Search

This research goal to develop a multiple-choice closed-ended test to assessing and evaluate students' digital literacy skills. The sample in this study were students at MTsN 1 Blitar City who were selected using a purposive sampling technique. The test was also validated by experts, namely 2 Doctors of Physics and Science from Yogyakarta State University. The test instrument was developed based on five aspects of digital literacy skills: information, communication, content creation, security and problem-solving. Data have been analyzed descriptively and inferentially using the Rasch version and the assist of Quest software. The results showed that eight multiple-choice closed-ended test instruments were declared valid based on expert validation with an Aiken V value of 1.00. The reliability result is 0.97 with a very high category, and the INFIT MNSQ standard deviation value is 0.86-1.16, so seven items are by the Rasch model. Thus, the seven items in the multiple-choice closed-ended test instrument can be used to assessing and evaluate students' digital literacy skills in learning science.

The metaverse which is considered as the digital big bang of humanity and the next evolution of the internet is anticipated to offer a living environment for civilization 5.0 and beyond in various domains including education. Each novice technology that enters our daily lives generates also fear, anxiety, and problems as well as hope, benefit, and attraction. The purpose of this research is to investigate what ethical problems the metaverse may cause in higher education institutions and how healthy metaverse universities can be created within the framework of ethics. Interpretative phenomenological research design was employed in the study and data was collected from the field experts and lecturers in higher education. The study indicated thirteen VR/AR/XR experts' and lecturers' visions on the metaverse-based ethical issues and practical implications that could be applied within the scope of five thematic nodes comprising metaverse awareness, security and data, safety and wellness, social equality and diversity, and accessibility. It is expected that the study will contribute to the design of a healthy and good metaverse in the future of higher education institutions pursuant to ethical values.

The purpose of this study was to investigate the ethical tendencies of medical faculty students, their unethical use of information and communication technologies, and their attitudes toward digital ethics in terms of certain variables. The study was designed using a relational survey model. The research group consisted of 335 medical faculty students studying at a state university in Turkey. Data were collected using the "Personal Information Form," the "Ethical Tendencies Scale," Information and Communication Technologies Ethics Scale," and "Attitude towards Digital Ethics Scale." The data analysis revealed that medical faculty students' digital ethical attitudes and ethical tendencies were at a high level and positive, while their unethical use of information and communication technologies was at a very low level. The study's findings indicated that there were gender-related differences in medical students' unethical use of ICT. In addition, there were significant differences in the ethical tendencies of the participating students based on the variable of year of study. Lastly, medical students' unethical use of information and communication technologies were significantly affected by their ethical tendencies and attitudes towards digital ethics.

Social network sites, most notably Facebook, have fundamentally transformed the way information is transferred, received, and shared by individuals and organisations. This article explores the diverse contexts in which Facebook is utilised as a knowledge-sharing instrument, along with the key challenges encountered in adopting Facebook as a knowledge-sharing instrument. It also indicates the gaps in adopting Facebook as a knowledge-sharing instrument. In a systematic literature review, 400 articles accomplishing the research objectives were identified. The findings revealed that Facebook can be used in different contexts. Greater awareness of Facebook's versatility as a platform for knowledge sharing across various domains is recommended. This article also advises that the challenges related to cost, time investment and technical expertise be addressed, and emphasises the need for education and training.

The use of online homework systems that require the purchase of an access code has become widespread. The purpose of this study is to examine student experiences with and perceptions of online homework systems with access codes. Postsecondary students (N = 966) completed a survey about the financial costs, perceptions of quality, engagement with, and learning with online homework systems. Most students (79.5%) indicated that they had been required to purchase an access code for an online homework system. Of those who had been required to purchase an access code, 29.4% reported their grade was hurt because they could not afford an access code. Students reported online homework systems were moderately helpful for learning. When considering students who have been historically underserved by higher education, Black students reported more courses with required access codes for homework and reported that online homework systems were more helpful than other students. Latino/a/x students were more likely to report their grades were hurt by not affording access codes (47.9%) than other students. First-generation students reported they avoided courses with online homework systems (36.9%) more than continuing-generation students (23.9%). Overall, the findings indicate that the cost of online homework systems is a barrier to education, and alternatives should be further developed and promoted.

Studies on digital rights in education have both gained attention and provided a framework for research, policy and practice in educational research within the field of educational technology. The potential benefits we appreciate in Internet use are inseparable from the maximum risks involved. Faced with this responsibility, individuals demand that their rights and freedoms be guaranteed in the digital environment according to their various roles as students, teachers, families or staff. This scoping review selects and analyses 54 theoretical and empirical studies from the last decade (2013-2023), identifying the main topics investigated as privacy protection in online environments, right to digital security or cybersecurity, and right to digital education. The review underscores the need to guide efforts towards digital education for citizens because the legal regulation of rights and responsibilities is necessary but insufficient. The paper also makes arguments about acceptance, limitations and implications for teacher training.

Artificial Intelligence (AI) has emerged as a prominent area of investigation in the field of education. Also, perceptions, challenges and threats of AI among university professors show notable variations. This study explores university professors' perspectives regarding AI, including their familiarity with AI, its educational impacts, challenges associated with its implementation, and perceived threats. To achieve this, a survey was administered to 65 university professors from diverse Egyptian institutions, both state and private. Subsequent statistical analyses were conducted to treat the collected data. The outcomes of these analyses reveal that university professors possess varying degrees of familiarity with AI. Despite this, they view AI as a valuable educational tool. The study identifies several challenges hindering AI adoption, encompassing difficulties in comprehending and interpreting AI algorithmic outcomes, the intricate autonomy of AI systems, financial implications of implementation, and concerns regarding data privacy. Additionally, the study identifies apprehensions pertaining to AI''s influence on professors' skills, potential dehumanization of pedagogy, adverse effects on students, and the potential obsolescence of professors. These findings bear implications for the integration of AI in educational contexts, highlighting the necessity for further exploration in this evolving field.

The use of commercial digital platforms in public schools like Google and Microsoft, which was exacerbated during the pandemic, requires analysis to encourage a safer and more appropriate educational use. The research objective behind this article was to analyse the concerns of school students in obligatory primary and secondary education in public schools within the Autonomous Region of Catalonia (Spain) together with the opinions of their families regarding the use of digital platforms offered by large technology companies (BigTech) in schools. This is a mixed design study, consisting of eight discussion groups with pupils (n = 56) and a questionnaire issued to 2,330 family members. The results show that both students and families are concerned about the lack of knowledge surrounding the data they generate when using these digital platforms, and their effect on democratic school governance and the reproduction of gender stereotypes. In conclusion, the study suggests it is necessary to create greater critical awareness among children, adolescents and families at all socio-economic levels, particularly in those who are most vulnerable.

This review explores the integration and effects of the Internet of Things (IoT) in education, highlighting its importance in transforming traditional teaching and learning techniques. It examines the early uses and historical growth of IoT, its development, and the turning points in its adoption. It explores IoT platforms, tools, and technologies in education, including wearables, smart devices, augmented and virtual reality, gamification, and collaborative learning. It discusses the role of IoT in improving campus management, including intelligent campuses with IoT-enabled infrastructure, energy-saving technologies, and safety and security improvements. The study discusses data security and privacy issues in IoT installations and the ethical and legal implications of data collection in the classroom. The study also discusses upcoming trends and prospects for IoT usage in education, including AI and machine learning integration. Finally, the review provides insights for educators, decision-makers, and stakeholders, identifying research gaps and recommending areas for future IoT implementation.

Artificial intelligence in education (AIEd) is a fast-growing field of research. In previous work, we described efforts to explore the possible futures of AIEd by identifying key variables and their future prospects. This paper re-examines our discussions on the governance of data and the role of students and teachers by considering the implications of (1) a recent case related to the General Data Protection Regulation (GDPR) and (2) the release of ChatGPT, a generative AI model capable to producing 'human-like' text. These events raise questions for the future of AIEd and the underlying function of assessment, and highlight the importance of active student participation in the integration of AI in education. [This article has been presented in the 5th International Open & Distance Learning Conference-IODL 2022.]

This study investigated the digital existence of the food bank users in a university town in Texas, and subsequently, aligned with the research's pragmatic focus, the researchers designed a training model for these food bank users. Two research questions guided the study: What are the digital existence levels of the food bank users, and what training model would best serve these food bank users? Data were collected by means of a survey from 230 individual food bank users representing households. Additional data included observations and conversations with food bank staff, and documents and materials from the site which provided deeper insights. The study found that the food bank users (1) had little to no broadband connectivity; (2) possessed limited digital devices which revealed significant barriers to their digital existence; and (3) had feelings of desperation, vulnerability and isolation. Regarding training offered at no cost, the food bank users did not show much interest, which was attributed to the food bank users' insufficient digital knowledge. The three-level training model was designed with the following objectives: (1) Prepare participants for training; (2) introduce the concept of "digital;" and (3) teach basic computing and cybersecurity skills. To implement this training, an interactive learner-centric model was created demonstrating collaboration among university instructors, volunteer students and the food bank staff. The study concluded that to exist in digital societies affordable broadband connectivity, needs-based devices, and continual support and training were needed for such underserved groups.

Generative artificial intelligence (AI) tools were met with a mix of enthusiasm, skepticism, and fear. AI adoption soared as people discovered compelling use cases--developers wrote code, realtors generated narratives for their websites, students wrote essays, and much more. Calls for caution attempted to temper AI enthusiasm. Experts highlighted inaccuracies in some of the generated information. Artists, writers, programmers, and other professionals who create for a living questioned their job security. Educators worried that these tools would harm academic integrity. Nevertheless, the tools persist, and AI enthusiasm shows no sign of abating. The current study focuses on how AI tools can be leveraged to improve self-directed learning in the classroom. In a capstone cybersecurity course, the instructor encouraged students to use ChatGPT 3.5 on a self-directed learning assignment to select topics, find learning resources, and carry out their learning plans. Some students did not use ChatGPT. Those who used ChatGPT found it to be a helpful learning aid. All students reported that they plan to use ChatGPT for self-directed learning after graduating. No student violated academic integrity policies. The results demonstrate that AI tools can enhance self-directed learning, though students should be trained to use them effectively. Recommendations for developing assignments that support academic integrity and rigor in the age of AI are provided.

The role of ethics becomes even more significant given the huge advent and increase of cyber-criminal activities in cyberspace. It has become an urgent necessity to curb the menace of unethical practices in cyberspace and contribute ethical guidelines to a safe and secure digital environment. To minimize the growth of cybercrimes and unethical issues online, users must understand how existing societal norms and ethics can be extended according to the challenges posed by ethical dilemmas in cyberspace. Hence, understanding the importance of cyber ethics in daily life has become essential than ever before. Cyber ethics implies the rules of social engagement and responsibility in cyberspace; it is really about social responsibility in cyberspace and it is aimed at inculcating knowledge of responsible behavior in man when using the online environment. This paper is an attempt to provide an overview of the relevance of cyber ethics education in fostering responsible behavior online.

Educational data mining has allowed for large improvements in educational outcomes and understanding of educational processes. However, there remains a constant tension between educational data mining advances and protecting student privacy while using educational datasets. Publicly available datasets have facilitated numerous research projects while striving to preserve student privacy via strict anonymization protocols (e.g., k-anonymity); however, little is known about the relationship between anonymization and utility of educational datasets for downstream educational data mining tasks, nor how anonymization processes might be improved for such tasks. We provide a framework for strictly anonymizing educational datasets with a focus on improving downstream performance in common tasks such as student outcome prediction. We evaluate our anonymization framework on five diverse educational datasets with machine learning-based downstream task examples to demonstrate both the effect of anonymization and our means to improve it. Our method improves downstream machine learning accuracy versus baseline data anonymization by 30.59%, on average, by guiding the anonymization process toward strategies that anonymize the least important information while leaving the most valuable information intact.

This paper reviews cybersecurity laws and regulations in Cameroon, focusing on cybersecurity and information security audits and risk assessments. The importance of cybersecurity risk assessment and the implementation of security controls to cure deficiencies noted during risk assessments or audits is a critical step in developing cybersecurity resilience. Cameroon's cybersecurity legal framework provides for audits but does not explicitly enumerate controls. Consequently, integrating relevant controls from the NIST frameworks and ISO Standards can improve the cybersecurity posture in Cameroon while waiting for a comprehensive revision of the legal framework. NIST and ISO are internationally recognized as best practices in information security systems and cybersecurity risk management. This paper highlights the lack of specific international law provisions addressing cybersecurity audits and risk assessments. Overall, the paper highlights the importance of continuous risk assessment and monitoring, implementation of security controls, and compliance with organizational policies, relevant laws and regulations to ensure the adequate protection of information systems. Finally, the paper underscores the importance of improving Cameroon's cybersecurity regulations by integrating provisions from NIST and ISO.

Cyberbiosecurity and workforce development in agriculture and the life sciences (ALS) is a growing area of need in the curriculum in higher education. Students that pursue majors related to ALS often do not include training in cyber-related concepts or expose the 'hidden curriculum' of seeking internships and jobs. Exposing students through workforce development training and hands-on engagement with industry professionals can provide learning opportunities to bridge the two and is an area of growth and demand as the workforce evolves. The objectives of this work were (1) to learn key concepts in cybersecurity, including data security, visualization, and analysis, to name a few, through class activities and engagement with professional partners and (2) to understand what knowledge students gained from participating in the course could transfer over for when they enter the workforce. Three themes emerged from the study where students, through direct engagement with industry partners, gained more insight about the industry applicable to their studies; they established work environment expectations for entering internships and official job placements and established ways in which the workforce development training informed their future careers.

Research indicates that deceitful videos tend to spread rapidly online and influence people's opinions and ideas. Because of this, video misinformation via deepfake video manipulation poses a significant online threat. This study aims to discover what factors can influence viewers' capability to distinguish deepfake videos from genuine video footage. This work focuses on exploring deepfake videos' potential use for deception and misinformation by exploring people's ability to determine whether videos are deepfakes in a survey consisting of deepfake videos and original unedited videos. The participants viewed a set of four videos and were asked to judge whether the videos shown were deepfakes or originals. The survey varied the familiarity that the viewers had with the subjects of the videos. Also, the number of videos shown at one time was manipulated. This survey showed that familiarity with subjects has a statistically significant impact on how well people can determine a deepfake. Notably, however, almost two-thirds of study participants (102 out of 154, or 66.23%) were unable to correctly identify a sequence of just four videos as either genuine or deepfake. This study provides insights into possible considerations for countering disinformation and deception resulting from the misuse of deepfakes.

With the development of technology, security, a core human concern throughout history, has changed and branched out into new areas. Novel security concepts, including environmental security, economic security, and cybersecurity, have emerged as a result of these expanding areas. The importance of cybersecurity has increased in the linked world of today as a result of how prevalent technology is in our daily lives. This study looks at how the literature on international relations approaches the idea of cybersecurity, with an emphasis on the role gender dynamics play. This study adopts a comprehensive strategy in recognition of the possibility that people of all genders may be affected by the dominant gender roles. The study seeks a comprehensive understanding of cybersecurity by utilizing a mixed-methods research methodology that incorporates both qualitative and quantitative techniques. Conducting in-depth interviews with young adults (ages 18 to 27) who identify as people of different genders will be part of the field research. Various aspects of cybersecurity, such as perceptions of cybersecurity, understanding of security, and encounters with cyber dangers, will be covered in these interviews. The research will be carried out in both Turkey and Italy, enabling a comparison of the cybersecurity laws and conditions in these two nations. This study aims to give a fresh viewpoint by combining theoretical underpinnings with empirical fieldwork. The survey data will also be subjected to statistical analysis. The study's findings will shed light on how young adults' perceptions of cybersecurity are influenced by gender norms and what that means for cybersecurity laws. This research contributes to the larger discussion on cybersecurity and gender studies by broadening its focus beyond gender as a binary construct and offering insightful information about how gender roles affect cybersecurity views across various identities.

Cybersecurity has traditionally been perceived as a highly technical field, centered around hacking, programming, and network defense. However, this article contends that the scope of cybersecurity must transcend its technical confines to embrace a more inclusive approach. By incorporating various concepts such as privacy, data sharing, and ethics, cybersecurity can foster diversity among audiences with varying educational backgrounds, thereby cultivating a richer and more resilient security landscape. A more diverse cybersecurity workforce can provide a broader range of perspectives, experiences, and skills to address the complex and ever-evolving threats of the digital age. The research focuses on enhancing cybersecurity education to attract a diverse audience through the development and testing of a virtual platform on Haaukins (a cybersecurity training platform) designed with features resembling social media for capture-the-flag exercises. The results show that the cyber training platform effectively engages a diverse group of learners, bridging the gap between traditional technical boundaries and the urgent demand for comprehensive cybersecurity competence.

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.

Data collection, use, leveraging, and sharing as a business practice and advantage has proliferated over the past decade. Along with this proliferation of data collection is the increase in regulatory activity which continues to morph exponentially around the globe. Adding to this complexity are the increasing business disruptions, productivity and revenue losses, settlements, fines, and penalties which can amount to over $15 million, with many penalties now being ascribed to the organization's leadership, to include the Board of Directors (BoD), the CEO and members of the senior leadership team (SLT). Thus, boards of directors can no longer ignore and in fact must embrace data privacy as a critical part of doing business in the digital world. In fact, not embracing data privacy as a critical part of their strategy, not only puts their stakeholders and stockholders at risk, but also places the future success of their organization in jeopardy. Additionally, increasingly through legal, regulatory, and normative occurrences, Boards are being pressured into taking a more active role in the data privacy activities in their organizations. Therefore, it behooves the BoD to be proactive vice reactive toward their data privacy endeavors.

Cyber threats have escalated in recent years. Many of these threats have been direct and vicious attacks on K-12 systems. Educators are rarely trained on how to address cyber threats from a systemic and educational perspective when such challenges arise in their school buildings. This article explains the cyber threats that are looming large for K-12 systems and provides concrete tools for school leaders to employ in order to provide preventive education to their school communities.

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.

In today's digitally connected world, privacy has transformed from a fundamental human right into a multifaceted challenge. As technology enables the seamless exchange of information, the need to protect personal data has grown exponentially. Privacy has emerged as a critical concern in the digital age, as technological advancements continue to reshape how personal information is collected, stored, and utilized. This paper delves into the fundamental principles of privacy and explores the potential harm that can arise from the mishandling of personal data. It emphasizes the delicate balance between safeguarding individuals' privacy rights and fostering innovation in a data-driven society. By analyzing key privacy principles and their implications, this paper explores the foundational privacy principles that define the concept of privacy while delving into the potential harms that can arise when these principles are violated.

This study aimed to assess the readiness of Jordanian science teachers for integrating Artificial Intelligence (AI) in science education, focusing on their perceptions, challenges, and training needs. A quantitative survey methodology was employed, using a 35-item questionnaire distributed to 136 science teachers in urban Jordan. The questionnaire, developed and refined through expert peer review and a pilot study, encompassed demographics, attitudes towards AI, perceived benefits and challenges of AI in science teaching, self-efficacy in using AI, and behavioural intentions regarding its use. The results indicated varying teacher readiness levels, influenced by gender, educational background, and concerns over data privacy and security. While there was a general sense of optimism about the potential of AI, significant challenges related to limited resource access and insufficient professional development were identified. These results emphasized the need for targeted policy initiatives and training programs to enhance teachers' readiness for AI adoption. The study's insights contributed to understanding the facilitators and barriers to AI integration in science education, highlighting the critical role of teacher readiness in the effective utilization of AI in educational contexts.

In this paper, we present an activity to introduce the idea of public-key cryptography and to make pre-service STEM teachers explore fundamental informatics and mathematical concepts and methods. We follow the Theory of Didactical Situations within the Didactical Engineering methodology (both widely used in mathematics education research) to design and analyse a didactical situation about asymmetric cryptography using graphs. Following the phases of Didactical Engineering, after the preliminary analysis of the content, the constraints and conditions of the teaching context, we conceived and analysed the situation a priori, with a particular focus on the milieu (the set of elements students can interact with) and on the choices for the didactical variables. We discuss their impact on the problem-solving strategies the participants need to elaborate to decrypt an encrypted message. We implemented our situation and collected qualitative data. We then analysed a posteriori the different strategies that participants used. The comparison of the a posteriori analysis with the a priori analysis showed the learning potential of the activity. To elaborate on different problem-solving strategies, the participants need to explore and understand several concepts and methods from mathematics, informatics, and the frontier of the two disciplines, also moving between different semiotic registers.

Academic credentials play an immensely significant role in the career of a person and in the progress of society. The system in place currently used for the issuance, storage & sharing of academic credentials is quite inefficient in its operations, due to being paper based in large. There is also widespread fraud committed every year in terms of academic credentials, ranging from diploma mills to plain forgery. There presents a need for a total digital transformation in this field, which ensures complete independent authenticity of credentials that could be proven in a fool-proof manner. Blockchain technology promises to alleviate the above identified problems by ensuring complete transparency & verifiable proofs of ownership using decentralized storage of credentials & Public Key Cryptography (PKC) in the form of Digital Signatures. This project implements the proposed solution by using the ECDSA algorithm to (i) sign the accreditation of institute by governing body, such as The Ministry of Education (MOE) (ii) sign the academic credentials by the issuing party (iii) sign the issued credentials by the learner to claim iv) sign the credentials by some governing body like the MOE. The learner can share the signed credential with any third party, such as a potential employer. The ECDSA algorithm can then authenticate the credential by programmatically verifying the signature proof by any party using the corresponding Public Key without going through tedious channels.

This paper proposes a human-centered approach to using Artificial Intelligence (AI) in higher education that promotes equitable access to knowledge while preserving privacy and ethics. Through the lens of third-generation Activity Theory we examine the interaction between three activity systems in higher education: AI teachers, human teachers, and students. Our multi-role design recognizes the role of different actors and AI-based tools and technologies, highlighting the importance of understanding how these different systems interact and influence one another in order to effectively design and implement ethical educational technology solutions. By constructing an interaction space between these systems, we gained a deeper understanding of the dynamics of teaching-learning in higher education. Based on this analysis, we frame and design our Ethical AI in Education (EAIED) multi-platform, integrating recent development in AI in education systems, pedagogical strategies, and complying with ethical guidelines recommendation. The EAIED emphasizes data privacy, ethics, and interoperability between learning systems. This approach offers interactive, personalized, and equitable teaching-learning experiences that lead to developing critical thinking, higher-order skills, improving engagement, communication, and expansive learning.

In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students' cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the designers in performing such analytic and evaluation tasks is ad-hoc and insufficient. With unsupervised machine learning methods, we designed a tool for clustering the trainee actions that can exhibit their strategies or help pinpoint flaws in the training design. By using a k-means++ algorithm, we explore clusters of trainees that unveil their specific behavior within the training sessions. The final visualization tool consists of views with scatter plots and radar charts. The former provides a two-dimensional correlation of selected trainee actions and displays their clusters. In contrast, the radar chart displays distinct clusters of trainees based on their more specific strategies or approaches when solving tasks. Through iterative training redesign, the tool can help designers identify improper training parameters and improve the quality of the courses accordingly. To evaluate the tool, we performed a qualitative evaluation of its outcomes with cybersecurity experts. The results confirm the usability of the selected methods in discovering significant trainee behavior. Our insights and recommendations can be beneficial for the design of tools for educators, even beyond cyber security.

Artificial intelligence (AI) and machine learning (ML) have transformed the landscape of data management in higher education institutions, necessitating a critical evaluation of existing data privacy policies and practices. This research delves into the inadequacies of current frameworks in adapting to the swift evolution of Big Data. Student, faculty, and staff perspectives on data privacy are examined in terms of how their viewpoints influence university policies. Data privacy incidents at several universities are discussed to identify patterns and extract lessons learned. Recommendations and best practices for enhancing data privacy in the context of AI/ML implementation are discussed, with an emphasis on the need for policy reform and improved protocols to safeguard student privacy effectively. The integration of AI/ML in higher education must align with robust data privacy standards, enabling institutions to optimize teaching, learning, and administrative processes while safeguarding sensitive student information.

Unnoticed by most, some technology corporations have changed their terms of service to allow user data to be transferred to clouds and even to be used to train artificial intelligence systems. As a result of these developments, remote data collection may in many cases become impossible to be conducted anonymously. Researchers need to react by reconsidering their mode of data collection, raising awareness, and expanding informed consent to ensure information sovereignty. Considerations for data sharing are discussed.

The purpose of the current article is to evaluate social responsibility, digital ethics, and knowledge about safe data storage among students of different ages. Four hundred students took part in the study: 200 people each in the first and fifth years of study. Their ages were 19.2 years (SD = 1.08) and 24.4 years (SD = 1.18), respectively. The research tools were the Chinese University Students' Social Responsibility Scale (CUSSRS), the Digital Ethics Level Scale (SLDE), and the Cyber Security Awareness Survey (CSA). It was found that with age, the indicators of Social Responsibility become higher. Digital Ethics also increases with age: in the category of Privacy and Data Protection, first-year students had a mean value of 11.49 versus 16.04 of fifth-year students; in the Ethical Use of Technology -- 12.05 versus 16.49; in Digital Security -- 11.02 versus 15.00, respectively. At the same time, the Digital Accessibility subscale was the same for the two groups, without significant differences. In addition, the value of Cybersecurity Awareness was higher among fifth-year students with an indicator of 58.86 against an indicator of 46.33 for first-year students, that is, it was 12.53 higher.

The involvement of technology in the education domain has transformed the traditional system in many countries. The need was realized when 300 million students in India itself were pushed to move from traditional to various digital education platforms during the pandemic. There has been an essential emphasis given to the promotion of digital based education for achieving the aim of Digital India and National Education Policy (NEP) 2020. Considering the vision, this research work is an attempt to articulate such factors affecting the attainment of digital education based on previous researches and opinions of domain experts in this area through Nominal Group Technique (NGT). ISM based hierarchical model along with MICMAC were used to analyze the interactions among identified factors. The ISM results have put technology awareness, course & subject choice, digital literacy, geographical location, interactivity, cyber security and training for handling ICT, as the most crucial factors driving the others. The MICMAC results indicate geographical location as the most driving factor and switching behaviour as the most dependent factor. The model will assist to understand how factors work in hierarchy with inter-relationships and thus provide support to policy planners and institutions in planning the effective implementation.

COVID-19 has significantly impacted humankind's lifestyle since its emergence. Educational institutions quickly adopted online courses to deal with its spread. Regrettably, the adoption of e-learning solutions, particularly in Africa, has not given due priority to security. However, cyberattacks and cyber incidents are leaping forward. To propose suitable solutions adapted to West African schools and universities' realities, it is essential to understand their online learning environment fully. This paper presents the status of West Africa's online learning workspace security during the COVID-19 lockdown by highlighting the tools and devices used for the courses and security risks associated, and students' cybersecurity awareness level. The research employs a quantitative methodology involving an online survey, which gathered data from a total of 1653 participants hailing from countries in West Africa. The data analysis revealed that students are concerned about privacy and personal data security, and West African online learning environment security faces many challenges and issues. Identified issues are related to students' low level of cybersecurity concepts, best practices, and applicable privacy laws and regulations. Finally, recommendations are made on needed efforts to secure West African online learning space through existing or proposed security mechanisms.

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.

Existing research literature in computing and IT education shows that there has been limited work on investigating how offense based learning approaches using hacks can enhance learning of mobile security topics. In an effort to fill this research gap, we performed an experimental study with a unique, nifty user hack driven offense based learning strategy to effect mobile security awareness and interest in cybersecurity at the high school and middle school levels, as described in this work. A highlight of our novel study is our original CovertEyeOp mobile app, which was designed and developed strategically to be the driving force towards implementing our hacking based offense driven leaning technique. In this research, we carried out a comparative analysis of our app based offense driven learning approach with other relevant works on mobile security education. To conduct experiments with our user hack driven offense based learning strategy, we created a hands on experiential learning activity using our CovertEyeOp app, which educates users about security and privacy issues in mobile devices by hacking them and enabling them to self-discover issues with user permissions given to mobile apps. We offered this unique mobile app based learning activity to 90 participants (both students and teachers) primarily from the high school community across different states over multiple years and have collected quantitative plus qualitive data in the form of survey responses from these various users. Additionally, we discuss our earlier experiments of hosting an older version of our mobile app based lesson with 100 middle school students. We analyze this gathered learner data from the overall 190 participants' survey responses to determine whether our app driven offense based learning approach works and makes a difference in terms of fostering K-12 learning and engagement through acquired evidence of increased mobile security awareness and interest in cybersecurity. Overall, our study results in unique findings that show the prospects, benefits, and efficacy of including a user hack driven offense based learning strategy in K-12 teaching of mobile security topics. In the process, it advocates for the usage of this unique, non-traditional learning approach in cybersecurity education.

Today's college students increasingly rely on technology in their daily activities, and a basic awareness of data privacy is becoming essential from both a personal and professional standpoint. This article describes the design of an interdisciplinary undergraduate course focused on data privacy law. It outlines the key content areas that encompass the foundational principles of this emerging field and includes descriptions of hands-on exercises that illustrate the technical and managerial elements of a comprehensive privacy compliance program. The course framework and sample assignments can serve as a model for other faculty seeking to teach data privacy law to undergraduate students.

Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However, for short answer formats, automatic grading is challenging due to natural language ambiguity and versatility. While automatic short answer grading models are beginning to compare to human performance on some datasets, their robustness, especially to adversarially manipulated data, is questionable. Exploitable vulnerabilities in grading models can have far-reaching consequences ranging from cheating students receiving undeserved credit to undermining automatic grading altogether--even when most predictions are valid. In this paper, we devise a black-box adversarial attack tailored to the educational short answer grading scenario to investigate the grading models' robustness. In our attack, we insert adjectives and adverbs into natural places of incorrect student answers, fooling the model into predicting them as correct. We observed a loss of prediction accuracy between 10 and 22 percentage points using the state-of-the-art models BERT and T5. While our attack made answers appear less natural to humans in our experiments, it did not significantly increase the graders' suspicions of cheating. Based on our experiments, we provide recommendations for utilizing automatic grading systems more safely in practice.

While a great deal has been published about the educational value of social networking sites (SNSs) for teachers, less has focused on teachers who are arguably more dependent on these virtual platforms for informal professional learning due to financial constraints and a lack of regular in-service professional development. Situating this study in Vietnam and focusing on teachers teaching English as a foreign language, we examined how these teachers have adapted SNSs, a tool typically used in leisure and social life, into online personal learning networks. The evidence was collected from 393 teachers' responses to an online survey. The results from descriptive and non-parametric inferential tests revealed three main findings: (1) Teachers engage in a variety of professional learning activities using SNSs with high frequency, regardless of their self-perceived levels of technology competence or teaching experience; (2) Teachers make use of online groups on SNSs for professional topics and their preferences of topics are not likely to be determined by their experience, except for the topics of classroom management techniques and knowledge about learners; (3) The most decisive factors these teachers associated with effective professional learning on SNSs include time availability, reliability of information and materials, personal information privacy and desire to learn. Teachers' perceptions about these factors are influenced by the frequency of their SNS use and professional work experience. The implications of these findings for teacher professional development in Vietnam, and other countries in similar economic circumstances, are also discussed.

Computer-supported learning technologies are essential for conducting hands-on cybersecurity training. These technologies create environments that emulate a realistic IT infrastructure for the training. Within the environment, training participants use various software tools to perform offensive or defensive actions. Usage of these tools generates data that can be employed to support learning. This paper investigates innovative methods for leveraging the trainee data to provide automated feedback about the performed actions. We proposed and implemented feedback software with four modules that are based on analyzing command-line data captured during the training. The modules feature progress graphs, conformance analysis, activity timeline, and error analysis. Then, we performed field studies with 58 trainees who completed cybersecurity training, used the feedback modules, and rated them in a survey. Quantitative evaluation of responses from 45 trainees showed that the feedback is valuable and supports the training process, even though some features are not fine-tuned yet. The graph visualizations were perceived as the most understandable and useful. Qualitative evaluation of trainees' comments revealed specific aspects of feedback that can be improved. We publish the software as an open-source component of the KYPO Cyber Range Platform. Moreover, the principles of the automated feedback generalize to different learning contexts, such as operating systems, networking, databases, and other areas of computing. Our results contribute to applied research, the development of learning technologies, and the current teaching practice.

A qualitative case study focused on understanding what steps are needed to prepare the cybersecurity workforces of 2026-2028 to work with and against emerging technologies such as Artificial Intelligence and Machine Learning. Conducted through a workshop held in two parts at a cybersecurity education conference, findings came both from a semi-structured interview with a panel of experts as well as small workgroups of professionals answering seven scenario-based questions. Data was thematically analyzed, with major findings emerging about the need to refocus cybersecurity STEM at the middle school level with problem-based learning, the disconnects between workforce operations and cybersecurity operators, the distrust of Non-Traditional Training Programs, and the need to build digital security generalists' curriculum and training. Recommendations are also made for possible next steps.

The principal investigator (PI) conducted this research study to explore the strategic cybersecurity defense IT Managers should implement to reduce healthcare data breaches. The PI conducted a systematic literature review and selected articles that addressed healthcare data security breaches, information disclosure, cybersecurity in healthcare, and IT Managers' lack of leadership competence. Also, various annotations from contextual, seminal, grey, and recent literature were used to find the research problem: The strategic cybersecurity defense IT Managers should implement to reduce healthcare data breaches has not been established. The PI collected secondary data from the Office of Civil Rights (OCR)/Department of Health and Human Services (HHS). The analysis, results, and findings are provided below in Part 9. Nevertheless, the routine interaction during health information exchange (HIE) on an interoperable network and the behavior of care providers and third parties who use computers and mobile devices to exchange patient data is an opportunity for cybercriminals to install malware or launch a ransomware attack to exploit potential vulnerabilities whether to steal sensitive data or compromise the network systems. Therefore, strategic cyber defense or an innovative security model would mitigate the threat. An exploratory design is used, and an epistemological approach supports the research method and design. The study is significant, and it will contribute to the body of knowledge the PI suggested for future research and provide major recommendations.