Programming Training Research Articles

АНАЛІЗ ЗАСОБІВ МОДЕЛЮВАННЯ МЕРЕЖ ЩОДО МОЖЛИВОСТІ ЇХ ВИКОРИСТАННЯ ДЛЯ ПРАКТИЧНОЇ ПІДГОТОВКИ ФАХІВЦІВ ІЗ КІБЕРБЕЗПЕКИ

Despite the existing information security systems, the key aspect of effective cyber defense remains the level of training of personnel responsible for cyber security. Today, the training of a cybersecurity specialist should be based on a comprehensive study of modern information technologies, mechanisms and patterns of cyberattacks, ways to counter them, and include both theoretical and practical components. It has been established that the most common practice in the leading educational and scientific institutions of the world and Ukraine in terms of practical training of cybersecurity specialists is the creation and deployment of complex software and hardware complexes - cyber training grounds, but this requires significant resources. Therefore, software tools for emulating and simulating computer networks are becoming an alternative to obtaining initial practical skills in cybersecurity. The article analyses three of the most popular free tools for simulating and emulating computer networks - Cisco Packet Tracer, GNS3 and EVE-NG - with regard to the possibility of their use for practical training of cybersecurity specialists. The analysis found that Cisco Packet Tracer, which is aimed at novice users, provides simulation of network devices exclusively from Cisco, allows you to configure basic protocols and practice the basics of cyber defence. GNS3 is slightly more advanced than Cisco Packet Tracer in terms of functionality, emulates real operating system images and supports many network device vendors, making it useful for complex training tasks. In addition, GNS3 provides the ability to recreate cyberattack scenarios, and the integrated Wireshark network analyser allows you to monitor traffic and analyse the course of a cyberattack on the system. In turn, EVE-NG is a powerful network emulation platform that is very close to GNS3 in terms of functionality. It also provides extensive hardware support and enables the deployment of complex network topologies. However, the main feature of EVE-NG is its client-server architecture, which enables multi-user operation. Thus, Cisco Packet Tracer, GNS3, and EVE-NG complement each other in the process of acquiring practical cybersecurity skills at different levels of education. The use of all three tools in training programmers will help to develop the comprehensive knowledge and practical skills necessary to effectively protect critical information infrastructure from cyberattacks.

Patient Satisfaction with the Empathic Communication Skills of Nurses at a Tertiary Care Hospital, Uttarakhand

Background and Aim Empathic communication has a great impact on patient satisfaction and health outcomes. With the advent of technology in healthcare human touch in caring for patients is diminishing gradually. This study explores the satisfaction of the patients with the empathic communication of nurses. Methods A descriptive cross-sectional study design was used to conduct the study. Data were collected by a self-structured 5-point Likert scale to assess the satisfaction of patients with the empathic communication skills of nurses in the month of August 2021. Results The mean age of the participants was 43.36 ± 15.76. 41% of respondents have an overall moderate satisfaction with the empathic communication skills of nurses, 33.33% had low satisfaction and only 25.7% had high satisfaction with empathic communication skills of nurses. Furthermore, a significant number of patients (87.5%) reported that their opinion was recognized and respected by nurses and more than 80% reported that nurses were good in communication. Conclusion This study provides significant data about one of the most important factors in the improvement of patient satisfaction. Nurse’s empathic communication skills can be improved and sustained by training programmers on regular basis.

Artificial intelligence as a tool for analyzing and classifying programming problems in the educational process

The article considers the use of artificial intelligence as a tool for analyzing and classifying programming problems in the educational process. An approach to automating the problem classification process is proposed, which takes into account their complexity, subject matter, and type. Particular attention is paid to the advantages of using AI technologies to increase the efficiency of programming training, in particular, adapting problems to the level of students' knowledge. Practical results of implementing the problem classification system are presented, which demonstrate its high accuracy and prospects. The article also outlines the possibilities for further development of this area, such as the creation of adaptive platforms and recommender systems. The conclusions of the article emphasize the importance of integrating artificial intelligence into the modern educational process.

Аналіз номенклатури мікроконтролерів для побудови елементів домашньої автоматизації

The subject of study and research in this article is the list of modern microcontrollers and technologies of the programming for creation elements of home automation, embedded systems, and components of Internet of Things. The goal is to analyze the product range and nomenclature of modern microcontrollers for creation of components of IoT systems and home automation considering an available resources and hardware implementation of interfaces. The tasks: to analyze a significant parameters of microcontroller for practical use; to analyze the product range and a modern manufacturers list of the most widely used microcontrollers; to analyze the main features of AVR microcontrollers; to perform an analysis of the advantages of STM32 microcontrollers; to analyze the capabilities of ESP32 microcontrollers; to perform the comparison of hardware resources of these three groups of microcontrollers. According to the tasks, the following results were obtained. Fourteen leading manufacturers of microcontrollers are analyzed with taking into account the bit length and a set of series and families of devices. The main characteristics and requirements for the practical application of microcontrollers for both the creation of embedded systems and for training and prototyping are highlighted. The reasons of the great popularity of the use of AVR microcontrollers by the community for training and learning of programming are identified. The capabilities of hardware resources and the advantages of using for embedded systems of the set of models of STM32 microcontrollers series are analyzed. The reasonability of the use of ESP32 microcontrollers for building of components of IoT systems and devices with Internet access is concluded. The comparison of the hardware resources of microcontrollers of three manufacturers is performed with taking into account the available size of program memory, the number of interfaces and pins. Conclusions. The main contribution and scientific novelty of the obtained results is that the performed analysis allows to simplify the process of a decision making about the selection of the required product range of modern microcontrollers for the creation of the components of the systems of home automation and Internet of Things with taking into account the available hardware resources, the number of pins, and the presence of hardware interfaces. This reduces the required efforts and costs at the initial stages of prototyping such systems, as well as during the porting to new microcontrollers and integrated environments of an already existing project.

Uniqueness of suspiciousness scores: towards boosting evolutionary fault localization

Context. Software is subject to the presence of faults, which impacts its quality as well as production and maintenance costs. Evolutionary fault localization uses data from the test activity (test spectra) as a source of information about defects, and its automation aims to obtain better accuracy and lower software repair cost. Motivation. Our analysis identified that the test spectra commonly used in research exhibit a high ratio of sample repetition, which impairs the training and evolution of Genetic Programming (GP) evolved heuristics. Problem. We investigate whether evolutionary training based on the uniqueness of suspiciousness scores can increase the ability to find software faults (defects), even in repeat-sample scenarios. Specifically, we examine whether the GP-evolved heuristic, which is based on the distinguishability of program elements in terms of faults, is really competitive. Methodology. The investigation formalized hypotheses, introduced three training strategies to guide the research and carried out an experimental evaluation, aiming to reach conclusions regarding the assessment of research questions and hypotheses. Analysis. The results have shown the competitiveness of all the proposed training strategies through evaluation metrics commonly used in the research field. Conclusion. Statistical analyses confirmed that the uniqueness of suspiciousness scores guides the generation of superior heuristics for fault localization.

Development and Implementation of a Web-Based Management Information System for Enhancing Computer Programming Training in Education

In the current era of information technology, web-based training systems are critical for enhancing the efficiency of training processes. This study focuses on the development of a Management Information System (MIS) tailored for computer programming training, utilizing a web-based training (WBT) platform. The primary objective is to introduce a framework for a web-based MIS that optimizes the management and delivery of computer programming courses. Computer programming education presents unique challenges, such as real-time participant tracking and dynamic content management, which are addressed by this MIS. The system was developed using the waterfall model, with data collected through interviews, observations, and requirements analysis. Key features include training schedule management, participant tracking, material organization, session management, evaluation tools, and reporting capabilities. Real-time feedback enhances participant engagement, while session management improves the overall learning experience. The web-based platform offers flexible access and simplifies the management of training processes, enabling users to track schedules, access materials, and monitor progress. Validation results show a high validity score (V = 0.883), exceeding the required threshold, and the materials received a validity score of 0.864, confirming their suitability for basic programming competency training at Medan State University. These results demonstrate the system’s effectiveness and potential for wider application, making it a valuable tool for improving the management and delivery of programming courses across various educational contexts.

Ethical Practices and Efficiency in the Internal Control of Peruvian Public Transport

The study aims to assess the impact of ethical practices on the effectiveness of internal control in public transport companies in Peru, to understand how these aspects influence corporate integrity, customer trust and corporate reputation; a quantitative, descriptive and explanatory methodology was used; data were collected through structured surveys applied to 50 employees of a transport company, covering various areas such as sales, administration and internal control; it is concluded that ethical practices significantly influence the effectiveness of internal control. Deficiencies in these areas lead to loss of customer confidence and financial and legal risks. The integration of sound ethical practices into business culture and processes improves management, customer confidence and business sustainability; highlights the need to improve integrity and operational efficiency in transport companies. It recommends implementing ethics training programmers and strengthening internal control systems adapted to the local context, as well as integrating advanced technologies for risk management and visualization.Corporate Governance

Micro: bit programming effects on elementary STEM teachers’ computational thinking and programming attitudes: a moderated mediation model

Cultivating computational thinking (CT) for K-12 students has become the central issue in the digital age. However, the most significant impediment to the long-lasting development of students’ CT is teachers’ lack of CT and positive programming attitudes (PA). Therefore, this research aimed to explore the effects of Micro: bit programming training activities on STEM teachers’ CT and PA. We conducted a quasi-experimental study with 55 elementary STEM teachers that included 12 Micro: bit programming training activities and measured changes in teacher CT and PA levels using the TCTS and TPAS. The results revealed that Micro: bit programming training activities effectively enhanced STEM teachers’ CT and PA. Further analysis showed that Micro: bit programming training activities mainly improved problem-solving and creativity in CT and cognition and beliefs in PA of STEM teachers. Meanwhile, we found that Micro: bit programming training activities benefited CT and PA enhancement for STEM teachers with high educational level and low teaching years. Furthermore, the findings indicated a partially mediated effect of STEM teachers’ PA in terms of educational level affecting CT, and teachers’ teaching years also significantly moderated the second half of this mediated effect. Generally, this research expands the training approaches of CT and PA for elementary school STEM teachers while clarifying the multifactorial influence mechanisms related to CT and PA, which can provide practical references for future STEM teacher training.

Development and Evaluation of an Internet of Things Project for Preservice Elementary School Teachers

Programming education is gaining more attention in elementary schools, especially through the use of visual programming tools and development boards. However, the elementary school teacher education in Taiwan allows only limited time periods for training in visual programming and the use of development boards. Development boards are ideal for creating internet of things (IoT) projects, and project-based learning (PBL) is an effective teaching strategy in programming education to promote active learning. Therefore, to sustainably cultivate 21st-century teachers, this study developed an IoT PBL activity for preservice elementary school teachers in Taiwan, so as to improve their attitude toward programming and to enhance their content knowledge of programming teaching, including in computational thinking concepts and knowledge concerning the micro:bit and IoT. This project aimed to engage preservice elementary school teachers in using the micro:bit and electronic modules to create cardboard games with IoT features. A preliminary evaluation was conducted within a teacher education course to verify the project’s feasibility. Consequently, the preservice elementary school teachers participating in this project could develop various IoT cardboard games through teamwork. Their scores on the assessments of computational thinking concepts, development board knowledge, and attitude toward programming showed significant improvement after the project activity. They also expressed highly positive feedback on the project. These findings verify that the proposed PBL activity could be feasible for elementary teacher education.

Design and implementation of an asynchronous online course-based undergraduate research experience (CURE) in computational genomics.

As genomics technologies advance, there is a growing demand for computational biologists trained for genomics analysis but instructors face significant hurdles in providing formal training in computer programming, statistics, and genomics to biology students. Fully online learners represent a significant and growing community that can contribute to meet this need, but they are frequently excluded from valuable research opportunities which mostly do not offer the flexibility they need. To address these opportunity gaps, we developed an asynchronous course-based undergraduate research experience (CURE) for computational genomics specifically for fully online biology students. We generated custom learning materials and leveraged remotely accessible computational tools to address 2 novel research questions over 2 iterations of the genomics CURE, one testing bioinformatics approaches and one mining cancer genomics data. Here, we present how the instructional team distributed analysis needed to address these questions between students over a 7.5-week CURE and provided concurrent training in biology and statistics, computer programming, and professional development. Scores from identical learning assessments administered before and after completion of each CURE showed significant learning gains across biology and coding course objectives. Open-response progress reports were submitted weekly and identified self-reported adaptive coping strategies for challenges encountered throughout the course. Progress reports identified problems that could be resolved through collaboration with instructors and peers via messaging platforms and virtual meetings. We implemented asynchronous communication using the Slack messaging platform and an asynchronous journal club where students discussed relevant publications using the Perusall social annotation platform. The online genomics CURE resulted in unanticipated positive outcomes, including students voluntarily discussing plans to continue research after the course. These outcomes underscore the effectiveness of this genomics CURE for scientific training, recruitment and student-mentor relationships, and student successes. Asynchronous genomics CUREs can contribute to a more skilled, diverse, and inclusive workforce for the advancement of biomedical science.

Accounting for Cognitive Impairment in Concurrent Disorders Treatment: Practical Resources to Meet the Needs of Our Most Complex Clients.

Much has been written about the interplay between mental health and substance use disorders. However, there is a third dimension, which often complicates the provision of care and renders many mainstream approaches less effective. Cognitive impairments, including those that arise from traumatic brain injury, are increasingly being recognized as an important consideration in addictions programming. This article will discuss the findings from a cross-sectorial partnership between the Centre for Addiction and Mental Health (CAMH) and Community Head Injury Resource Services of Toronto (CHIRS). Four recommendations for program administrators are proposed: (1) support screening for brain injury; (2) use free resources to train staff members to recognize, accommodate and address neurocognitive impairment; (3) establish cross-sector partnerships to facilitate collaborative programming and cross training for the most complex clients being served; (4) when developing new programming, include structures and behavioural interventions that have been shown to benefit individuals with cognitive impairment.

Impact of Resistance to Change and Organizational Structure on Employee Performance in Jordanians Banks: Case Study of Housing Bank for Trade and Finance

The study aimed to demonstrate the impact of resistance to change and organizational structure on employee performance. The study population consisted of all employees at the Housing Bank for Trade and Finance. The descriptive analytical approach was used to collect, classify, and analyze the data. The study sample size was 180 employees. A scale consisting of three axes was developed (resistance to change, organizational structure, employee performance). The results of the study showed a statistically significant positive impact of resistance to change on employee performance. The cognitive dimension had a significant positive impact, unlike the emotional and behavioral dimensions, which did not have a significant impact. The organizational structure also had a significant positive impact on employee performance. According to the study recommended a set of recommendations, including enhance employees' ability to adapt to changes. This can be achieved by providing training programmers’ and workshops that aim to enhance employees' adaptability and change management skills, enabling them to deal effectively with changes in the work environment. Additionally, management should play a key role in enhancing employees' awareness of the organizational structure and clarifying how it affects their performance. This can also be achieved through orientation sessions and workshops on the bank's structure and its impact on daily work.

How Low-Code Tools Contribute to Diversity, Equity, and Inclusion (DEI) in the Workplace: A Case Study of a Large Japanese Corporation

Learning and using technology in the workplace are essential for a company’s commitment to the sustainable development of its resources. Finding competent engineers who can handle information communication technologies (ICTs) is a challenge for companies. Currently, however, the ability to use these technologies is limited to technicians with specialized training, and not everyone can engage in development. Therefore, it is safe to conclude that equity in the use of technology has not yet been realized. This study aims to analyze, based on actual cases, the necessary conditions and mechanisms for people with diverse experiences and circumstances, not limited to engineers, to participate in ICT development to address human resource diversity. The use of technology such as low-code platforms (LCPs) that have recently emerged on the market has shown that nonprofessional engineers without programming training can participate in development projects. This research will be useful to managers in advancing Diversity, Equity, and Inclusion (DEI) strategies in their workplaces and contribute to organizational research regarding new trends in technology use by individuals: low codability. The findings of this study are of significant relevance to the Sustainable Development Goals (SDGs) of decent work and economic growth, as well as gender equality.

Easily porting material point methods codes to GPU

AbstractThe material point method (MPM) is computationally costly and highly parallelisable. With the plateauing of Moore’s law and recent advances in parallel computing, scientists without formal programming training might face challenges in developing fast scientific codes for their research. Parallel programming is intrinsically different to serial programming and may seem daunting to certain scientists, in particular for GPUs. However, recent developments in GPU application programming interfaces (APIs) have made it easier than ever to port codes to GPU. This paper explains how we ported our modular C++ MPM code to GPU without using low-level hardware APIs like CUDA or OpenCL. We aimed to develop a code that has abstracted parallelism and is therefore hardware agnostic. We first present an investigation of a variety of GPU APIs, comparing ease of use, hardware support and performance in an MPM context. Then, the porting process of to the Kokkos ecosystem is detailed, discussing key design patterns and challenges. Finally, our parallel C++ code running on GPU is shown to be up to 85 times faster than on CPU. Since Kokkos also supports Python and Fortran, the principles presented therein can also be applied to codes written in these languages.

Collaboration of Unplugged and Plugged Activities for Primary School Students: Developing Computational Thinking Skills with Programming

The study was carried out with 18 primary school students (11 girls, 7 boys) who participated in programming training conducted at a university. In this research, the implementation of programming activities in the whole classroom is a case study. While trying to understand the phenomena during the implementation of the activities in the study, a quasi-experimental design was carried out without a control group in order to determine the changes before and after learning and to investigate the research questions. In this quasi-experimental design, measurements were made both before the implementation (pre-test) and after the implementation (post-test). The results showed that the combination of plugged and unplugged programming activities help improve primary school students' computational thinking skills. At the end of the study, it was concluded that unplugged and plugged activities would be beneficial for primary school students when used together. Further research is needed to evaluate these activities separately, their role in providing the gains, and the students' thoughts about these activities. In addition, the effects of using different teaching methods in programming education can be examined.

Workplace Stress, Social Support and Coping Strategy as Predictors of Mental Well-Being among Nurses in Ibadan

This study examines workplace stress, social support and coping strategy as predictors of mental well-being among nurses in Ibadan North Local Government (LGA) Oyo State, Nigeria. Cross-sectional survey research design was adopted while purposive sampling technique was used to select the LGA. Data were collected using validated scales from 163 participants and analyzed using zero-order correlation statistics and multiple regression analysis to test four hypotheses which were accepted at p < .05 level of significance. The result revealed that significant others support and friends social support independently predicted mental well-being among nurses among study participants. Furthermore, coping strategy and workplace stress independently predicted mental well-being among nurses in the study population. Finally, workload stress, social support and coping strategy jointly predicted mental well-being among study participants. The study concluded that workplace stress, social support and coping strategy are robust predictors of mental well-being among nurses. It is recommended that management of health institutions should integrate training and education programmers that focus on coping strategy and stress reduction techniques that foster positive relationships with friends and significant others to enhance mental well-being among nurse’s workforce.

Pengembangan Proyek Pemrograman Medıa Pembelajaran Interaktıf Untuk Tugas Pemecahan Masalah Pelatihan Berpıkır Komputasıonal Mahasiswa Dengan Scratch

Media is needed in learning to attract and make it easier for students to understand the material being taught. Interactive learning media for computational thinking material through Scratch programming as an example of a block-based programming project assignment by applying computational thinking concepts for PGSD student training has not been researched in Indonesia. The research carried out aims to develop an example of a final programming project for interactive media learning computational thinking for PGSD student programming training as a valid and practical problem solving task using the Scratch program as well as the level of competency of the programming project being created. The research carried out is of the research and development type using the ADDIE model. The research participants were 40 students from a private university in West Sumatra. Data was collected using observation, interview, artifact analysis, and questionnaire techniques. The research instrument was a questionnaire with a Likert scale filled in by material, media and research subject experts. Analysis of research data was carried out in a qualitative descriptive manner. From the development research carried out, it was found that the final project example of interactive media programming for computational thinking learning which was developed for PGSD students' computational thinking training as a problem solving task received a very good score with a score of 85.5% from the validation of material experts, media and students, 85. 2% for product practicality, and makes it easier for students to created the program because the difficulty is at intermediate level.

Multimodal Robot Programming Interface Based On RGB-D Perception and Neural Scene Understanding Modules

In this paper, we propose a system for natural and intuitive interaction with the robot. Its purpose is to allow a person with no specialized knowledge and no training in robot programming to program a robotic arm.We utilize data from the RGB-D camera to segment the scene and detect objects. We also estimate the configuration of the operator's hand and the position of the visual marker to determine the intentions of the operator and the actions of the robot. To this end, we utilize trained neural networks and operations on the input point clouds. Also, voice commands are used to define or trigger the execution of the motion. Finally, we performed a set of experiments to show the properties of the proposed system.

The Quantification of Physical Performance and Internal Training Load in Youth Male Soccer Players During Preseason.

The monitoring of training loads and quantification of physical performance are common practices in youth soccer academies to support coaches in prescribing and programming training for individuals. The interaction between training load and physical performance is unknown during a preseason period in youth soccer players. The current study assessed changes in training load and physical assessments across a 4-week preseason period. The relationship between physical performance and match playing time in youth male soccer players was also investigated. The training loads of 25 professional youth academy male soccer players were monitored throughout a 4-week preseason period. Assessments of power, agility, speed, and aerobic capacity were undertaken in the first training session. Session ratings of perceived exertion (sRPE) and well-being questionnaires were collected during all training sessions and preseason matches. Playing time during subsequent competitive matches was recorded. T test and 30-m-sprint assessments, conducted on the first day of preseason, were predictors of sRPE throughout preseason (t test χ2/df = 2.895, poor adjustment; 30-m sprint χ2/df = 1.608, good adjustment). YoYo Test performance was related with changes in perceived fatigue (χ2/df = 0.534, very good adjustment). Faster players reported higher values of sRPE, and players with higher aerobic capacity reported higher levels of fatigue across preseason. Well-being, perceived fatigue and soreness, and sRPE decreased across preseason. Greater match durations were related to higher levels of fatigue during preseason (P < .05). The current study highlights the relationship between training load, physical assessments, and playing time. Coaches and practitioners can use physical test data at the start of preseason as an indication of players that report higher sRPE, perceived fatigue, and reduced well-being across preseason, supporting decisions around individualized training prescriptions.

Enhancing Educational Assessments: Score Regeneration through Post-Item Analysis with Artificial Intelligence

Over the years, the significant increase in candidates taking part in examinations and competitive exams has prompted the relevant bodies and institutions to reconsider their assessment approaches. This evolution largely stems from the growing prevalence of Artificial Intelligence (AI) and continuous technological advances. The primary aim of this research is to evaluate the effectiveness of Multiple-Choice Tests (MCTs) enhanced by AI through comprehensive item analysis followed by score regeneration focusing on the most discriminant items, aiming to strengthen assessment accuracy. The predominant adoption of MCTs has emerged, offering a practical and efficient solution for rigorously assessing a wide range of candidates. The success of this method hinges on the quality of its items. Therefore, ensuring the validity of such exams relies heavily on statistical analysis to select relevant items that are balanced in terms of difficulty and discriminatory power. Given the challenges of this analysis during test development, a new approach using score regeneration through an AI tool is proposed. This approach is based on a posterior statistical analysis of candidate performance with adjusted scores by eliminating the least discriminating items. The research sample was intentionally selected, consisting of computer science trainee teachers spread over the last three academic years. To validate this approach, a comparative study was conducted using the t-student’s test and the Spearman correlation coefficient on the grades obtained in algorithmic and programming training modules each year. The results demonstrate that incorporating this score regeneration phase considerably improves the credibility of MCTs-based assessments, providing a solid foundation for educational decision-making. The findings affirm the research objective by showing that AI-enhanced MCTs offer a reliable and valid method for large-scale candidate assessment.