Aim/Purpose: This study seeks to present a learning model of discrete mathematics elements, elucidate the content of teaching, and validate the effectiveness of this learning in a digital education context. Background: Teaching discrete mathematics in the realm of digital education poses challenges, particularly in crafting the optimal model, content, tools, and methods tailored for aspiring computer science teachers. The study draws from both a comprehensive review of relevant literature and the synthesis of the authors’ pedagogical experiences. Methodology: The research utilized a system-activity approach and aligned with the State Educational Standard. It further integrated the theory of continuous education as its psychological and pedagogical foundation. Contribution: A unique model for instructing discrete mathematics elements to future computer science educators has been proposed. This model is underpinned by informative, technological, and personal competencies, intertwined with the mathematical bedrock of computer science. Findings: The study revealed the importance of holistic teaching of discrete mathematics elements for computer science teacher aspirants in line with the Informatics educational programs. An elective course, “Elements of Discrete Mathematics in Computer Science”, comprising three modules, was outlined. Practical examples spotlighting elements of mathematical logic and graph theory of discrete mathematics in programming and computer science were showcased. Recommendations for Practitioners: Future computer science educators should deeply integrate discrete mathematics elements in their teaching methodologies, especially when aligning with professional disciplines of the Informatics educational program. Recommendation for Researchers: Further exploration is recommended on the seamless integration of discrete mathematics elements in diverse computer science curricula, optimizing for varied learning outcomes and student profiles. Impact on Society: Enhancing the quality of teaching discrete mathematics to future computer science teachers can lead to better-educated professionals, driving advancements in the tech industry and contributing to societal progress. Future Research: There is scope to explore the wider applications of the discrete mathematics elements model in varied computer science sub-disciplines, and its adaptability across different educational frameworks.

Aim/Purpose: To explore the effectiveness of utilizing the design thinking approach in developing digital self-directed learning environment to enhance digital literacy skills in Thai higher education. Background: To foster digital literacy skills in higher education, Thai students require more than access to technology. Emphasizing digital self-directed learning and incorporating Design Thinking approach, can empower students to learn and develop their digital skills effectively. This study explores the impact of digital self-directed learning environment, developed using a design thinking approach, on enhancing digital literacy skills among higher education students in Thailand. Methodology: The research methodology involves developing a digital self-directed learning environment, collecting and analyzing data, and using statistical analysis to compare the outcomes between different groups. The sample includes 60 undergraduate students from the School of Industrial Education and Technology at King Mongkut Institute of Technology, divided into a control group (n=30) and an experimental group (n=30). Data analysis involves mean, standard deviation, and one-way MANOVA. Contribution: This research contributes to the evidence supporting the use of Design Thinking in developing digital self-directed learning environment, demonstrating its effectiveness in meeting learners’ needs and improving learning outcomes in higher education. Findings: Key findings include: 1) the digital media and self-directed learning activities plan developed through the design thinking approach received high-quality ratings from experts, with mean scores of 4.87 and 4.93, respectively; and 2) post-lesson comparisons of learning outcome and digital literacy assessment scores revealed that the group utilizing digital media with self-directed learning activities had significantly higher mean scores than the traditional learning group, with a significance level of 0.001. Recommendations for Practitioners: Practitioners in higher education should use design thinking to develop digital self-directed learning environments that enhance digital literacy skills. This approach involves creating high-quality digital media and activities, promoting engagement and improved outcomes. Collaboration and stakeholder involvement are essential for effective implementation. Recommendation for Researchers: Researchers should continue to explore the effectiveness of design thinking approaches in the development of learning environments, as well as their influence on different educational aspects such as student engagement, satisfaction, and overall learning outcomes. Impact on Society: By enhancing digital literacy skills among higher education students, this study contributes to the development of a digitally skilled workforce, encourages lifelong learning, and aids individuals in effectively navigating the challenges of the digital era. Future Research: Future research could explore a broader range of student demographics and educational settings to validate the effectiveness of the Design Thinking approach in enhancing digital literacy. This could include integrating design thinking with alternative digital learning and teaching methods to further improve digital literacy.

Aim/Purpose: This paper describes a technologies education model for introducing Simulation Learning and Extended Reality (XR) solution creation skills and knowledge to students at the tertiary education level, which is broadly applicable to higher education-based contexts of teaching and learning. Background: This work is made possible via the model’s focus on advancing knowledge and understanding of a range of digital resources, and the processes and production skills to teach and produce playable educational digital content, including classroom practice and applications. Methodology: Through practice-based learning and technology as an enabler, to inform the development of this model, we proposed a mixed-mode project-based approach of study within a transdisciplinary course for Higher Education students from the first year through to the post-graduate level. Contribution: An argument is also presented for the utility of this model for upskilling Pre-service Teachers’ (PSTs) pedagogical content knowledge in Technologies, which is especially relevant to the Australian curriculum context and will be broadly applicable to various educative and non-Australian settings. Findings: Supported by practice-based research, work samples and digital projects of Simulation Learning and XR developed by the authors are demonstrated to ground the discussion in examples; the discussion that is based around some of the challenges and the technical considerations, and the scope of teaching digital solutions creation is provided. Recommendations for Practitioners: We provide a flexible technologies teaching and learning model for determining content for inclusion in a course designed to provide introductory Simulation Learning and XR solution creation skills and knowledge. Recommendation for Researchers: The goal was to provide key criteria and an outline that can be adapted by academic researchers and learning designers in various higher education-based contexts of teaching and inclusive learning design focused on XR. Impact on Society: We explore how educators work with entities in various settings and contexts with different priorities, and how we recognise expertise beyond the institutional interests, beyond discipline, and explore ‘what is possible’ through digital technologies for social good and inclusivity. Future Research: The next step for this research is to investigate and explore how XR and Simulation Learning could be utilised to accelerate student learning in STEM and HASS disciplines, to promote knowledge retention and a higher level of technology-enhanced learning engagement.

Aim/Purpose: This research explores the influence of organizational-level and individual-level creativity and innovation and the technology acceptance model toward the higher education creative environment that consists of research creativity and teaching creativity. Background: Creativity and innovation are essential pillars for higher education institutions (HEIs). The two terms are interconnected, where creativity is referring to finding better ideas to do the work, while innovation is referring to how to do and implement these creative ideas. Choosing the optimal creative process and the organizational support needed to develop it is an important goal in achieving a creative and inventive environment. For the success of the creative environment to ensure the improvement of higher education institutions, information technology as social networking sites plays a crucial part in the creative process within universities. However, assessing the creativity and innovation of Saudi higher education institutions has not been well recognized. Universities today serve as knowledge-based institutions because they are at the forefront of cutting-edge R&D and scientific innovations. Creating such a productive research environment in universities, however, necessitates a work culture that encourages employees to be more creative while also encouraging the creation of new ideas and innovations. Methodology: A survey instrument was utilized as a quantitative method for this research to gather data from the study sample on the influencing variables employed in the research framework. Respondent data were analyzed using a disjoint two-stage method using PLS-SEM path modelling. Contribution: The results of this research contribute to the theoretical and scientific literature by offering a model of creativity and innovation in higher education institutions. The model proposes an optimal blend of organizational, individual, and technology variables that contribute to the development of the Higher Education Creative Environment in HEIs via creativity in teaching and research and a culture of innovation. In another way, the proposed framework especially helps to comprehend the challenges regulating establishing teaching and research creativity in HEIs via the adoption of organizational, individual, and technology enablers identified as part of this study. Findings: According to the results, organizational factors such as organizational encouragement, freedom, and challenging work have a positive relationship with the higher education creative environment. However, realistic work pressure, a lack of organizational impediments, managerial encouragement, and work group support is insufficient to affect the creative environment in higher education in Saudi Arabia. Individual variables (creative thinking skills and expertise, for example) also have a positive impact on the higher education creative environment. In the higher education creative environment, however, the influence of intrinsic motivation is insignificant. Finally, technology factors such as social networking site adoption intention, perceived usefulness, and perceived ease of use have the potential to influence the higher education creative environment. Recommendations for Practitioners: On the practical front, the obvious recommendation of this research is that it enables top leadership in Saudi HEIs to rethink the norms of creativity and innovation in their institutions, thereby instilling a mindset guided by a flourishing culture of creativity in the HEI environment with a specific focus on creativity practices in research and teaching domains. Furthermore, to promote the environment’s creativity within Saudi Arabian HEIs, university leaders must consider the suggested Organizational, Individual, and Technology factors as key enablers of creativity and innovation, which will guide them in revisiting their strategic actions in terms of further augmenting the creative performance of their academic’s staff, thereby sustaining a culture of Higher Education Creative Environment (HECE). Recommendation for Researchers: This study addressed many organizational, individual, and technology variables that facilitate Saudi Arabian HECE accomplishment in the form of research and teaching creativity. Furthermore, fresh insights for Saudi public HEIs are revealed when the success aspects of the creative environment are considered. If academic leadership at Saudi HEIs is to encourage the creative environment in general and creativity in teaching and research, it would be suitable for them to highlight individual, organizational, and technology success elements. As a result, their HEIs will be able to produce more innovative research, products, and services that can support and meaningfully achieve national transformation initiatives, opening the path for a transition into a knowledge-based economy. Impact on Society: In fact, this research is based on a quantitative research method, and the findings were also significant especially considering the current global crises. It is clearly understood by this process that includes organizational, individual, and technology factors as key enablers of the creative performance of academic staff, thereby sustaining a culture of HECE. Future Research: While providing the research model, it is probable that this study overlooked any other crucial aspects influencing creativity and innovation. As a result, future research should look at additional variables that may impact HECE in Saudi Arabian HEIs. Furthermore, while this study focused on deriving HECE with a particular emphasis on research and teaching creativity as results, future research might look at deriving other creativity outcomes (e.g., entrepreneurial creativity) within the investigated HECE dimension.

Forensic document forgery investigations have elevated the need for source identification for printed documents during the past few years. It is necessary to create a reliable and acceptable safety testing instrument to determine the credibility of printed materials. The proposed system in this study uses a neural network to detect the original printer used in forensic document forgery investigations. The study uses a deep neural network method, which relies on the quality, texture, and accuracy of images printed by various models of Canon and HP printers. The datasets were trained and tested to predict the accuracy using logical function, with the goal of creating a reliable and acceptable safety testing instrument for determining the credibility of printed materials. The technique classified the model with 95.1% accuracy. The proposed method for identifying the source of the printer is a non-destructive technique.

This study examines the relationships between ICTs (e.g., chatbots, virtual assistants, social media platforms, e-mail marketing, mobile marketing, data analytics, interactive voice response, big data analytics, push notifications, cloud computing, and augmented reality) and e-customer relationship management (e-CRM) from the banking industry of China. Similarly, this study unfolds the moderation interference of trust and risk between the association of ICTs and e-CRM, respectively. The study provided a positive nexus between ICTs and e-CRM. On the other side, a significant moderation of trust, as well as financial risk was observed between the correlation of ICTs and customer relationship management. This study endows with insights into ICTs which are critical for achieving e-CRM by streamlining interactions and enhancing their experience. Similarly, trust and financial risk were observed as potential forces that sway the association between ICTs and e-CRM.

The study aims to unveil the various determinants that drive the adoption of e-governance services (EGS). Using the UTAUT 3 model, the research investigated these factors within the Indian context. A purposive sampling technique was utilised to collect the samples from 680 respondents through the online survey method. Furthermore, the study employs structural equation modelling (SEM) to examine the structural relationships between the UTAUT3 model's dimensions in the context of e-governance. Findings revealed that the UTAUT3 model adequately predicts the intention to adopt EGS. The present study addressed a significant gap in the literature on EGS and technology adoption by establishing a relationship between different dimensions of the UTAUT3 model and actual usage of EGS. The findings have implications for practitioners and policymakers as they throw light on the effective implementation of e-governance programs, which are essential for providing the citizens with high-quality services.

This article presents a case study that outlines the potential of DigiBot technology, an interactive automated response program, in mobile open learning (MOL) for business subjects. The study, which draws on a project implemented in Sub-Saharan Africa, demonstrates the applications of DigiBots delivered via WhatsApp to over 650,000 learners. Employing a mixed-methods approach, the article reports on live event tracking, qualitative observations from facilitators and learning technologists, and a learner survey (<i>N</i> = 304,000). The research offers practical recommendations and proposes a model for scalable DigiBot learning. Findings reveal that in this case, DigiBot MOL had the potential to effectively address two key obstacles in open learning: accessibility and scalability. Leveraging mobile platforms such as WhatsApp mitigates accessibility restrictions, particularly in resource-constrained contexts, while tailored micro-learning enhances scalability.

Bright Lights has a history of success, but is at a pivotal point, facing the pains of strategic change. One salesperson has found a way to maintain sales and increase profit margin, but it requires operating between the lines of ethical boundaries. Ethics provides a choice between right and right as opposed to moral temptation of right and wrong (Kidder, 1996). As the case unfolds, Jim receives a mandate of which customers he can call on, reducing sales, profit margin, and customer satisfaction. A top performer, Jim finds a solution within company policy and the law, but although not hidden, is not entirely transparent. This creates two ethical decisions: 1) Should he be reprimanded or praised? 2) Should the company update policies to ban his actions, or promote his actions among other salespeople? This case clearly strikes the dilemma found in navigating the boundaries of a questionable business strategy.

In order to improve the quality of higher education, student satisfaction, and employment rate, a data mining based high-quality management method for higher education is proposed. Firstly, construct a high-quality evaluation system for higher education based on the principles of education quality evaluation. Secondly, the association rule mining method is used to construct a university education quality management model and determine the weight of the impact indicators for high-quality management of university education. Finally, the fuzzy evaluation method is used to determine the high-quality evaluation function of higher education, and the results of high-quality evaluation of higher education are obtained. High-quality management strategies are developed based on the evaluation results to improve the quality of education. The experimental results show that the student satisfaction rate of this method can reach 99.3%, and the student employment rate can reach 99.9%.

Aiming to improve the accuracy, recall, and F1 value of data classification, this paper proposes an applied university innovation and entrepreneurship data classification method based on the nearest neighbour criterion. Firstly, the decision tree algorithm is used to mine innovation and entrepreneurship data from applied universities. Then, dynamic weight is introduced to improve the similarity calculation method based on edit distance, and the improved method is used to realise data de-duplication to avoid data over fitting. Finally, the nearest neighbour criterion method is used to classify applied university innovation and entrepreneurship data, and cosine similarity is used to calculate the similarity between the samples to be classified and each sample in the training data, achieving data classification. The experimental results demonstrate that the proposed method achieves a maximum accuracy of 96.5% and an average F1 score of 0.91. These findings indicate a high level of accuracy, recall, and F1 value for data classification using the proposed method.

Copying and duplicating papers for educational purposes is a violation form of copyright in Indonesia. The principle of fair use in education is a form of structured violation. Copying and duplicating the papers of the authors for educational purposes has provided commercial (business) benefits for libraries and universities. The research method is conducted using the observation method in libraries and universities that duplicate papers. The method also uses the normative juridical method that connects duplication of the papers in libraries and universities with the fair use principle. The results explain the authors' loss from copying and duplicating of papers in libraries and universities. Therefore, copying and duplicating the papers can only be done by implementing the responsibility system. Copying and duplicating the papers of the authors' in libraries and universities can be allowed if they fulfil the elements of copyright protection in the new concept.

In order to improve the identification accuracy, accuracy and time-consuming of traditional financial risk identification methods, this paper proposes a risk identification method for financial abnormal data based on weighted random forest. Firstly, SMOTE algorithm is used to collect abnormal financial data; secondly, the original accounting data is decomposed into features, and the features of abnormal data are extracted through random forests; then, the index weight is calculated according to the entropy weight method; finally, the negative gradient fitting is used to determine the loss function, and the weighted random forest method is used to solve the loss function value, and the recognition result is obtained. The results show that the identification accuracy of this method can reach 99.9%, the accuracy rate can reach 96.06%, and the time consumption is only 6.8 seconds, indicating that the risk identification effect of this method is good.

In order to solve the problems of large generalisation error, low recall rate and low retrieval accuracy of customer evaluation information in traditional trust evaluation methods, an evaluation method of customer trust in e-commerce market based on entropy weight analytic hierarchy process was designed. Firstly, build an evaluation index system of customer trust in e-commerce market. Secondly, the customer trust matrix is established, and the index weight is calculated by using the analytic hierarchy process and entropy weight method. Finally, five-scale Likert method is used to analyse the indicator factors and establish a comment set, and the trust evaluation value is obtained by combining the indicator membership. The experiment shows that the maximum generalisation error of this method is only 0.029, the recall rate is 97.5%, and the retrieval accuracy of customer evaluation information is closer to 1.

The European Union Rights Management Directive 2014/26/EU, provides regulatory oversight of European Union (EU) Collective Management Organizations (CMOs). However, the Directive has no provision indicating how members of EU CMOs may conduct non-financial audits of their CMO income and reporting. This paper addresses the problem of a lack of an audit method through a case study of the five writer members of the music group Duran Duran, who have been members of the UK's CMO for performing rights - the Performing Rights Society (PRS) for over 35 years. The paper argues a new audit CMO member method that can address the lacunae regarding the absence of CMO member right to audit a CMO and an applicable CMO audit method.

The present paper offers a critique of the General Data Protection Regulation in the realm of access to information. Even though the GDPR supports the constitutionally obvious position that the right to data protection does not outweigh other equally important rights, the enhanced protection of the right to the protection of personal data leads to the potential neglect of other constitutional rights, such as that of access to information. Data protection and access to information authorities should be established both on an EU, as well as at national level as a single authority. Scientific research must be facilitated through access to a multitude of information. The present article explores the question of data ownership and aims to propose a new system that will enhance access to information. A key tool of our research will be the comparative overview of existing legislative systems and a review of the different approaches in the case-law of independent authorities.

This paper analyses the adoption of learning analytics to predict at-risk students. A total of 233 research articles between 2004 and 2023 were collected from Scopus for this study. They were analysed in terms of the relevant types and sources of data, targets of prediction, learning analytics methods, and performance metrics. The results show that data related to students' academic performance, socio-demographics, and learning behaviours have been commonly collected. Most studies have addressed the identification of students who have a higher chance of poor academic performance or dropping out of their courses. Decision trees, random forests, and artificial neural networks are the most frequently used techniques for prediction, with ensemble methods gaining popularity in recent years. Classification accuracy, recall, sensitivity, and true positive rate are commonly used as performance metrics for evaluation. The results reveal the potential of learning analytics for informing timely and evidence-based support for at-risk students.

Using information criteria is a common method for making a decision about which model to use for forecasting. There are many different methods for evaluating forecasting models, such as MAE, RMSE, MAPE, and Theil-U, among others. After the creation of AIC, AICc, HQ, BIC, and BICc, the two criteria that have become the most popular and commonly utilised are Bayesian IC and Akaike's IC. In this investigation, we are innovative in our use of exponential weighting to get the log-likelihood of the information criteria for model selection, which means that we propose assigning greater weight to more recent data in order to reflect their increased precision. All research data is from the major stock markets' daily observations, which include the USA (GSPC, DJI), Europe (FTSE 100, AEX, and FCHI), and Asia (Nikkei).

In 2008 the University of Hull, Stanford University and University of Virginia decided to collaborate with Fedora Commons (now DuraSpace) on the Hydra project. This project has sought to define and develop repository-enabled solutions for the management of multiple digital content management needs that are multi-purpose and multi-functional in such a way as to allow their use across multiple institutions. This article describes the evolution of Hydra as a project, but most importantly as a community that can sustain the outcomes from Hydra and develop them further. The data modelling and technical implementation are touched on in this context, and examples of the Hydra heads in development or production are highlighted. Finally, the benefits of working together, and having worked together, are explored as a key element in establishing a sustainable open source solution.

In this article, we have attempted to study the ways in which the COVID-19 pandemic has gradually increased and impacted the world. The authors integrate the knowledge from cognitive psychology literature to illustrate how the limitations of the human mind might have a critical role in the decisions taken during the COVID-19 pandemic. The authors show the correlation between different biases in various contexts involved in the COVID-19 pandemic and highlight the ways in which we can nudge ourselves and various stakeholders involved in the decision-making process. This study uses a typology of biases to examine how different patterns of biases affect the decision-making behaviour of people during the pandemic. The presented model investigates the potential interrelations among environmental transformations, cognitive biases, and strategic decisions. By referring to cognitive biases, our model also helps to understand why the same performance improvement practices might incite different opinions among decision-makers.