Problem-solving Capabilities Research Articles

Quantum Computing in Telecommunication—A Survey

Quantum computing, an emerging paradigm based on the principles of quantum mechanics, has the potential to revolutionise various industries, including Telecommunications. This paper explores the transformative impact of quantum computing on the telecommunication market, focusing on its applications in solving computationally intensive problems. By leveraging the inherent properties of quantum systems, such as superposition and entanglement, quantum computers offer the promise of exponential computational speedup and enhanced problem-solving capabilities. This paper provides an in-depth analysis of the current state of quantum computing in telecommunication, examining key algorithms and approaches, discussing potential use cases, and highlighting the challenges and future prospects of this disruptive technology.

Project-Based Learning through the STEM Approach in Elementary Schools: How to Improve Problem-Solving Ability

Problem-solving ability is a fundamental competence that must be mastered by students. Consequently, the educational orientation across various stages of learning should emphasize the development of this competence. The objective of this study is to enhance problem-solving skills among sixth-grade students at SDN Munjul 03 through the implementation of Project-Based Learning model with a STEM (Science, Technology, Engineering, and Mathematics) approach. The research approach employed is quantitative, employing a pre-experimental design with a one-group pretest-posttest design. The research sample comprises 41 sixth-grade students at SDN Munjul 03. Data for this study were collected through observation, interviews, and tests. The findings of the research reveal that the average scores in the problem-solving skills test after the implementation of the Project-Based Learning model with the STEM approach are significantly better than before. Descriptive analysis of these results indicates a notable enhancement in problem-solving skills among students following the Project-Based Learning treatment with a STEM approach. The results of the hypothesis testing, utilizing the paired sample t-test method, also indicate that the difference between pre-treatment and post-treatment problem-solving skills test scores is statistically significant. Consequently, it can be deduced that a tangible improvement has occurred in the problem-solving abilities among the experimental class students. The conclusion drawn from this study is that the Project-Based Learning model with a STEM approach is effective in elevating problem-solving skills. The implementation of the Project-Based Learning model through the STEM approach can be regarded as one of the alternative solutions available to educators for enhancing students' problem-solving capabilities.

How Important Psychological Safety is in Supporting Strategic Management to Achieve Success: A Narrative Literature Review

Psychological safety plays a crucial role in enhancing strategic management processes and outcomes. Psychological safety encourages open and honest communication among team members and leaders. When individuals feel safe to share diverse perspectives, it fosters the generation of innovative ideas, facilitates effective decision-making, and improves problem-solving capabilities within strategic management teams. Psychological safety cultivates a supportive and inclusive work environment. It encourages active participation and collaboration among team members, resulting in increased trust, stronger team cohesion, and improved overall team performance. Organizations can enhance their strategic management practices and ultimately achieve sustainable competitive advantage by creating an environment that promotes open communication, inclusivity, risk-taking, and employee well-being. Understanding and prioritizing psychological safety within the strategic management framework is crucial for organizations aiming to thrive in an increasingly complex and uncertain business landscape.

고등학교 기하 수업의 교수⋅학습 자료 개발

Objectives The purpose of this study is to develop and apply teaching and learning materials for geometry class using process-centered assessment and to explore ways to implement process-centered assessment in high school classes. Methods Teaching and learning materials for geometry class using process-centered assessment were designed based on previous research on process-centered assessment and analysis of curriculum competencies according to the steps of the ADDIE model. In addition, the materials were developed for the entire scope of geometry so that they can be continuously assessed in all class periods, not as a one-time assessment after class. It was applied to 96 students in the third grade of E High School in Seoul, Korea, and the developed materials were evaluated through student evaluations, surveys, and interviews. Results The teaching and learning materials for the geometry class were designed considering the three conditions (task, interaction, and feedback) for implementing process-centered assessment, and a total of 30 process-centered assessments were developed. A total of 30 process-oriented assessments were developed, and a method for feedback on the results of process-oriented assessments was presented. Conclusions Through the process-centered assessment designed considering achievement standards and problem-solving capabilities, teachers were able to observe students' learning process and status, and students responded positively to problem-solving. In addition, interaction and feedback were actively carried out, which was effective in improving classroom atmosphere.

Beyond The Maritime Education Classrooms: Analysis Of Life Skills Gained From Maritime Trainings

Intensive maritime education and training cultivate the competence of students in their future career. As the industry evolves, it also requires professionals who can apply their skills in real-life scenarios. This investigation explored the life skills gained from maritime trainings by analyzing the experiences of maritime students (n=15). The participants in the one-on-one interview were purposively sampled based on several demographic characteristics i.e., a college student, have maritime units (>50), have been in curriculum-specified trainings. Findings of the study indicated that maritime students gained life-essential skills, including career-based, health-related, and emergency skills, through undergoing rigorous training programs. These acquired skills empower students to effectively address practical challenges and contribute positively to their career progression, personal growth, and well-being. As maritime students undergo specialized training and gain proficiency in technical and non-technical skills, their self-confidence and self-efficacy in addressing challenges and excel in their careers could be enhanced. The students' recognition of the practical use of their acquired skills in real-world scenarios highlights their self-efficacy, influencing their motivation, critical thinking, and problem-solving capabilities. It is the responsibility of maritime education industry to raise awareness and provide comprehensive education to aspiring seafarers.

Integrated team approach to decommissioning Environment Plan development

The offshore oil and gas industry is facing a significant transition period in the coming decades due to the evolving energy market and aging oil and gas infrastructure. Industry has over 1000 offshore wells to plug and abandon, 57 fixed facilities and over 8000 km of subsea lines to decommission over the coming decades. Most of this significant portfolio is regulated by NOPSEMA (National Offshore Petroleum Safety and Environmental Management Authority) with the expectation that decommissioning involves the full removal of equipment as per Section 572 of the Offshore Petroleum and Greenhouse Gas Storage Act 2006 (Cth) (OPGGS Act). However, other options may be considered if the titleholder can demonstrate that an alternative decommissioning approach delivers equal or better environmental and safety outcomes compared to complete removal. Integration of environment and engineering functions primarily occurs during the process of developing an Environment Plan (EP) and, specifically, the process of identifying environmental hazards (Environmental Hazards Identification, ENVID) and mitigation measures. This paper proposes that improved stakeholder, regulatory, cost and environmental outcomes could be achieved through an earlier integrated approach to planning decommissioning activities. Specifically, co-designing an approach to decommissioning at the earliest stages would inform, for example, approvals strategy and equipment selection. This would ultimately result in improved outcomes without the application of mitigating control measures. The paper will discuss some of the current challenges and outline the value of early identification and understanding of key environmental values and sensitivities to ensure site-specific information is considered during planning stages, later streamlining EP development. A multi-disciplinary decommissioning team in the early stages of project development enhances problem-solving capabilities and ultimately improves environmental and safety outcomes.

Using a Multi-Agency Response Framework During COVID19 by Emergency Managers in a Healthcare Organization

Introduction:The paper provides the perspective of emergency managers within a healthcare service, using a multi-agency framework to coordinate a regional response to COVID 19. While health services play a role in the planning, response and recovery to major emergencies they are rarely the lead in coordinating the response. The exploration of existing research through Pauchant and Mitroff Onion Theory is combined with the challenges and experiences faced by emergency managers during the COVID 19 response in Ireland. The research mirrors the experience of emergency managers that preparedness and relationship building are key to quickly establishing a response. However the experience of emergency managers was that although shared situational awareness is critical a flexible system framework is required, particularly in a prolonged pandemic situation. A hierarchical command and control system can negatively impact on strong local relationships and problem solving capability. The experience of emergency mangers concurs with research that the development of a learning organization is pivotal in information preparedness before and during the response and recovery phase. The challenges of implementing lessons learned across a national health service can be challenging especially during an extended response phase.Method:A deductive manifest analysis approach was adopted to carry out a qualitative thematic content analysis of exercise reports and emergency debrief reports.Results:Research QuestionsLessons learned in the five years prior to COVID 19 enhanced the response to the pandemic emergency–yes there are several examples of how lessons learned can improve response to seemingly unrelated emergencies.The principals of the MEM Framework in Ireland are applicable to a pandemic emergency–yes but this is dependent on local arrangements and relationships to allow flexibility in the implementation of the framework.Conclusion:Regular training and exercising as well as a debriefing of exercises and real emergencies enhances preparedness for emergencies.

Deep reinforcement learning-based active flow control of vortex-induced vibration of a square cylinder

We mitigate vortex-induced vibrations of a square cylinder at a Reynolds number of 100 using deep reinforcement learning (DRL)-based active flow control (AFC). The proposed method exploits the powerful nonlinear and high-dimensional problem-solving capabilities of DRL, overcoming limitations of linear and model-based control approaches. Three positions of jet actuators including the front, the middle, and the back of the cylinder sides were tested. The DRL agent as a controller is able to optimize the velocity of the jets to minimize drag and lift coefficients and refine the control strategy. The results show that a significant reduction in vibration amplitude of 86%, 79%, and 96% is achieved for the three different positions of the jet actuators, respectively. The DRL-based AFC method is robust under various reduced velocities. This study successfully demonstrates the potential of DRL-based AFC method in mitigating flow-induced instabilities.

초등학생의 실생활문제해결역량 발달을 위한 앙트러프러너십 교육프로그램 개발과 실행 효과

Objectives This study was to develop an entrepreneurship education program for the development of real-life problem-solving competences in elementary school, and to investigate the effects after conducting classes.
 Methods For the development of an entrepreneurship education program, a draft was devised through literature research and learner's demand analysis. And the final draft was developed through expert evaluation of the draft. Introspection data were collected during the course of class in this program. After class, 25 participating students were divided into 6 groups, and focus group interviews (FGI) were conducted. The data collected in this way were analyzed according to the content analysis method to find out the effectiveness of the educational program.
 Results Through the classes of the entrepreneurship education program, the students went through the 16 class hour. In this process, students were able to develop application and analysis of knowledge, communication skills, creativity, leadership and execution skills. In addition, in the process of problem-solving, students were able to obtain positive effects such as challenging spirit for difficulties, positive self-awareness, and self-efficacy.
 Conclusions The point of entrepreneurship education program is to find empathic problems in real life, create solutions, and put them into practice. Entrepreneurship education program is useful as an educational method to develop competencies necessary for the future society. Entrepreneurship education is to discover and define problems from unstructured situations in real life spaces, and to directly practice solutions created while interacting through team activities. Entrepreneurship education is an educational method that internalizes problem-solving capabilities and is an essential method for fostering future social capabilities.

A Survey on Security Threats to Machine Learning Systems at Different Stages of its Pipeline

In recent years, Machine learning is being used in various systems in wide variety of applications like Healthcare, Image processing, Computer Vision, Classifications, etc. Machine learning algorithms have shown that it can solve complex problem-solving capabilities close to humans or beyond humans as well. But recent studies show that Machine Learning Algorithms and models are vulnerable to various attacks which compromise security the systems. These attacks are hard to detect because they can hide in data at various stages of machine learning pipeline without being detected. This survey aims to analyse various security attacks on machine learning and categorize them depending on position of attacks in machine learning pipeline. This paper will focus on all aspects of machine learning security at various stages from training phase to testing phase instead of focusing on one type of security attack. Machine Learning pipeline, Attacker’s goals, Attacker’s knowledge, attacks on specified applications are considered in this paper. This paper also presented future scope of research of security attacks in machine learning. In this Survey paper, we concluded that Machine Learning Pipeline itself is vulnerable to different attacks so there is need to build a secure and robust Machine Learning Pipeline. Our survey has categorized these security attacks in details with respect to ML Pipeline stages.

Micro-alloyed Mg-Ca: Corrosion susceptibility to heating history and a plain problem-solving approach

The exceptionally low corrosion rate (∼0.1 mm y–1 in concentrated NaCl solution for 7 days) enables lean Mg-Ca alloys great potential for diverse applications, particularly if relevant properties (e.g. mechanical strength, electrochemical performance, etc.) can be enhanced by thermomechanical processing. However, herein it is demonstrated that the corrosion performance of lean Mg-Ca is susceptible to the heating process. The corrosion rate of Mg-0.15 wt% Ca alloy is remarkably accelerated after annealing even for a short time (4 h at 400 °C) because Fe precipitation readily takes place. Fortunately, it is found that micro-alloying with dedicated additional elements is able to solve this problem. Nevertheless, the problem-solving capability is dependent on the element category, particularly the ability of the alloying element to constrain the Fe precipitation. Among the three studied elements (i.e. Sn, Ge and In), only In shows good competence of restricting the formation of Fe-containing precipitates, thereby contributing to retention of the superior corrosion resistance after annealing even at a rigorous condition (24 h at 450 °C). The finding creates good foundation for follow-up work of developing lean Mg-Ca-based alloys combining high corrosion resistance, superior electrochemical performance with excellent mechanical properties for applications as biodegradable implants and anode materials for aqueous batteries.

PENERAPAN MODEL PEMBELAJARAN CONTEXTUAL TEACHING AND LEARNING (CTL) UNTUK MENINGKATKAN KEMAMPUAN KONEKSI DAN PEMECAHAN MASALAH MATEMATIS SERTA SELF REGULATED LEARNING SISWA

The study is intended to examine the issue of increasing the capability of connection and mathematical problem solving and self regulated learning (SRL) students through the learning of contextual teaching and learning (CTL), in terms of overall student and Early Math Ability category (KAM) students (high, medium, low). The research method is the mix method range of embedded. The population in this study are all the students of SMK Nur Pandeglang and Human Samples randomly selected two classes, namely class X 2 TKJ as class experiments, and class X 1 of the control class as TKJ. Instruments in this research in the form of a test and non-test. 6 the question of mathematical ability test connection, and 4 the question of mathematical problem solving ability tests, while tests of non instrument in the form of the now self regulated learning, observation sheets, and interviews. The results of this research were: 1) increased ability of Mathematical connections students who learn learning Contextual Teaching and Learning (CTL) is better compared to conventional learning when are reviewed from tegori Early Mathematical Ability (KAM) students; 2) increased Mathematical problem solving abilities students who learn learning Contextual Teaching and Learning (CTL) is better compared to conventional learning when are reviewed from tegori Early Mathematical Ability (KAM) students; 3) self regulated learning students who learn learning Contextual Teaching and Learning (CTL) is better compared to conventional learning: 4) there is a relationship between the ability of problem-solving and mathematical connections assembled and self regulated learning.

Socio-inspired evolutionary algorithms: a unified framework and survey

It is well recognized that human societies and their problem-solving capabilities have evolved much faster than biological evolution. The inspiration from human behaviors, knowledge exchange, and transformation has given rise to a new evolutionary computation paradigm. Multiple research endeavors have been reported in the literature inspired by the diverse aspects of human societies with corresponding terminologies to describe the algorithm. These endeavors have resulted in piles of algorithms, worded differently but with more or less similar underlying mechanisms causing immense confusion for a new reader. This paper presents a generalized framework for these socio-inspired evolutionary algorithms (SIEAs) or socio-inspired meta-heuristic algorithms. A survey of various SIEAs is provided to highlight the working of these algorithms on a common framework, their variations and improved versions proposed in the literature, and their applications in various fields of search and optimization. The algorithmic description and the comparison of each SIEA with the general framework enable a clearer understanding of the similarities and differences between these methodologies. Efforts have been made to provide an extensive list of references with due context. This paper could become an excellent reference as a starting point for anyone interested in this fascinating field of research.

Long-Term Matching Optimization With Federated Neural Temporal Difference Learning in Mobility-on-Demand Systems

Efficient bipartite graph matching of orders and drivers is a central operational problem in industrial mobility-on-demand (MOD) systems. Traditional studies adopt pure combinatorial optimization models for order-and-driver matching, which do not consider the long-term rewards of the dynamic MOD decision making process. Toward long-term optimization, this article presents a systemic paradigm of online matching with federated neural temporal difference learning (FedTDLearning), which encompasses learning and matching phases. During the learning phase, the long-term matching process is modeled as a Markov decision process, which is typically solved by employing data-driven reinforcement learning in an offline central training scheme. Massive amounts of data would be generated on the network by industrial MOD systems. It is impossible to send all the large-scale industrial data to the cloud server for centralized model training due to network bandwidth limitations and safety concerns. Therefore, a generic and innovative FedTDLearning is proposed to achieve long-term matching in a distributed manner. During the matching phase, a real-time bipartite matching optimization problem is formulated to maximize the learned spatiotemporal value and minimize the pickup distance, which is reducible to the minimum-cost maximum weight bipartite graph matching problem. A distance-learned-value ratio algorithm is proposed to find an optimal matching in the bipartite graph based on the joint optimization of FedTDLearning and the combinatorial fractional programming approach. Furthermore, to pursue optimal computation efficiency, we solve the real-time matching problem by constructing a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -nearest neighbor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(k$ </tex-math></inline-formula> NN) bipartite graph where each order is connected with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> NN drivers. Using openly available real-world data, the prototype system and experimental evaluations show that our proposed algorithms have effective problem-solving capability in practice.

A deeper generative adversarial network for grooved cement concrete pavement crack detection

Periodic grooved cement concrete pavement crack detection is of great importance for pavement condition monitoring and maintenance. The current state-of-the-art (SOTA) detection solutions highly depend on datasets. However, due to the limited access to crack images, more efficient methods are urgently needed to advance the detection of cracking on grooved cement concrete pavement. This study proposes an improved deeper Wasserstein generative adversarial network with gradient penalty (WGAN-GP) to generate datasets of pavement images with a size of 512 × 512 pixels 2. Poisson bleeding is adopted to create the synthesized grooved cement concrete pavement crack images based on the generated crack images and groove images. The robustness of the proposed improved deeper WGAN-GP model is validated by Faster R-CNN, YOLOv3, and YOLOv4 models trained on original crack images and generated crack images for region-level detection. U-Net and W-segnet are used to achieve pixel-level crack detection to evaluate the effectiveness of proposed model. Results show that the improved deeper WGAN-GP could generate more realistic transverse, longitudinal and oblique crack images. In addition, the Poisson bleeding algorithm contributes to synthesizing grooved cement concrete pavement crack images. Moreover, it is observed that YOLOv3 trained by the augmented dataset could achieve a mean average precision (MAP) of 81.98%, 6% MAP higher than the non-augmented dataset. U-Net and W-segnet benefit from augmented dataset with a better pixel-level segmentation result. Based on the results, it can be concluded that the improved deeper WAGN-GP image generation method can provide a straightforward way to fill the data shortage gap of grooved cement concrete pavement cracks, thus increasing the problem-solving capability of the SOTA crack detection models.

Considerations in Preparing Social Work Students to Thrive in Health Care Settings

ABSTRACT Over a quarter of the members of the social work profession are working in health related settings yet preparing students to work in such multi-disciplinary environments, with hierarchical organizations and problem-focused systems, can create value conflicts, principally with the strengths-based paradigm inherent in social work practice. In order to prepare social work students for delivering services that honor the profession’s ethics, values, and principles in medical environments, a focused academic curriculum and field experience are warranted. This conceptual paper aims to inform social work educators about the unique considerations for preparing students to practice in health care settings. We address how the underlying influence of the biomedical model, organizational culture, and billing and reimbursement services within the medical context can challenge social work values and practice. However, we illustrate how the Integrated Behavioral Health model can be applied to help students utilize clients’ inherent strengths and problem-solving capabilities while they navigate the terrain of multi-disciplinary medical environments.

Artificial Intelligence: An Innovative Approach in Orthodontics: A Narrative Review

The present article aims to describe how Artificial Intelligence (AI) assists orthodontics with its potent algorithms for identification and prediction, aiding medical professionals in making better treatment choices. AI is a valuable tool for helping orthodontists determine the best approach for moving teeth with orthodontic appliances to predetermined positions. Symbolic AI, an expertise system based on human comprehension of a problem, organises knowledge into algorithmic structures. While it remains applicable for problem-solving with limited potential outcomes and the need for human explainability, building rule-based models in complex healthcare scenarios with multiple explanatory variables proves exceptionally challenging, if not impossible. However, modern AI often overlooks oral disorders, fails to fully incorporate facial analysis into its models, and neglects functional issues when developing remedies. Nonetheless, AI does improve imaging, diagnosis, specificity, and more in various situations, from identifying syndromes to detecting caries. Orthodontic diagnosis is complex, involving the simultaneous assessment of multiple facial features from different perspectives. Digital dentistry tools and AI-driven automation solutions have streamlined the process by digitally recording patient history and reducing diagnostic variations, benefiting both diagnosis and treatment. With its problem-solving capabilities, AI is starting to provide orthodontists with more powerful resources to deliver higher standards of care. AI-based technology can be utilised to gain new insights from various types of medical data. The present article aims to provide a concise overview of the use of AI in orthodontic care. The literature review is divided into six categories: extraction or non extraction therapy in orthodontic treatment, orthognathic surgery, segmentation and landmark identification, growth prediction, cleft-related studies, and Temporomandibular Disorders (TMD) classification.

Towards a technology acceptance methodology for Industry 4.0

Industry 4.0 fuses ubiquitous computing and leads to a culmination of physical, digital, and biological paradigms. Previously inanimate objects are enabled to “talk” to each other and to the users, and guide specific behaviours of speed, breadth, depth, and systems impact. Research suggests however that 70% of large-scale technological change programs don't reach their stated goals. Current theories and methodologies including Technological Transitions (TT), Digital Transformation (DT), Technology Acceptance Models (TAM, TAM2 & UTAUT), Multi-Level Perspectives (MLP), come with challenges and limitations. Management and key decision makers need new tools that will assist them to identify which factors their companies must consider to efficiently adapt to Industry 4.0. The aim of this paper is to address existing TAM, DT and MLP challenges, and propose an Industry 4.0 specific digital transformation model, involving business and management practices. Ideas, best practices and different prospective, from diverse markets and industries, will be mitigated and combined. The synergetic methodology will support management, enhance organizational problem-solving capabilities, and provide recommendations to formulate a strategic approach based on company lifecycle, corporate governance, enterprise culture, change management, company size and structure. Key lessons learned will help in forming evolutionary perspectives specific to the needs and challenges of Industry 4.0 transitions.

Applying the Innovative Approach of Employing a Business Simulation Game and Prototype Developing Platform in an Online Flipped Classroom of an Entrepreneurial Summer Course: A Case Study of UAEU

As opposed to only having subject knowledge, the necessity of skills has repeatedly been emphasized as essential to succeed in the practical world. Being able to adjust to new circumstances is crucial, especially in today’s world, where uncertainty, volatility, ambiguity, and complexity are ubiquitous. Experiential Learning Theory can be implemented during innovative pedagogical approaches to better prepare students for entering the market as successful entrepreneurs in such a tumultuous time—for instance, an entrepreneurial course might incorporate using business simulation games, such as MonsoonSim and prototype developing software, including Justinmind to experience enhanced experiential learning with thematic goals. In order to strengthen the quality of teaching and learning and foster self-directed learners better equipped to cope with existing challenges, this study investigates the processes of implementing a business simulation game along with prototype development software and distinguishes it from a typical classroom experience. The sample consists of students enrolled in a short summer entrepreneurial course designed by the United Arab Emirates University at the request of the Ministry of Education, United Arab Emirates (U.A.E.), for secondary and higher secondary school graduates. The students from private and government schools across all seven emirates of the United Arab Emirates participated in this course. The online flipped classroom was carefully designed by blending several approaches during the pre-class, in-class, and post-class activities. In order to provide an advanced learning experience, a web-based business simulation game (MosoonSim) and online prototype development software, Justinmind, were introduced during the course. The qualitative and quantitative results show that incorporating business simulation games had a significantly positive impact on students’ learning outcomes, such as critical and higher-order thinking, idea creation, and problem-solving capabilities, and improved engagement through an easy, enjoyable, and interactive environment. Furthermore, findings show that the learning outcomes are significantly influenced by the attributes of the group members and their consistency during group activities in a flipped classroom, and assigning a dedicated instructor or a senior group member having solid background knowledge in a particular subject can assist in significantly enhancing the learning outcomes of a whole group.

Educational goals and objectives of nursing education programs: Topic modeling

Purpose: This study aimed to understand the keywords and major topics of the educational goals and objectives of nursing educational institutions in South Korea.Methods: From May 10 to May 20, 2022, the educational goals and objectives of all 201 nursing educational institutions in South Korea were collected. Using the NetMiner program, degree and degree centrality, semantic structure, and topic modeling were analyzed.Results: The top keywords and semantic structures of educational goals included ‘respect for human (life)-spirit-science-based on, global-competency-professional nurse-nursing personnel-training, professional-science-knowledge-skills, and patients-therapeutic care-relationship.’ The educational goals’ major topics were clients well-being based on science and respect for human life, a practicing nurse with capabilities and spirit, fostering a nursing personnel with creativity and professionalism, and training of global nurses. The top keywords and semantic structures of the educational objectives included ‘holistic care-nursing-research-action-capability, critical thinking-health-problem solving-capability, and efficiency-communication-collaboration-capability.’ The educational objectives’ major topics were ‘nursing professionalism, communication and problem-solving capability; a change of healthcare environments and a progress of nursing practices; fostering professional nurses with creativity and global capability; and clients’ health and nursing practice.’Conclusion: Educational goals in nursing presented specific nursing values and concepts, such as respect for human life, therapeutic care relationships, and the promotion of well-being. Educational objectives in nursing presented the competencies of nurses as defined by the Korean Accreditation Board of Nursing Education (KABONE). Recently, the KABONE announced new program outcomes and competencies, which will require the revision of educational goals. To achieve those educational objectives, it is suggested that the expected level of competencies be clearly defined for nursing graduates.