite improved provisions of person-centered care. Patient-centered outcomes research (PCOR) translates evidence into practice for meaningful outcomes. This piece describes findings from an environmental scan and stakeholder outreach to identify and prioritize opportunities to enhance IDD PCOR data infrastructure. These opportunities include developing a standardized research definition; advancing data standards for service systems; improving capture of IDD at point of care; developing standardized outcome measures; and encouraging Medicaid data use for IDD research. Within this piece, we discuss the implications of addressing data gaps for enhanced research. While the identified activities provide a path towards advancing IDD PCOR data infrastructure, collaborative efforts between government, researchers, and others are paramount.

This article provides an account of the making of KBLab, the data lab at the National Library of Sweden (KB). The first part discusses the work involved in establishing a lab as both a physical and a digital site for researchers to use digital collections at previously unimaginable scales. The second part explains how the lab has deployed the library's collections as data to produce high quality Swedish AI models, which constitute a significant new form of digital research infrastructure. We situate this work in the context of uneven AI coverage for smaller languages, and consider how the lab's models have contributed to the making of important AI infrastructure for the Swedish language. The conclusion raises the possibilities and challenges involved in continuing this type of library-based AI development.

Seeking to better understand the longitudinal association between online usage of library-licensed content and short- and long-term student performance, we linked EZproxy logs to institutional university data to study how library usage impacts semester and cumulative GPAs. Panel linear mixed effects regression models indicate online library usage is significantly associated with both semester and cumulative GPAs. The library usage effect is larger for semester GPA, and varies by on- and off-campus residency. The effect on semester GPA is larger for off-campus students, while for cumulative GPA the effect is larger for on-campus students. Longitudinally linked library-institutional data offers key insights on the library's value.

With the growth in digital teaching and learning, there has been a sharp rise in the number of cybersecurity attacks on K-12 school networks. This has demonstrated a need for security technologies and cybersecurity education. This study examined security technologies used, effective security practices, challenges, concerns, and wish list of technology leaders in K-12 settings. Data collected from 23 district websites and from interviews with 12 district technology leaders were analyzed. Top security practices included cloud-based technologies, segregated network/V-LAN, two-factor authentication, limiting access, and use of Clever or Class Link. Top challenges included keeping users informed, lack of buy-in from staff and decision-makers, lack of expertise to implement modern best practices, and cost of resources. Top concerns included possible cyberattacks, leaked student data, and lack of user awareness. Finally, their wish list included technology personnel, access to Clever of Class Link, external system diagnostic checks, professional development for staff, and replacing aging infrastructure. The findings have implications for K-12 administrators, technology leaders, and teachers.

It is critical for nations to have trained professionals in network security who can safeguard hardware, information systems, and electronic data. Network security education is a key knowledge unit of the National Centers of Academic Excellence in Cybersecurity and various information systems security curricula at the master's and bachelor's levels in higher education. Network security units are components of computer science curricula in high school contexts as well. Educators who teach these concepts play a significant role in developing a skilled workforce of network security experts for both governmental and non-governmental organizations. Understanding the necessary knowledge and skills of network security educators serve to better inform institutes of higher education, educator preparation programs, and others who support educators in the field. This study describes knowledge constructs of a higher education faculty member who teaches networking and network security and was developing, and piloting innovative network security curriculum embedded in both undergraduate and graduate courses. Data were transcripts of recorded monthly meetings with the educator, fieldnotes taken during the meetings, and course artifacts. Existing teacher knowledge frameworks that have been applied in both K-12 and higher education contexts were used to deductively code the data. Examples of curricular knowledge and pedagogical content knowledge specific to the teaching of network security are provided. The affordances of using engagement within curriculum development to understand educator knowledge constructs and the existing teacher knowledge frameworks as tools for analyses are highlighted.

Green internet of things is important to achieve atmospheric decarbonisation, it is crucial to implement procedures and practices that prioritise resource conservation and environmental protection. However, the growing use of internet of things devices poses a challenge due to their high-energy requirements for data reception and transmission which often leads to rapid battery drain, necessitating frequent battery replacement and consequently these discarded batteries often end up in landfills, causing adverse environmental impacts. This paper examines the environmental consequences of IoT devices' energy consumption and battery disposal and also explores potential solutions and strategies to mitigate these issues. This paper reviews two methods, which have proven useful in measuring energy usage. The study emphasises the importance of adopting sustainable practices in the design, usage, and disposal of IoT devices to minimise their ecological footprint and promote a greener future.

The interactive mechanism between social and concept networks is a key question in connectivist learning, which explains the impact of interaction on cognitive development and knowledge generation. The successful practice of "Internet Change Education: Dialogue between Theory and Practice", the first cMOOC in China, provides data support and research context for exploring the learning rules. This study proposed an evaluation framework of individual social network status in cMOOCs and a model for concept network characteristics analysis in cMOOCs. Analysis from 10,598 interactive data points of cMOOC1.0 using complex network analysis, topic clustering algorithm and correlation analysis found that there was a correlation between a learner's individual network status and concept network characteristics, and there are two kinds of special connectivist learners in cMOOC learning: someone with higher network status but lower knowledge output, and someone with higher knowledge output but weaker network status. Furthermore, we put forward three practical suggestions: (1) facilitators should focus on guiding learners' expression and connection to important individuals; (2) according to different correlation trends, facilitators can flexibly tailor activity design strategies, such as providing additional wayfinding support for learners with low centrality; and (3) carry out adaptive learning evaluations and design diversified certificates.

Intangible cultural heritage is an important part of Chinese excellent traditional culture, and college dance teaching is paid more attention by researchers of physical education and computer technology. In order to help the inheritance and development of non-legacy culture in college dance teaching, this paper analyzes the influencing factors of wireless communication network in college dance teaching, constructs an interactive platform for non-legacy digital dance teaching based on wireless communication network technology, and applies it in the dance teaching process of a university in Henan province to highlight the role of wireless communication technology in dance teaching. The results show that the interactive platform can effectively reduce teachers' physical energy consumption and has certain reliability and practicality. Through artificial intelligence algorithm, the traditional dance teaching method has been changed, and a new exploration of non-legacy dance teaching has been realized.

This research evaluates the efficacy of a basketball-based teaching and training system supported by 5G technology in a wireless network environment. Initially are information about the Chinese basketball students is first gathered and then divided into a Control Group (CG) and an Experimental Group (EG). The control group uses the standard method of collegiate basketball instruction, while the experimental group learns the game under the background of 5G technology. For transmitting the basketball teaching data in the 5G network, we proposed a novel routing protocol named Probability-based Coupling Zone Routing Protocol (PbCZRP). An optimization technique called the Shark optimization approach is used to enhance the performance of the routing protocol. Finally, a comparison of the two groups reveals that the experimental group's basketball players fared better than the control group. The basketball training plan powered by 5G will supply students with adaptive learning services that take into account their individual needs and strengths.

Higher education is becoming increasingly competitive and all educational institutions are concentrating on improving quality and changing traditional higher education teaching methods. New-type classroom instruction has embraced a unique advancement opportunity with the arrival of the fifth generation (5G) era. It is critical to develop a teaching assistance system that makes use of high-speed network methodology and new-type display methodology. For the innovation and reform of higher education, this article combines soft computing techniques, artificial intelligence (AI), and 5G networks. This paper outlines the exact processes and measures for incorporating "5G" technology into higher education. Finally, conduct a comparative experiment to see how good the system is at learning AI knowledge when compared to standard learning methods. The outcomes of the experiments are examined to show that employing this approach to gain AI knowledge is successful and improves students' enthusiasm in learning as well as their hands-on abilities.

Based on a brief analysis of the current situation of university education management and research on intelligent algorithms, this article constructs a university education management system based on big data. For the clustering and prediction modules in higher education management, corresponding algorithms are used for optimization design. A fuzzy clustering algorithm based on entropy weight is proposed to address the shortcomings of the C-means clustering algorithm. This algorithm adds weighting coefficients on the basis of improvement and continuously updates the clustering centers. The prediction module uses Apriori algorithm to map and compress the target transaction database, reduces the number of candidate item sets through pruning process, and designs simulation experiments to measure the performance of the algorithm. The simulation results show that the clustering results of this algorithm are closer to the actual clustering situation, with shorter running time and better algorithm performance.

In the context of the multimedia era, college counselors and college students should make progress together. This article aims to explore the practical issues of applying multimedia and visual-image technology to the training of college counselors. We propose a three-dimensional multimedia visual image recognition technology based on convolutional neural networks (CNNs) and apply the algorithm to image-recognition tasks to provide support and assistance for college-counselor training in network and multimedia environments. By combining a CNN with image recognition, our research results show that this method can effectively adapt to different types of image-recognition tasks. This means that our algorithm can be fully applied to these tasks and provide strong support for the training of college counselors.

This paper employs BP Neural Network (BPNN) theory to evaluate innovation and entrepreneurship education in universities. It utilizes students' evaluation indexes as input vectors and determines the number of hidden layer neurons. Experimental results serve as output vectors. The BPNN method proves reasonable and feasible for vocational education course evaluation, exhibiting a 14.96% higher accuracy than traditional genetic algorithms. The paper discusses the model, configuration, characteristics, training process, algorithm enhancement, and limitations of neural networks, followed by an introduction to genetic algorithms. Through analysis of principles, basic operations, and common operators, it establishes a theoretical foundation for subsequent discussions.

Purpose: Inclusive growth in the education sector is still a major challenge in some countries because of limited access to technologies and internet connectivity, among other reasons. However, as a technology, augmented reality (AR) is expected to be widely used in the field of education in the future. The main purpose of this paper is to explore the use of AR for inclusive growth in education as well as identify the challenges, particularly in countries like India and Tanzania. Design/methodology/approach: This paper applies a systematic literature review by analysing and synthesising relevant documents, mainly journal articles, books and conference papers. Descriptive statistics and cross-tabulation were used for the analysis. Content analysis was used to evaluate the contents of the reviewed literature. Findings: For the use of AR, it is important to have adequate digital infrastructure, access to universal internet or broadband facilities and the digital empowerment of citizens. Major challenges to inclusive growth in education include the lack of trained teacher educators and students' preference for practical or project-based curriculum. Practical implications: Practitioners in both countries may consider the use of AR for inclusive growth in education. Originality/value: This paper specifically examines the use of AR in higher education and the related challenges based on a review of two countries, namely India and Tanzania.

Purpose: This paper evaluated the effectiveness of blended learning of business courses in higher learning institutions (HEIs) in developing economies. Design/methodology/approach: A survey, involving 215 learners, was used to collect data. A stratified sampling technique was used in this study. The data were analyzed using the PROCESS macro in SPSS. Findings: In the blended learning approach, student attitudes, social presence, IT infrastructure and flexible learning are all favorable predictors of learner satisfaction. The impact of blended learning on learner satisfaction is further mediated by IT infrastructure, social presence and learner attitude. Practical implications: HEIs need to invest in planning and resource mobilization in order to realize several benefits derived from the use of blended learning. For optimal learning outcomes, this should be combined with training on IT infrastructure usage for both facilitators and learners. In order to assist learners in developing competencies through consistent use, institutions should also invest in tailored blended learning technologies. In addition, emphasis should be placed on training all actors in order to better manage change. Originality/value: This paper presents and ranks several dimensions for blended learning success in low-budget universities. In addition, the study contributes to the understanding of intervening variables necessary for enhancing the potential of pedagogy in maximizing learner satisfaction.

The COVID-19 pandemic sparked an unprecedented expansion of educational technologies and digitisation of the university sector, and also amplified existing inequalities and crises. In this paper, we introduce the 'socio-technically just pedagogies framework' to systemically explore curriculum-making, student-staff partnerships, knowledge production, and networked capabilities in higher education. This conceptual innovation seeks to (re)articulate pedagogy across four aspects: (i) a commitment to curriculum-making as a form of everyday activism; (ii) a nurturing of student-staff coalitions to expand student-staff partnerships; (iii) development of generative spaces for transdisciplinary co-creation; and (iv) the deliberation of networked capabilities. This framework emerged from a partnership with students at an Australian university that sought to experiment with pedagogical practices and possibilities. Our coalition then responded to the framework to illicit collective insights about the curriculum-making phenomenon. The framework seeks to articulate curriculum-making initiatives that collectively enact socio-technically just pedagogies.

Qualitative research has been strongly affected by the COVID-19 pandemic, highlighting the possibilities that Voice over Internet Protocol (VoIP) technologies such as Skype, WhatsApp, and Zoom offer to qualitative scholars. Based on the experience of using such technologies to collect qualitative data for our PhD studies, we present how we dealt with the challenges of this interview mode. Precisely, we discuss problems related to rapport, technology, digital exclusion, and ethics frequently pointed out in the methodological literature on online interviews. Thereby we put forward strategies and techniques that helped us to 1) build a rapport, 2) manage technical difficulties, 3) reflect on risks of digital exclusion, and 4) comply with the ethical standards of our institution. In doing so, we draw on our qualitative data to support the arguments. The aim of this paper is, thus, to deepen the methodological debate on online interviews in social sciences.

Modern life is increasingly influenced by networks, making cybersecurity a crucial area of study. However, due to their few resources and varied makeup, they are more vulnerable to a wide range of cyber-attacks. Such risks result in sensitive information being stolen as well as financial and reputational harm to firms. How far malicious detection techniques have advanced in the intrusion detection system (IDS) industry is difficult to quantify. Therefore, a unique IDS known optimized Artificial Intelligence approach is designed to effectively identify the intrusions. The preprocessing activity is initially carried out to improve the data quality for identifying network intrusions utilizing normalization and standardization. The Corporate Hierarchy optimization (CHO) technique is then used to choose the important features from the databases. By accurately identifying intrusions, the suggested golden eagle optimization-based Self-constructing Multi-layer Perceptron Interfaced Fuzzy system (GEO-SMPIF) solution improves privacy and security within the professional network infrastructure. The ensuing hyperparameters are adjusted optimally using GEO methods during parameter identification, and a backpropagation technique tunes the precondition parameters. Using datasets of NSL-KDD and UNSW-NB15, the Python platform creates the experimental setup. When compared to existing approaches, the analysis's findings show that the suggested method performs better at identifying intrusions with prediction performance in terms of a 99.78% of high detection rate, 99.99% of high accuracy, and 0.04 less false alarm rate in NSL-KDD and 99.70% of high detection rate, 99.97% of high accuracy and 0.065 of less false alarm rate in UNSW-NB15 dataset.

The objective of this study was to analyze the gap in expected benefits and actual benefits of virtual classrooms used at the time of nationwide lockdown for the teaching-learning process for faculty members and students in higher education during the COVID-19 pandemic. A total of 893 responses have been used for this study. The overall mean of expected benefits, from 305 faculty members and 588 students of higher education institutes/colleges/universities, is higher than the overall mean of actual benefits and that difference value is 0.250055, with a Sig. (2-tailed) value of 0.036 which is less than 0.05 for faculty members and 0.3872827, with a Sig. (2-tailed) value of 0.000 which is less than 0.05 for students. We found that the network connectivity was the major challenge faced by the faculty members with a mean value of 3.68 followed by a 3.17 mean value for lack of professional environment at home, 3.03 for lack of teaching material at home, 2.92 for lack of personal computer/laptop. From students' responses, we found the lack of a professional environment at home with a mean value of 3.59 was the major challenge faced by the students followed by 3.57 for lack of teaching material at home (for lack of printed teaching- learning material at home), and 3.35 for network connectivity, 3.31 for lack of personal computer/laptop. The moderation effects of challenges between expected benefits and actual benefits is found significant for faculty and students both. The moderation effects of challenges between expected benefits and actual benefits is found significant for faculty ([beta]_ Expected Benefit_Challenges = -0.110, p < 0.05) and students ([beta]_ Expected Benefit_Challenges = -0.0.094, p < 0.05) both. The faculty members and students both were able to perceive higher actual benefits due to the low challenges of virtual classrooms. Further, the faculty members and students both were able to perceive lower actual benefits when challenges are more. The policymakers of higher education must work to resolve the issues and challenges of virtual classrooms to improve the effectiveness of the virtual classroom. The post-COVID higher education may require a continued focus on flexibility, adaptability, technology integration, student engagement, equity, and well-being. By prioritizing these areas, institutions can create a resilient and inclusive learning environment for their students and faculty in the post-pandemic era. the COVID-19 pandemic has highlighted the critical importance of organizational learning in responding to crises. Organizational scholars can contribute by advancing knowledge on effective learning patterns, documenting best practices, and incorporating these lessons into teaching and practice. By doing so, we can help organizations be better prepared for future crises, including pandemics, and ensure that the lessons learned are not forgotten. post-COVID higher education may require a continued focus on flexibility, adaptability, technology integration, student engagement, equity, and well-being. By prioritizing these areas, institutions can create a resilient and inclusive learning environment for their students and faculty in the post- pandemic era. It's important to note that effective online instruction often involves a combination of different learning theories, depending on the nature of the content, the goals of the instruction, and the characteristics of the learners. Online instructors should consider how these theories can inform their instructional design and delivery to create meaningful and effective online learning experiences. learning theories have a significant impact on the performance of higher education institutes in the context of online education. By aligning instructional strategies, course design, assessments, feedback, and learner support with learning theories, higher education institutes can optimize their online education programs and enhance student performance. the pandemic has necessitated the use of various teaching strategies in higher education institutions to adapt to remote and online learning. Blended learning, technology-enhanced instruction, student-centered approaches, flexible assessments, active learning strategies, and social-emotional support are some of the most appropriate teaching strategies that have been used during the pandemic to support student learning and engagement. It is important for instructors to continually assess and adapt their teaching strategies based on student needs and feedback to ensure effective learning outcomes.

Technology is advancing and metaverse is gaining popularity. The magic of metaverse is beyond our imagination. In simple terms, the metaverse refers to a virtual shared space that exists online, where people can interact, socialise, work, and play using digital avatars, just like they do in the real world. It is a combination of virtual reality, augmented reality, and the internet, all rolled into one immersive environment. Virtual reality (VR) immerses users in entirely computer-generated environments through headsets, while augmented reality (AR) overlays digital information onto the real world, enhancing the user's perception. This paper introduces new strategies to bring healthcare into the metaverse by providing solutions to the hurdles that have kept us from exploring this idea. These include reducing data transfer delays in the metaverse, making VR headsets more affordable, accurately predicting diseases by studying symptoms, and creating a platform for medical professionals to practice procedures on avatars before performing them on real patients. Metaverse has immense scope of revolutionising the healthcare and we are yet to unfold its complete usefulness.

A modern technology-supported vocational educational system significantly affects the quality of vocational training and contributes to the innovation and economic development of the regional area. The visualization literature analysis was adopted with the purpose of exploring the theoretical framework for developing a 6G-assisted network to realize the multi-party participation in the modern government-industry-education Integration system. The literature review showed the network should involve all cooperation entities into the communication system to intensify all coordination guided by the triple helix theory, should be strong enough to store all kinds of resources to support the optimized sharing, be efficient to track student training processes and learning data to provide scientific evaluation to student development in personal qualities and competencies, be supportive to develop a cooperating culture to form a healthy ecosystem in which all enterprises actively participate and invest in vocational education.

Information Technology (IT) skills gap discourse suggests a mismatch between what students are acquiring in terms of knowledge and skills in their education versus what employers believe are useful skills for doing day to day tasks. This study builds upon previous research (analyzing the skills of college students in IT-related majors) by surveying industry professionals to determine the skills their organization requires and offering suggestions that can benefit the educational institutions and create a better educated workforce. Implications are drawn and a conclusion is presented.

The freshman student's perspective on the activities performed in a data center by the network analyst is complex and intricate. These activities include the configuration of equipment and the connection between network devices. There are several issues with these activities that demand technical knowledge. Questions such as: "what does this equipment do?"; "How is it connected to another?"; "How is it configured?" can be complicated for beginner students. Moreover, these technical questions are also associated with scalability, availability, security, portability, accounting, and costs. These resources require technical knowledge and also how to aggregate them into a network solution. We applied an abstraction set to mitigate these issues for first-year students and created the Network Analyst Board Game. This board game introduces students to the computer network field geared toward Data Center activities. The objective of this paper is to report this game. The students obtained essential theoretical and practical knowledge regarding computer networks after playing. A quasi-experiment was conducted with a set of students from the computing courses. After these experiments, more interactivity was noted among the students, resulting from the game mechanics applied. Therefore, in addition to increasing their interest in the area, the students elaborated more complex questions. The professors found that, after playing, the students presented more pertinent doubts during classes.

Connectivism, a learning theory that reveals a new learning in the Internet environment, has become a popular academic topic at the forefront of online learning. The MOOC Research Team at the Distance Education Research Centre at Beijing Normal University designed and developed the first massive open online course in China, adapting a connectivist (cMOOC) approach. Using the data collected from six offerings of the cMOOC over 3 years, the big data paradigm was used for data analysis including complex network analysis, content analysis, text mining, behaviour sequence analysis, epistemic network analysis, and statistical and econometric models. This paper summarizes the findings of the patterns of connectivist learning, including a) the basic characteristics and evolutional patterns of complex networks, b) the characteristics and modes of knowledge production, c) the patterns of instructional interactions, and d) the relationships between "pipe" (connection) and content and between facilitators and learners. It is expected that the outcome of this study could make contributions to understanding the changes of online learning in depth and further promote the theoretical development and practical application of a connectivist approach.

Learners have to engage in academically purposeful instructional endeavors to be successful in school. Latest research indicates that the learners of today are not as interested in educational deeds as they need to be. Educational stakeholders should look for means to address this tendency to have a positive influence on educational results. This study explores the instructional practices that play a role in behavioral engagement (also known as involvement) of learners in schoolwork in the Cisco Certified Network Associate (CCNA) program -- an information technology certificate program. Behavioral engagement in this context refers to learners' active learning and collaboration with peers. A two-level hierarchical linear modeling was established to predict behavioral engagement from instructional practices while controlling for certain learner level (expectancy and value motivation, gender, and age) and teacher level (teaching and networking experience) variables. Learners who attended the CCNA program in the United States, totaling 773 high school and community college students, were matched specifically with 149 teachers who taught them. Student and instructor surveys were conducted online to gather data. The results show that the level of learner involvement in the program was poor, equivalent to the national student engagement survey of the period. However, if their teachers used collaborative and learner-centered practices, learners were more involved in schoolwork behaviorally. Learners were also very involved in the program if they placed a high value on the program. Female learners were not as active as male learners. In addition to the two instructional practices implied in this study, another major takeaway is that learners should be advised as early as possible about the detrimental impact of poor motivation in the program.

Hardware security is one of the most researched areas in the field of security. It focuses on discovering and understanding attacks and countermeasures for electronic hardware that provides the "root-of-trust" for modern computing systems upon which the software stack is built. The increasing reliance on electronic devices in our everyday life has also escalated the risks of experiencing security threats on these technologies. Students today are exposed to these devices and thus require a hands-on learning experience to be aware of the threats, solutions, and future research challenges in hardware security. Currently, there are limited opportunities for students to learn and understand hardware security. A significant factor limiting exposure to these topics is the lack of an accessible, low-cost, flexible, and ready-made platform for training students on the innards of a computing system and the spectrum of security issues/solutions at the hardware-level. In this paper, we introduce the motivation and efforts behind a course named "Hands-on Hardware Security." The Department of Electrical and Computer Engineering at the University of Florida has been offering this course for the past three years in providing experiential learning of hardware security through a set of well-designed experiments performed on a custom hardware module. We also present, in detail, the idea of a custom-designed, easy-to-understand, flexible hardware module with fundamental building blocks that can emulate a computer system and create a network of connected devices. We refer to the module as "HaHa SEP" (Hardware Hacking Security Education Platform), and it encourages students to learn and exercise "ethical hacking," a critical concept in the hardware security field. It is the first and only known lab course offered online, where students can perform ethical hacking of a computing system using a dedicated hardware module. This paper also provides a brief introduction to the experiments performed using this module, highlighting their significance in the field of Hardware Security. Finally, it concludes with a compilation of course evaluation survey results discussing the success of this course in engaging students' interest in the subject matter and determining the accomplishment of maintaining a balance between their expectation and the effort required towards the course.

Any academic from an overrepresented group who advocates more "diversity" is directly contributing to the lack of "diversity" by remaining in his position. Assuming the number of jobs is relatively fixed, such an individual is effectively saying, "I want the percentage of academics who have the same demographic characteristics as me to go down, but I am not willing to give up my job in order to achieve that goal. Rather, I want other academics with those demographic characteristics to give up their jobs, or to lose job opportunities." In this article, Noah Carl argues that this is not a principled stance. Academics from overrepresented groups who are in favor of more "diversity" have an obligation to resign, and they should continue to fulfil this obligation until the demographic composition of academia matches the demographic composition of the general population.