A prominent medical school in the Southeast United States conducts an active International Medical Outreach Program (IMOP) at multiple international locations. These medical outreach trips provide medical services to those who do not have access to or limited access to health care. Medical students who volunteer to participate in these trips welcome the experiential education experiences. This developmental research study focuses on three IMOP trips to San Cristóbal, Galápagos Islands (Ecuador). Traditional approaches in the dissemination of clinical knowledge, skills, and confidence building for medical students rely on classroom training. In the IMOP experiential trips, knowledge sharing was supported by oral communication with senior clinicians and patients, as well as the transition from a paper-based to a novel custom-built Electronic Health Record (EHR) system. Paper-based record systems are cluttered with issues; some include illegible handwriting and missing or incomplete data. A team of health informatics professionals from the university transitioned the paper-based forms to a novel digitalized EHR system. The new novel digitalized EHR system resolved many of the paper-based issues and significantly improved knowledge dissemination among medical students, patients, and clinicians, furthering skills enhancement as well as efficiencies in resource coordination, however, some adjustments in clinical documentation procedures were needed to reduce the volume of missing data entries during the implementation, where a total of 848 adult and pediatric patients were treated over the three IMOP trips documented in this research. This digitalized EHR system enabled a more efficient transfer of knowledge to medical students.

This study aimed to analyze the relationship between environmental factors, Knowledge Management (KM), absorptive capacity, KM maturity level, and innovation capacity. This research used a descriptive survey of the field and was carried out from a quantitative perspective through an online questionnaire. Then, a multivariate exploratory factorial analysis was carried out, which was followed by Structural Equation Modeling (SEM) to identify and verify significant relationships, both analyses were done using Partial Least Squares (PLS). The PLS-SEM results indicated a high level of significance in the relationship between the organizational environment and KM and innovation capacity respectively. Regarding the hypotheses posed by the research model, positive influences were found in the relationships between environmental factors and knowledge transfer, knowledge transfer and maturity level, as well as maturing level and innovation capacity. Hypotheses involving absorptive capacity were also confirmed. The research framework highlights factors that impact KM and assist in their practical application to reach a high level of knowledge maturity, thus conferring a constant strategic advantage in terms of innovation capacity. A model including organizational environment, knowledge transfer, absorptive capacity, knowledge maturity, and innovation capacity has never before been tested to the best of our knowledge. As for implications for the private sector, this study illuminates how these factors are related, influence each other, and contribute to increasing KM maturity and innovation capacity within a company.

This paper investigates the dynamic interplay between Artificial Intelligence (AI) and human logic in the domain of mathematical problem-solving. By critically examining a series of case studies, we compare the efficacy of AI-generated solutions, particularly those offered by ChatGPT, against traditional human problem-solving methods. The study employs various mathematical challenges, ranging from abstract logical puzzles to applied numerical problems, to evaluate AI's problem-solving approach and alignment with human cognitive processes. Our analysis highlights instances where AI's computational strategies complement or diverge from human reasoning, shedding light on AI's potential and limitations in deciphering mathematical problems. Furthermore, we explore the implications of integrating AI tools in educational contexts, specifically their role in enhancing students' mathematical problem-solving skills. The paper aims to contribute to the ongoing discourse on the optimal utilization of AI in education, proposing a balanced approach that leverages AI's computational power while fostering the depth and creativity of human logic. Through this comparative study, we advocate for a collaborative model where AI and human reasoning merge to enrich the educational landscape, particularly in the teaching and learning of mathematics.

Cybersecurity continues to be a major concern and presents significant challenges for businesses, governments, nonprofits, and individuals. Organizations are working diligently to mitigate threats to these entities while the rate of cybercrime continues to increase in sophistication and reach. Current models in cybersecurity are becoming increasingly ineffective against the velocity, agility, and persistence of cyber adversaries. This challenge presents an opportunity to consider concepts and methods in knowledge management to strategically evaluate and prioritize adversarial cyber threat activities. This research aims to explore a conceptual framework designed to provide cybersecurity professionals with new models for knowledge management to increase the effectiveness of the detection, mitigation, and attribution of these threats. This conceptual approach draws from the literature on knowledge management and cybersecurity to integrate key concepts into a new theoretical framework. This paper presents a new hybrid model for cybersecurity that integrates core concepts of the classic Nonaka and Takeuchi Knowledge Spiral and the National Institute of Standards and Technology (NIST) Cybersecurity Framework augmented with emerging artificial intelligence and machine learning technologies. The development of a hybrid cybersecurity model combined with proven knowledge management strategies for continual knowledge creation and innovation represents an integrative model designed to address emerging cybersecurity challenges.

It seems that most educational systems nowadays are focused on just part of human intelligence (basically logical, mathematical, and lingual), which implies a lot of general assumptions and actions in the teaching process. As a result, many students are treated as untalented because their dominant intelligence is not the one valued in today’s schools. This causes both frustration and educational problems, not to mention the fact that many great abilities are being wasted due to being undiscovered. This article aims to investigate the possibility of using Artificial Intelligence (AI) to define individual intelligence profiles, which can be used to outline personal development paths in line with the specific set of talents of every human being. Based on the literature review, the authors have identified a need for further qualitative research aimed at projecting a roadmap focused on discovering the complete personality profile of everyone with the use of AI and then creating the optimal development path for people to reach their full potential. This will be very advantageous for both individuals and the whole society. We kindly invite all the researchers interested in implementing AI in holistic talent diagnosis and development to contribute to a common, systematic, and interdisciplinary research project that would aim at taking full advantage of AI opportunities for individuals, specific communities, and the whole society.

Software development is a domain that impacts numerous facets of the world. Careers in software development offer attractive financial compensation. However, the nature of software development jobs often requires sacrifices that may reduce job satisfaction, particularly due to ethical implications in the workplace. This paper examines how ethical perception is related to the job satisfaction of software developers. Using unique data from a 2018 survey of software developers, this paper employs ordinal logistic regression to measure the relationships between job satisfaction and various aspects of ethical perception, while controlling for age, gender, race and ethnicity, country, education level, undergraduate major, employment status, and salary. Job satisfaction among software developers is found to be positively related to ethical perception. Developers who uphold ethical standards by considering the ethical implications of the code they write, declining to write unethical code, and whistleblowing express greater job satisfaction. This study contributes to the field of disciplinary-based Knowledge Management (KM) by offering insights into the relationship between ethical perception and job satisfaction for software developers. The results can be applied in managerial decisions to improve employee engagement, retention, and productivity.