In order to evaluate the consistency of the knowledge areas (KAs) covered in the advanced certificate in engineering (AdvCertEng) course, this study used the Fuzzy Analytic Hierarchy Process (FAHP) technique. Both universities of technology and comprehensive universities in South Africa offer this subject. The primary requirements that an engineering programme should meet for the purposes of creating and implementing FAHP, are knowledge areas. The opinions of experts and decision-makers are prone to some subjectivity, imprecision, even some uncertainty and ambiguity, which results in fuzziness. Triangular fuzzy numbers (TFN1) between (1,1,1) and (9,9,9) are used to establish fuzzy pairwise comparisons between criteria on a qualitative level, whilst FAHP is used to calculate the weights of the criterion on a quantitative one. In this investigation, TFNs linked to a fuzzy distance from the crisp values of 1 are employed, and the related FAHP is denoted as FAHP1. The credit weight for each knowledge area is then calculated uniformly using the same method. AdvCertEng's existing knowledge area credit weights were generally confirmed using FAHP1. FAHP and ECSA's credit weights did, however, differ by minuscule amounts.

There are several popular note-taking methods, amongst which the Cornell note taking method is very well-known. The method consists of taking notes by dividing the page into three parts: the main notetaking part; the part summarizing themes, key-, and cue- words; and a part summarizing, in a few lines, contents. This article explores using the Cornell method, originally designed for students, as a means of pedagogy delivery for instructors. Hendel’s four pedagogic pillars, rooting pedagogic excellence in fundamental psycho-neurological processes, explain the success of the Cornell method as attributed to its encouraging executive function and optimal goal-setting techniques. The paper also examines the contrastive practices of some textbooks and confirms critiques of these approaches as employing lower levels of the Bloom- Anderson hierarchy.

Education for Sustainable Development (ESD) is crucial for equipping individuals with the competences needed to address the pressing social, economic, and environmental challenges of our time. Despite the recognized potential of service-learning in cultivating competences that can promote sustainable development, there is a lack of empirical research exploring the development of these competences among students. Hence, this study examined the effectiveness of service-learning as a pedagogical approach to ESD in fostering essential competences among students. The research involved 43 groups of students, who engaged in addressing various sustainable development issues through service-learning. A thematic analysis of students’ written reflections revealed the development of six key competences: systems thinking, anticipatory, normative, strategic, interpersonal, and intrapersonal competences. These competences were nurtured through real-world engagement that enabled students to understand complex, interconnected sustainable development issues, anticipate future challenges, set ethical and practical goals, plan and implement strategic solutions, collaborate effectively, and display resilience amid challenges. The findings show the transformative potential of service-learning in aligning education with the Sustainable Development Goals (SDGs) and preparing students to contribute meaningfully to sustainable development by addressing community issues, creating impactful initiatives, and promoting personal and social transformation.

Although there are several frameworks for the synthesis of form, and for the automated development of geometric shapes, studies in the systematic analysis of architectural forms and their automation are still underrepresented. This paper describes a framework for computer-aided geometric form analysis. It illustrates the framework’s applicability by an example from precedent architectural design.

The form analysis framework is developed theoretically and further translated into a computer code that is written in the AutoLISP language to fit its graphic operation system. Application of the framework and its computerized code demonstrates its power as a promising analytical tool that can help designers analyze precedents’ morphological structure more efficiently.

Transformative potential of the knowledge economy of the XXI century, establishment of networked society, emergency digitization due to the pandemic and wartime measures have imposed elaborate interdisciplinary and transdisciplinary demands on the marketability of Liberal Arts university graduates’ skills and competences, upon entering the workforce. The study is focused on the in-depth diagnostics of the development of multipurpose orientation, universality and interdisciplinarity of skillsets for students of European (English, Spanish, French, Italian, German) and Oriental (Mandarin Chinese, Japanese) Languages major programs through the span of educational activities in the time-frame of sustainable and emergency digitization measures of 2020-2024 in Ukraine. A computational framework of foreign languages education interdisciplinarity is introduced in the study. The survey analysis is used to evaluate the dimensions of interdisciplinarity, universality and transdiciplinarity, informed by the interoperability of soft skills and digital communication skills for Foreign Languages Education across contrasting timeframes and stages of foreign languages acquisition and early career training.

In this study, the writer, through her own twenty-four (24) years of teaching experience at a non-English University, discusses how challenging the transference of knowledge in interlinguistic communication is, that is, when non-English students, researchers, academics want to transfer knowledge from their local knowledge-based environment to a wider knowledge-based environment that uses English as a means of international communication (lingua franca). During her discussion, the author of this study shows that in order for the transference of knowledge in interlinguistic communication to be successful there must be three support systems: (1) a Human Intelligence (nous) who functions as a helper and/or mediator; (2) Artificial Intelligence (AI) in various forms; and (3) a mnemonic knowledge management tool (TDB) in an electronic form so that human knowledge acquired is not lost.

The Markov chain (MC) technique is used to make prediction of the ranking of a university in South Africa. The ranking is approached as a stochastic variable. The data were extracted from Scimago in the prediction process. A university was randomly selected to evaluate the level of prediction of the MC method. The university was relatively low ranked. The MC states for this study were adopted from a previous one, based on performance brackets. The Markov chain displayed a satisfactory level of prediction for the probability of a university moving from one level to another. The distribution of university rankings could be well defined to determine the performance of a university.

This pilot study aimed to identify the factors influencing corporations' willingness to establish Corporate Venture Capital (CVC) funds in regions outside core venture capital (VC) centers. Through content analysis, factors affecting the creation and continuation of CVC funds were identified and their interconnectedness was examined. These insights were applied to analyze the initial attempts of a major Latvian corporation to engage in CVC activities.

The evaluation of the fund established by the corporation revealed financial losses and a lack of strategic integration of portfolio companies' business ideas into the corporation's operations. However, the corporation's pioneering efforts in CVC activities in an undeveloped and unsupportive environment were acknowledged as beneficial to the broader ecosystem.

Several internal factors were identified as potentially detrimental to the fund's success, including limited interaction between the corporation's staff and the fund's portfolio companies and the corporation's partial state ownership.

The study highlighted the undeveloped state of the Latvian CVC market and the still-maturing VC market. Nonetheless, public funding for VC funds was a key catalyst for the corporation’s fund's development. The study suggests that enhancing government policies and incentives is crucial for encouraging CVC activities in regions with undeveloped CVC markets. Further research is needed to identify other potential market players and their obstacles for CVC activities.

There is a significant gap in the current acquisition and engineering workforce’s knowledge, skills, and support resources needed to address software and supply chain risk. This gap is widened by two factors: the growing reliance on software to handle system functionality and the exponential increase in cyber attacks. These factors underscore the importance of ensuring that all acquisition software functions as intended and is free from vulnerabilities that can create or contribute to existing cybersecurity issues. However, acquirers, developers, program managers, systems engineers, and decision makers typically lack the knowledge required to create and comply with these requirements. Determining who should be trained and how they should be trained has been an ongoing discussion in the software community for several years. In this paper, we summarize the efforts currently underway to address gaps in workforce knowledge, skills, and support resources based on recent publications and panel discussions held by the Software Assurance Supply Chain (SSCA) forum.

This research explores the crucial role of bridge makers in fostering the success of open innovations within innovation ecosystems. Emphasizing governance structures, this study highlights the importance of creating synergies among participants through effective intermediaries. Bridge makers act as connectors, facilitators, and integrators, crucial for fostering collaboration among diverse stakeholders, aligning interests, and overcoming barriers to innovation. By integrating the bridge maker role into ecosystem strategies, stakeholders can ensure that the connections formed are not only numerous but also robust, inclusive, and capable of driving long-term innovation and collaboration.

Given the fragmented nature of recent literature on the role of bridge makers, and the various terminologies used to describe similar roles, this research aims to provide a clear definition and comprehensive understanding of the bridge maker’s role. The objective is to analyze different aspects and names attributed to this role within the context of innovation ecosystems.

This paper concludes by discussing future research avenues that can build on the developed role typology, shedding further light on the process of open innovation ecosystem genesis. By incorporating the bridge maker role into the various ecosystem models, this research suggests that enhanced connectivity and synergy can be achieved, benefiting the entire ecosystem.

The Aurel_AI research project was born from the need to implement a virtual help desk for a university, providing accurate organizational information to both internal and external clients. The information includes details about academic programs, regulations, processes, and personnel. Aurel_AI is part of a broader research program on the use of AI in academia. Traditional solutions for a help desk, such as telephone call centers, present quality and efficiency issues that are difficult to solve. Call center staff generally lack comprehensive knowledge about the institution, rely on specific information that is sometimes outdated, require additional systems for information retrieval, and experience high turnover rates. This leads to associated costs and issues related with outdated information, resulting in inaccurate responses and long waiting times. Generative artificial intelligence models, known as Large Language Models (LLMs), offer an interesting alternative for an automated virtual help desk. These models can understand even vague and poorly structured questions and generate reasonably appropriate answers. However, they are not without flaws, as they tend to present issues like "hallucinations" when the required information is not present in their training data. To minimize this problem, it is crucial to ensure that the model has precise and comprehensive information, which needs a specific methodology for information collection, validation, and updating. Base models require an adaptation process to be used for specific cases, for which techniques like Fine-Tuning and Retrieval Augmented Generation (RAG) exist. Fine-tuning retrains a model’s weights with new specific information, while RAG uses both proprietary information—in this case, from the university—and publicly available internet data. Both techniques have pros and cons that need to be evaluated to select the most suitable option. They also demand appropriate and specialized infrastructure, which is often expensive. Thus, another challenge is to find a balance between suitable equipment and reasonable costs. The final system, from the user’s perspective, must be accurate, flexible, and adaptable to deliver a satisfactory experience. As the results show, Aurel_AI represents an advance in the digitalization of educational services, standing out for its ability to generate accurate and personalized responses. However, its current limitations, such as handling concurrent queries and hallucinations, underscore the need for adjustments to both infrastructure and data processing methodology. With strategic improvements, the system has the potential to consolidate itself as a replicable model for multiple university digital services.

In the digital transformation era, companies must foster adaptability and invest in modernizing their technological infrastructure. A key component of this shift is developing a robust data strategy, which presents implementation challenges in large organizations. We outline criteria for senior management to consider when crafting a data strategy, covering both offensive and defensive measures. While a hybrid approach is common among successful organizations, there's no one-size-fits-all strategy. Instead, companies should tailor their approach to their unique business needs. Our ongoing project, using Design Science methodology, aims to create a tool aiding senior management in selecting the most suitable strategy. This involves assessing sector-specific requirements, improving data management practices, and ensuring alignment across departments.