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Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that enables users to store, query, and analyze large datasets. It also explored the benefits and applications of both tools and their integration with other platforms and services. The project offers an introductory insight into Tableau's functionalities, employing a data file from the US Census Bureau via Google BigQuery.

The objectives of this research were: 1) to study the current situation of digital management in universities in Guangxi, 2) to develop the purpose model for improving digital management in universities in Guangxi, 3) to evaluate the suitability and feasibility of the purpose model for improving digital management in universities in Guangxi. The sample group of this research was 148 administrators in 20 public undergraduate universities in Guangxi. They were selected by systematic random sampling and sample random sampling. The interview group was led by administrators from 12 universities, totaling 12 people. The experts for evaluating the suitability and feasibility of the purpose model for improving digital management consisted of high-level administrators from 7 universities, totaling 7 people. The research instruments were document analysis, questionnaire, structured interview, and evaluation form. The statistics to analyze the data were percentage, average value, and standard deviation. The results found that the current situation of digital management in universities in Guangxi in five aspects was at a high level. Considering the results of this research aspects ranged from the highest to lowest level were as follows: the highest level was the digital campus security management system, followed by the digital student management system, and the digital scientific research management system was the lowest level. The purpose model for improving digital management in universities in Guangxi has five aspects, which contain 40 measures. There are 7 measures to enhance the digital management ability of Guangxi University managers, 10 measures to promote the digital teaching management system in Universities in Guangxi, 8 measures to promote the digital scientific research management system in Universities in Guangxi, 9 measures to promote the digital student management system in Universities in Guangxi, 6 measures to promote the digital campus security management system in Universities in Guangxi. The results of the evaluation of the suitability and feasibility of the purpose model for improving digital management in universities in Guangxi were at the highest level.

Blockchain technology usage in education sector has a capacity to change the way academic records, diplomas, and credentials are maintained, communicated, and verified. Thus, this study aims at understanding the role of blockchain in the higher education sector. Mixed method approach was used in the study for a deeper understanding of the concept. Study 1 is qualitative in nature which includes the structured interviews. On the basis of transcripts generated from study 1, study 2 assimilates Technology Acceptance Model and Extended Theory of Planned Behaviour to study the adoption of blockchain technology in higher education institutes. Partial Least Squares Structural Equation Modelling (PLS- SEM) has been applied to test the hypothesis derived. A total of 333 responses were gathered via offline and online modes from the state of Punjab, India. Further, the proposed model frame was tested and validated through SmartPLS software version 3.2.8. The results of the study reveals that Perceived Usefulness, Perceived Ease of Use, Attitude, Perceived Behaviour Control, Awareness and Regulatory Support were found significant whereas, Personal Norms and Facilitating Conditions were insignificant. The study tries to extend the existing knowledge about the application of blockchain in the education system. Moreover, the study contributes to society by providing practical implications for policy formulation regarding deployment of blockchain technology in higher education institutions.

This research aims to investigate information asymmetry in e-commerce supply chain channels and the impact of the fair preference model on the behavior and returns of channel members. Therefore, by contrasting it with the model in the completely rational case, this research establishes a more realistic principal-agent model and incorporates the fair preference model into the e-commerce supply chain channel. According to the model's analysis, the effort level of the retailer at each stage is positively correlated with the e-commerce efficiency coefficient, and the incentive coefficient of manufacturers is positively correlated with the e-commerce efficiency coefficient in the case where all rationality is assumed. Manufacturing companies' anticipated profits are positively correlated with the e-commerce efficiency coefficient. According to the fair preference model, retailers will put forth more effort to sell products when their fixed income from manufacturers is higher and their optimal effort level is positively correlated with that income. When e-commerce's efficiency coefficient is higher than 1, the retailer's revenue and effort exceeded those of traditional channels. Manufacturers and retailers both experience Pareto improvements in their earnings after the fair preference model is introduced.

Indonesian universities are implementing various strategies to improve the quality and quantity of scientific publications. Sriwijaya University has restructured its research and community service grant services by implementing e-services through the new generation management information system of the institute of research and community service (SIM LPPM NG). Numerous studies have been performed to determine the factors that influence lecturer performance, particularly in scientific journals. The purpose of this research is to utilize a model to investigate the impact of system quality, information quality, and service quality on user satisfaction and performance. For partial least squares structural equation modelling (PLS-SEM), 280 respondents comprised the dataset. The results demonstrated that system quality, information quality, and service quality influence user satisfaction. Individual performance is influenced by the level of user satisfaction. According to the findings of this study, the DeLone and McLean information system success model can be used to evaluate obligatory e-services that are integrated.

This research aimed to investigate the components of digital information fluency (DIF) skills among high school students. The sample comprised 354 teachers from schools supervised by the Office of the Basic Education Commission (OBEC) Secondary Educational Service Area Offices (SEAOs), selected through multiple-stage random sampling. Their opinions concerning student DIF skills were collected via a questionnaire and analyzed using descriptive statistics and a 2nd order confirmatory factor analysis (CFA). Results revealed a high overall level of opinion among technology teachers regarding student DIF skills, with Digital Data Communication (DDC) exhibiting the highest weight ([beta] = 1.00, R[superscript 2] = 1.00), followed by Digital Literacy (DL) ([beta] = 0.97, R[superscript 2] = 0.95), and Digital Information Management (DIM) ([beta] = 0.91, R[superscript 2] = 0.83). This study contributes to the literature by providing insights into the perception of DIF skills among teachers, shedding light on areas of emphasis in digital fluency education. Additionally, it offers valuable implications for curriculum development and teacher training programs aimed at enhancing students' digital literacy in today's information-rich environment.

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 GbL platform, or game-based learning platform, with generative AI is a research tool initiated from the combination of game-based learning concepts and generative artificial intelligence technology; thereby, this platform is intended to be used as a guideline for the instruction management, in which learners can respond and interact with the real-time activities by means of gamification. The objectives of this research are (1) to study and synthesize the conceptual framework of the GbL platform with generative AI to enhance digital and technology literacy skills, (2) to develop the architecture of the GbL platform with generative AI to enhance digital and technology literacy skills, and (3) to study the results of the development of the GbL platform with generative AI to enhance digital and technology literacy skills. The results of this research show that (1) the overall elements suitability of the architecture of the GbL platform with generative AI is at the highest level (Mean = 4.51, SD = 0.48), and (2) the overall suitability of the architecture of the GbL platform with generative AI is at the highest level (Mean = 4.59, SD = 0.41). Nevertheless, there are still some research gaps in this study; that is, this study was conducted with quite a small sample group and it focuses mainly on the results of evaluation on the architecture of the GbL platform. Therefore, this research is regarded merely as a pilot study designated for feasibility study to further develop the GbL platform that can be put in practical use in the future.

The proliferation of digital software is an increasingly accepted part of everyday life in higher education in the United States. While this software affords some opportunities, it can create confusing experiences for students as well. In this paper, I ask how might increasingly complex digital ecosystems in higher education shape the contours of instructor-student communication. To answer this question, I conducted an exploratory case study in the form of an online survey (n=83) and subsequent interviews (n=18) with user experience (UX) design students at a large public university in the southeastern United States. The research showed that students felt confusion regarding digital software protocols in their classes, how protocols varied from class to class, an inability to remember when and how to communicate with instructors outside of class, unsureness about where to locate information, and a preference for messaging applications over email. Research results suggest that instructor-student communication in higher education can be productively viewed through the lens of information architecture. In doing so, I argue for the need for instructors to implement strong information architecture strategies that help make sense of information in increasingly complex academic ecosystems.

The article is in the second phase of research is about "the big data architecture for pre-teacher preparation supply chain with prescriptive analytics of higher education in Thailand". The objectives of the study were (1) to study the pre-teacher preparation supply chain in Thailand, (2) to develop a model the big data system for the pre-teacher preparation supply chain management with prescriptive analytics of higher education in Thailand, (3) to design the big data architecture for the pre-teacher preparation supply chain management with prescriptive analytics of higher education in Thailand, (4) to develop the big data system for the pre-teacher preparation supply chain prescriptive of higher education in Thailand, (5) to assess accuracy of the predictive analytics in the pre-teachers needs of higher education in Thailand, and (6) to assess accuracy of the prescriptive analytics in the pre-teacher preparation of higher education in Thailand. In the study, the research procedures were divided into 6 steps according to the objectives, and all steps were assessed on the system suitability by 25 experts throughout the procedures.

This research aims to design an intelligent platform architecture for electronic asset supply chains for digital higher education and to evaluate the architecture of the intelligent platform for electronic asset supply chains for digital higher education. The sample group consists of evaluations of the intelligent platform architecture for the electronic asset supply chains for digital higher education by experts. These experts assess and certify the appropriateness of the architecture, evaluating the content's suitability and the management processes. The evaluations were conducted by 5 experts who have experience in managing assets in higher education or relevant areas. The research results indicate that the designed intelligent platform architecture for electronic asset supply chains for digital higher education, on average, scored 4.43, which is considered 'good'. The evaluation of its developmental trend from architecture to platform has an average score of 4.80, considered 'very good'. Following that, both the system (Administrators) and the (Webserver and Database Server) evaluations yielded the same average score of 4.60, which is also ranked as 'very good.'

While geographic search filters exist, few of them are validated and there are currently none that focus on Germany. We aimed to develop and validate a highly sensitive geographic search filter for MEDLINE (PubMed) that identifies studies about Germany. First, using the relative recall method, we created a gold standard set of studies about Germany, dividing it into 'development' and 'testing' sets. Next, candidate search terms were identified using (i) term frequency analyses in the 'development set' and a random set of MEDLINE records; and (ii) a list of German geographic locations, compiled by our team. Then, we iteratively created the filter, evaluating it against the 'development' and 'testing' sets. To validate the filter, we conducted a number of case studies (CSs) and a simulation study. For this validation we used systematic reviews (SRs) that had included studies about Germany but did not restrict their search strategy geographically. When applying the filter to the original search strategies of the 17 SRs eligible for CSs, the median precision was 2.64% (interquartile range [IQR]: 1.34%-6.88%) versus 0.16% (IQR: 0.10%-0.49%) without the filter. The median number-needed-to-read (NNR) decreased from 625 (IQR: 211-1042) to 38 (IQR: 15-76). The filter achieved 100% sensitivity in 13 CSs, 85.71% in 2 CSs and 87.50% and 80% in the remaining 2 CSs. In a simulation study, the filter demonstrated an overall sensitivity of 97.19% and NNR of 42. The filter reliably identifies studies about Germany, enhancing screening efficiency and can be applied in evidence syntheses focusing on Germany.

COVID-19, Artificial Intelligence (AI), and Climate Change, have disrupted work education, rendering sustainability of careers and livelihoods a concern. This paper outlines a collaborative response to that challenge, offering opportunities for sustainable livelihoods in a work education cloud collaboration, Project SLiC (Sustainable Livelihoods Collaboration). We have joined forces across nation states in the Global South/North to share cloud resources, focused on teaching a postgraduate course, Sustainable Livelihoods. Online modules are stored in a secure cloud site, from which local courses draw-down, autochthonously, whichever resources fit workforce development in context. We outline modules, and an evaluative process, in a proof-of-concept trial. Finally, we envisage how this initial collaboration may morph into a whole degree, including research supervision. We close with a call to career development professionals to share their unique expertise and experiences at the work education frontline, on how to develop this sustainable careers project, for the greater good.

This scoping review maps research ethics and integrity challenges and best practices encountered by research actors in the DACH countries (Germany, Austria, and Switzerland), including researchers, funders, publishers, research ethics committees, and policymakers, during the COVID-19 pandemic. The COVID-19 pandemic brought research and, in turn, research ethics and integrity, into public focus. This review identified challenges related to changing research environments, diversity in research, publication and dissemination trends, scientific literacy and trust in science, recruitment, research redundancy and study termination, placebo and human challenge studies, data management, and informed consent. These challenges are linked to two crucial factors: first, actors in the DACH research ecosystem lacked a sound knowledge base to assess the risks and benefits of research during the COVID-19 pandemic. Second, researchers in the DACH region faced pressure from policymakers, funders, and the public to generate relevant, timely, and consistent findings to mitigate the impacts of the COVID-19 pandemic. In addition, this review highlights best practices to mitigate the effects of future crises on research ethics and integrity, including enhanced cooperation among actors, continuous ethics assessments, and support for public scientific literacy.

This research demonstrates a method to introduce blockchain technology in the classroom based on the Proof of Attendance Protocol (POAP). A blockchain is a digital distributed ledger with the potential to improve transparency and trust between parties. Businesses are testing, piloting, and deploying blockchain technology across their organizations, and students show growing interest in the technology. This teaching brief proposes an exercise that uses POAPs, nonfungible tokens (NFTs) associated with an event, to help students understand blockchain technology within supply chain management contexts. Instructors can use the exercise for various purposes: as incentives for behavior the instructor wishes to encourage (such as attending class) or as prizes for games. The exercise also includes a glossary of blockchain-related terms to introduce the language of this industry to students. Student surveys showed a significant change in their knowledge of blockchain technology, specifically, a 41% increase in understanding of how blockchain technology may benefit supply chain management and a 35% improvement in the ability to explain blockchain technology to others. This brief concludes with resources to create and distribute POAPs for courses and other settings.

Educators are tasked with continually updating course objectives, content, assignments, and assessment to meet model curriculum guidelines. IS2020 proposes program level outcomes for required and elective areas. Two elective areas in IS2020 are Data and Business Analytics and Data and Information Visualization. IS2020 details 14 program level competencies (organized within knowledge elements and skills) that are then integrated into individual course-level design. This work presents a set of laboratory exercises to fulfill the competencies of both elective areas. The set of exercises have been taught in the classroom over several years and have been refined to evaluate coverage of the 14 program competencies. The exercises begin with step-by-step tutorials that build student capabilities with software. Advanced exercises propose open challenges to solve. These resources provide IS programs with a draft of potential exercises to include in courses and a framework for covering program-level objectives.

Contribution: This research explores the effectiveness of a proposed teaching strategy in blockchain education, finding that it enhances learning outcomes, cognitive well-being, and student engagement in tertiary education, ultimately resulting in a shallower learning curve for STEM knowledge. Background: In the context of Industry 4.0, blockchain technology has emerged as a key driver of transformation in data management and system automation across a range of industrial applications. Despite its significance, the intricate theories and concepts associated with blockchain often serve as a deterrent for novice learners, inhibiting their ability to appreciate the value of industrial blockchain. Consequently, there is a pressing need to develop interactive teaching content that alleviates the steep learning curve. Intended Outcomes: The teaching strategy for the gamification in blockchain education is proposed, which positively influence students' cognitive well-being in terms of knowledge retention, cognitive curiosity, and heightened enjoyment. Application Design: Based on the experimental learning theory, the gamification of blockchain education, namely "BlockTrainHK", is implemented in the experimental learning cycle. Therefore, the gamified learning in experimental learning (GEL) strategy is proposed to examine the effectiveness of concrete experience, reflective observation, abstract conceptualization and active experimentation by two case studies. Findings: The results of the two-year study on the gamified blockchain education are encouraging: test groups using the GEL strategy were better in the cognitive well-being, and students' cognitive well-being is positively proportional to the level of individual technical knowledge and skills.

Teachers form expectations that can influence their students' performance, and there are a variety of ways these expectations can be communicated. In the current study, we tested a novel method for communicating expectations via examples of student work--examples that contain basic, entry-level work and communicate low, but manageable expectations or examples that contain complex, advanced-level work and communicate high and challenging expectations. Across three semesters, 91 college students in a data management course completed a class assignment that involved exploratory coding activities. Prior to the assignment, students were randomly assigned to view basic or advanced examples of student work. Students assigned to the advanced-examples condition reported higher perceptions of task difficulty and frustration, but they also exhibited higher levels of performance in terms of the complexity of their own work. Results suggest that setting challenging expectations can create a desirable difficulty that ultimately benefits students' performance in an authentic learning environment.

The aim of the study is the development of methodology for accurate estimation of electric vehicle demand; which is paramount regarding various aspects of the firms decision-making such as optimal price, production level, and corresponding amounts of capital and labor; as well as supply chain, inventory control, capital financing, and operational expenses management. The forecasting methods utilized include statistical techniques ("autoregressive integrated moving average" [ARIMA], and "polynomial regression"), machine learning ("nonlinear autoregressive neural network" [NAR]), "deep learning (long short-term memory [LSTM])", "hybrid and combination forecasting." With regard to the latter method, our study experiments with four different combining model approaches, including the introduction of an original, novel combining method with the employment of a transcendental LASSO function, which is used to form combinations of forecasts generated by the NAR, ARIMA, and polynomial regression models. The LASSO-based combining model proved superior to all other models, for the majority of forecast error statistics; where the root mean square error (RMSE) and mean absolute percentage error (MAPE) values are 4.5% and 8% respectively lower than the average level of the component model forecasts. The major implications of our empirical findings are that greater accuracy in demand forecasting can be achieved with a combining model approach, rather than reliance on any particular, singular model. Furthermore, given its superior performance, the employment of the studys LASSO-based combining model to forecast electric vehicle demand may lead to optimal firm decision-making over a range of organizational facets, which is predicated on accurate demand function estimation.

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 research purposes 1) to study teachers' competency in logistics and supply chain in vocational institutions, 2) to investigate teacher competencies in logistics and supply chain, and 3) to create and develop programs, 4) to strengthening teachers' competencies in logistics and supply chain. This research and development approach was separated into 3 phases; 1) teachers' competency in logistics and supply chain by experts; 2) requirement needs to develop the competency of teachers in logistics and supply chain in education institutes by experts and 3) applying the program for developing teachers' complacencies in logistics and supply chain. The sample group were 144 people, and 23 indicators of teacher competency, 2) Study current conditions revealed that teacher's competency as a whole at a whole highest and overall need was at an average level with (PNImodified) 0.36, 3) the results of creating and developing a teacher competency program for logistics and supply chain management in educational institutions the Vocational Commission contents, 4) development methods, and 5) program evaluations. The overall evaluation of the program was suitable, feasible, and useful. The results of the teacher competency shown; 1) knowledge, competence, the efficiency of the practice process/efficiency of knowledge outcomes with an average percentage of 93.01/92.83, which is higher than 80/80 criterion set and, 2) after development knowledge is higher which is equal 0.9014, which meant gaining more knowledge at 90.14 percent when applying with the target group before using the program, mean values of the teachers ([X-bar]=3.30, S.D.=0.50) and after using the program, the logistics and supply chain management was at the highest level.

Micro-credentials can provide easily accessible and transparent evidence of skills or knowledge that have been certified by an authority, based on small units of learning. The recognition and transfer of credits is becoming essential, as an increasing number of students are studying at different institutions, often at the same time, online or in traditional settings. "Blockchain is a type of database that stores data in an "open, peer-to-peer (P2P) network that favors communal functionality in lieu of a centralized controlling entity" (Columbia Engineering Bootcamps, 2021, para 5). The development of blockchain (https://theconversation.com/demystifying-the-blockchain-a-basic-user-guide-60226) holds promise of becoming a useful facilitator for supporting the storage and dissemination of micro-credentials on a global scale. Besides providing effective data security and privacy, blockchain can also facilitate maintaining and disseminating credentials, while ensuring that access is readily available for students under their control. Because of its immutability, blockchain can be used to confidently attest to students' accomplishments and is therefore particularly appropriate for micro-credentials.

This article examines the structural disparities between the archives at the University of Nigeria Nsukka (UNN) and Michigan State University (MSU). While Nigerian archivists work to preserve their institutions' local content, they must contend with cultural and infrastructural constraints foreign to their American counterparts. To elucidate these differences, this analysis builds upon Stoler's 'archival turn' framework which shifts the gaze on archives to consider them as subjects of inquiry rather than mere sources of data. Reflecting on my own experience working with physical archives at UNN and MSU, along with digital artifacts from these institutions' websites, I analyze the contents and accessibility of hardcopy and digital collections at both universities. In conclusion, I argue that the ongoing and uneven footprint of imperialism, both socio-cultural and infrastructural, results in an unequal distribution of Trouillot's 'archival power' amongst global institutions like UNN and MSU. Additionally, I highlight means by which some Nigerian scholars have contested imperialism to reclaim ownership over their own archival contents and narratives.

Many funding agencies require researchers to include a data management plan with their grant applications explaining how they intend to make the data generated from the research publicly accessible. University administration and campus service providers could potentially leverage the content of data management plans to facilitate compliance and reduce the burden on researchers. A case study at the University of Michigan demonstrates the promise of using data management plans as a communications and information sharing tool and the barriers in doing so. I apply the results of a content analysis to develop a series of recommendations to funding agencies, university administration, and campus service providers to improve the utility of data management plans in supporting data sharing and compliance.

Cloud computing has grown to become an integral part of information technology (IT) infrastructure. Organizations are increasingly utilizing cloud services to deliver a variety of applications and services in conjunction with their on-premise data center environments. As such, students pursuing careers in information systems and computing need to add cloud concepts and skills to their "tool belts" to meet the demands of employers. Amazon Web Services (AWS) has the largest market share of cloud providers. This paper reports on a systems administration course at a private liberal arts institution that was re-tooled to integrate cloud computing fundamentals using AWS as a platform for hands-on labs. Cloud computing concepts paralleled content for the AWS Cloud Practitioner Certification Exam, which students took at the end of the course. The course provided necessary skills for students in their development as information systems (IS) professionals, as well as important lessons for IS and computing educators as they consider how to incorporate cloud computing skills into their curricula.

Increasing and compelling research demonstrates the affordances of personal video footage as an informative and transformational tool in teacher professional learning (PL), yet many in-service teachers avoid engaging in this practice. This Australian Research Council funded study tracked teacher willingness to use video to capture the application of PL over 12 months in a rural Australian primary school. Data from questionnaires, video-based learning conversations, and collaborative sharing sessions demonstrated a strong increasing trend in the number of teachers volunteering to be videoed across three iterations of research. Thematic analysis highlighted five key factors as catalysts for increased teacher participation in engaging with video as a professional learning (PL) tool. These factors include -- safe relationships and the building of relational trust; personalized connection of PL to classroom practice; an effective video annotation repository system; teacher agency within an iterative structure; and time -- the need for external support systems. This study found that when these factors were addressed, willingness to engage in using the power of video as a tool to support teacher PL increased.

Faced the vast amount of information, choosing the appropriate materials is a prerequisite for effective self-directed learning. The recommendation algorithm is a kind of intelligent technology that can accurately locate the required information which the users care about most. However, many recommendation techniques experience can not be trained adequately in scenarios with small sample data and extremely sparse ratings. Moreover, DLRAs (Deep learning based Recommendation Algorithms) require high hardware support. The probabilistic graph (PG) can effectively represent the implicit complex relations among nodes, but it still has the problem of sparse data sensitivity. Therefore, we propose a Matrix-Factorization-based Probabilistic Graph Model for Recommendation Algorithm (MF-PGMRA): By matrix-factorizing the sparse rating matrix, the users and items are mapped to the user/item spaces, respectively; We employ the inner product to data-enhance and overcome the problems of sparse data and cold start; Then, we build Probabilistic Graph to construct the "user-item" latent spaces and estimate the probability distribution based on expectation maximization (EM), so as to predict the ratings; Finally, we built a library management system with the recommendation module to highlight the benefits of MF-PGMRA for students' subject learning. According to a questionnaire, we confirmed that the students are satisfied with the system from four aspects of speed, accuracy, usability and convenience, which can confirm that the library management system based on MF-PGMRA can efficiently and accurately recommend suitable materials for students from the huge amount of learning materials to improve students' self-directed learning efficiency.

Libraries at academic institutions have been involved in research data management services (RDMS) for more than ten years. Institutions have adapted their service models in response to funder, journal, and federal mandates that have consequently increased RDMS demand. However, institutions that hope to start or grow their services may have difficulty extrapolating from thepublished literature, as few studies recount RDMS development strategies.

Facility placement is of strategic importance to most organizations as a well-placed distribution center minimizes delivery costs and reduces fulfillment lead times, thus improving customer service levels. Because organizations value the location planning process, this teaching brief offers an exercise that analyzes the planning process using the center-of-gravity algorithm, a service area map, and real-world constraints. The objective of the exercise is to identify two locations within a service area that minimize total network distribution costs. Our exercise is intended to complement standard course content and support instructors developing curricula for undergraduate operations management and supply chain management courses. Student-based survey results indicate that the assignment enhanced classroom engagement and helped students better understand the complexities of location planning.

The study develops a method for monitoring and management of the quality of educational programs using software instruments. The method describes each of the monitoring implementation stages in detail specifying the input and output data, as well as the controls that affect the time and quality of the implementation of the corresponding stage. Algorithm programs in the form of flowcharts reflecting all the content aspects are developed and formalized for the automatization of monitoring. The presented algorithm models allow implementing the program complex of the system for monitoring and management of the quality of educational programs using the modern object-oriented design and programming environments. The goal of the study is to develop a model of algorithms for the organization of monitoring and managing the quality of educational programs, which allow reducing the time costs of these processes while increasing the objectivity of quality assessment. The obtained results are intended for the audit of educational services, public control over the implementation of educational activities, accreditation of directions of training, or licensing of educational organizations. The developed algorithms provide for evaluating the content of each stage of the audit of an educational program, generate a list of notes ranked by importance, and ensure the rational allocation of resources for the implementation of each stage of the educational process.

This study explores how blockchain technology can be applied in the area of training in organizations, the benefits it brings, and the management challenges that blockchain technology raises. By exploring the decentralized, transparent, and intelligent contract nature of blockchain technology, we analyzed the application of blockchain technology to organizational training. The results show that organizations can achieve training resource sharing, supply and demand balancing, training certification, and intelligent contract enforcement based on blockchain technology. However, it also presents potential challenges, mainly regarding engagement across sectors, support from all members, global technology rollout, staff competency, data confidentiality, and return on investment. Case and industry analysis further validates the content of our research and demonstrates the potential and challenges of blockchain technology in the field of organizational training.

This study aims to understand the challenges in adoption of blockchain technology in higher education institutions in India using the technological-organizational-environmental (TOE) framework. Blockchain brings transparency, efficiency in working systems, and leveraging trust. The benefits of blockchain are multifaceted and might be beneficial to educational institutions. However, the utilization of blockchain technology is presently in its nascent stage within the educational sector in India. This research employed a qualitative methodology involving semi-structured interviews with participants working in higher administration teams and IT teams in private universities in the Delhi-NCR region of India. The responses of the participants were analyzed using thematic analysis. The study found 10 main challenges that were categorized under the three dimensions of the TOE framework.

Open Educational Resources (OER) are valuable tools for diversifying teaching practices, contributing to a quality, equitable, open, and participatory education. However, unlocking the full potential of OER requires overcoming challenges related to its widespread adoption. One key strategy is empowering teachers to actively participate in the collaborative construction of high-quality OER collections that directly address their specific needs. This paper presents the results of a survey (N = 84) and a semi-structured focus group interview (N = 5) designed to collect teachers' perceptions of the critical factors to consider in designing a Community of Practice (CoP) focused on promoting sharing and digital curation of OER. The results highlight the importance of peer open review of shared OER, community-based evaluation based on pedagogical, technical, and scientific criteria, and the inclusion of OER metadata that mimics teachers' natural thinking. Furthermore, participants believe private feedback should be prioritised within these systems, as they perceive publicly shared comments might discourage future contributions. Although an expert's involvement in resource validation is prized, participants stated that this should not be limited to OER publication. Finally, the paper puts forward some recommendations regarding the design of digital platforms that support the work of a CoP focused on creating an OER repository.

Purpose: Informational conflict and uncertainty are common features across a range of sources, topics and tasks. Search engines and their presentation of results via search engine results pages (SERPs) often underpinned by knowledge graphs (KGs) are commonly used across tasks. Yet, it is not clear how search does, or could, represent the informational conflict that exists across and within returned results. The purpose of this paper is to review KG and SERP designs for representation of uncertainty or disagreement. Design/methodology/approach: The authors address the aim through a systematic analysis of material regarding uncertainty and disagreement in KG and SERP contexts. Specifically, the authors focus on the material representation -- user interface design features -- that have been developed in the context of uncertainty and disagreement representation for KGs and SERPs. Findings: Searches identified n = 136 items as relevant, with n = 4 sets of visual materials identified from these for analysis of their design features. Design elements were extracted against sets of design principles, highlighting tensions in the design of such features. Originality/value: The authors conclude by highlighting two key challenges for interface design and recommending six design principles in representing uncertainty and conflict in SERPs. Given the important role technologies play in mediating information access and learning, addressing the representation of uncertainty and disagreement in the representation of information is crucial.

Purpose: This study aims to present a Faculty-Led Program applied in two contrasting countries, the USA and Peru, focused on the supply chain management of food and beverages to demonstrate its benefits in human capital development. This Faculty-Led Program provides valuable opportunities to acquire skills and knowledge in foreign environments. Design/methodology/approach: Students from Universidad del Pacífico and Rochester Institute of Technology were exposed to the food and beverages industry in Lima and New York. The theory will be presented to justify the program's positive impact on the human development of the participating countries and empirical evidence of training capabilities that it allowed, according to the theoretical framework proposed by (Braskamp et al., 2009), to identify dimensions of learning. The study was based on primary data collected from 20 students from Universidad del Pacífico through a participant observation approach, retrieving a final essay project and the students' testimonies at the end of the program implemented in other similar studies in Peru (Simone, 2021). The data were categorized into three domains and then summarized to provide key insights. In this case, the methodology is qualitative, but the data were also subjected to statistical analysis. Findings: The results suggest that knowledge of the value chain of food and beverages obtained in this program was successfully consolidated. The learning outcomes from this method were obtained through students' projects aimed to share the learned global practices with the industry and were materialized in three domains: the cognitive domain, with students recognizing and valuing cultural aspects; the interpersonal domain, students learned from social interactions with stakeholders; and the intrapersonal domain, students showed high acceptance of US culture within the course context, though their affect toward it was more potent than toward their own culture. These domains allowed students to assess how such international experience impacted their learning in more than just the academic outcome. Research limitations/implications: The study relies on self-reported subjective methods in the short term since it summarizes students' perspectives, expressed in a final written essay, regarding three main dimensions of learning. Besides, the process assesses the improvement of those dimensions through a participant observation approach and collecting testimonies. More objective, comparable outcomes could be achieved in the medium term by evaluating the participants' performance in the business world. Originality/value: This paper presents a conclusive application of the Faculty-Led Program, which exposed students to the diverse food and beverage industry in Lima and New York, providing valuable insights through field studies and allowing them to experience both cultures and different realities. They recognized technological advancements and delays applicable to both countries, benefiting future managers and planners in workforce development. The firsthand experience taught students practical skills and perspectives for effective industry management. To the best of the author's knowledge, this is the first research in Peru focused on a short-term study abroad program based on the food and beverage supply chain industry to identify its value and contribution to a more holistic human capital development.