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The purpose of this paper is to evaluate the effectiveness of role playing as an applied learning technique for enhanced classroom experiences as compared to traditional lecture methods.

This study uses the pre-test/post-test design to conduct experiments with several control and experimental groups. Subjects are graduate students in an MBA program at a private, non-profit university in a traditional classroom setting.

Students in the experimental group gained significantly more knowledge (post-test minus pre-test scores) – 45 percent higher – through participation in the role playing exercise as compared to the control group.

This study represents only a single educational discipline explored using a single role playing learning activity. Impacts on the long-term retention of the knowledge should be studied further.

Educators should enhance their classroom experience with more applied learning activities such as role playing in order to increase knowledge gain and potentially longer knowledge retention.

This study uses a customized role playing activity within a business curriculum as one of many applied learning techniques. The value to students was shown by significantly higher gain in knowledge while simultaneously enhancing their enjoyment of the classroom experience to potentially encourage further lifelong learning.

The purpose of this paper is to show how work-based and work-applied learning (WAL) can enhance the intellectual capital of organisations.

The paper draws organisational learning- and work-based learning literature and case study illustrations.

To achieve major strategic change in organisations requires working at senior level within the organisation to develop the capability of the organisation to learn and apply that learning strategically. WAL is explicitly geared to bring about change and enhance the learning capability within the organisation.

There is a need for further longitudinal studies of organisations that have used the work-based and WAL approaches.

The conclusions reached have implications for higher education and non-award bearing executive education.

The alignment of individual learning with organisational objectives positions learning as a co-operative part of working life rather than just individual preparation for employment.

The paper positions work-based learning and WAL as appropriate responses to the learning needs of organisations as well as individuals.

This study aims to summarize the critical issues in medical federated learning and applicable solutions. Also, detailed explanations of how federated learning techniques can be applied to the medical field are presented. About 80 reference studies described in the field were reviewed, and the federated learning framework currently being developed by the research team is provided. This paper will help researchers to build an actual medical federated learning environment.

Since machine learning techniques emerged, more efficient analysis was possible with a large amount of data. However, data regulations have been tightened worldwide, and the usage of centralized machine learning methods has become almost infeasible. Federated learning techniques have been introduced as a solution. Even with its powerful structural advantages, there still exist unsolved challenges in federated learning in a real medical data environment. This paper aims to summarize those by category and presents possible solutions.

This paper provides four critical categorized issues to be aware of when applying the federated learning technique to the actual medical data environment, then provides general guidelines for building a federated learning environment as a solution.

Existing studies have dealt with issues such as heterogeneity problems in the federated learning environment itself, but those were lacking on how these issues incur problems in actual working tasks. Therefore, this paper helps researchers understand the federated learning issues through examples of actual medical machine learning environments.

In this digital era, email is the most pervasive form of communication between people. Many users become a victim of spam emails and their data have been exposed.

Researchers contribute to solving this problem by a focus on advanced machine learning algorithms and improved models for detecting spam emails but there is still a gap in features. To achieve good results, features also play an important role. To evaluate the performance of applied classifiers, 10-fold cross-validation is used.

The results approve that the spam emails are correctly classified with the accuracy of 98.00% for the Support Vector Machine and 98.06% for the Artificial Neural Network as compared to other applied machine learning classifiers.

In this paper, Point-Biserial correlation is applied to each feature concerning the class label of the University of California Irvine (UCI) spambase email dataset to select the best features. Extensive experiments are conducted on selected features by training the different classifiers.

The purpose of this paper is to address the need to rethink the traditional approach to education in the university engineering curriculum. The paper examines two engineering projects led by university students in Sweden: the design and construction of a solar-powered car taking part in the Bridgestone World Solar Challenge and the creation of a business model for the ownership phase of an electric car together with Polestar.

An extensive literature review was conducted. Students were interviewed and surveyed on their impressions of their learning experience in the two projects and student logbooks reviewed. Problem-based learning (PBL), the Conceiving, Designing, Implementing and Operating approach and the ABCD procedure are used. Results are compared to theories from the literature.

PBL in real-world settings can increase engineering students’ technical knowledge and improve their technical skills as they solve complex problems or propose solutions to such problems. Such projects also strengthen students’ commitment, self-confidence and self-esteem as well as promote co-operation and creativity. These are soft skills largely absent from traditional engineering education.

Innovative, student-led learning in the applied engineering curriculum can foster students’ soft skills in ways that teacher-led, lecture-style learning does not.

This research offers a timely perspective on an issue of current interest in engineering education: student-led learning versus teacher-led learning. The paper also provides two illustrative student-led projects that focus on sustainability and mobility.

There is a need for higher education to produce graduates who are motivated to transfer learning into the workplace. Motivated graduates are work-ready and associated with increased performance. Presently, the research field around motivation to transfer learning by students in higher education is not clear and is inconsistent.

This scoping review provides an overview of the characteristics of the literature, including key concepts, recommendations and gaps based on eight published articles on the motivation of students in higher education to transfer learning.

The results reflected a research field, which focused primarily on the influence of specific factors, namely student characteristics, educational design, the workplace environment, and on higher education students' motivation to transfer learning. The lack of a shared conceptual definition of motivation to transfer learning in higher education appears to influence the description of the results from the included studies. Most of the previous studies applied rigorous research designs.

This seemingly stunted research field related to higher education students' motivation to transfer learning needs to be amplified to influence the development of work-ready graduates from higher education. Approaches towards including all elements of motivation, expanding to other fields in higher education, including low-income countries, may be a proximal step in enhancing the trajectory of this research field.

Given how smart today’s malware authors have become through employing highly sophisticated techniques, it is only logical that methods be developed to combat the most potent threats, particularly where the malware is stealthy and makes indicators of compromise (IOC) difficult to detect. After the analysis is completed, the output can be employed to detect and then counteract the attack. The goal of this work is to propose a machine learning approach to improve malware detection by combining the strengths of both supervised and unsupervised machine learning techniques. This study is essential as malware has certainly become ubiquitous as cyber-criminals use it to attack systems in cyberspace. Malware analysis is required to reveal hidden IOC, to comprehend the attacker’s goal and the severity of the damage and to find vulnerabilities within the system.

This research proposes a hybrid approach for dynamic and static malware analysis that combines unsupervised and supervised machine learning algorithms and goes on to show how Malware exploiting steganography can be exposed.

The tactics used by malware developers to circumvent detection are becoming more advanced with steganography becoming a popular technique applied in obfuscation to evade mechanisms for detection. Malware analysis continues to call for continuous improvement of existing techniques. State-of-the-art approaches applying machine learning have become increasingly popular with highly promising results.

Cyber security researchers globally are grappling with devising innovative strategies to identify and defend against the threat of extremely sophisticated malware attacks on key infrastructure containing sensitive data. The process of detecting the presence of malware requires expertise in malware analysis. Applying intelligent methods to this process can aid practitioners in identifying malware’s behaviour and features. This is especially expedient where the malware is stealthy, hiding IOC.

The purpose of this paper is to challenge how we have traditionally thought about organisations and introduce two frameworks to enable us to understand how change in organisations might be facilitated better.

The paper discusses organisations as complex adaptive systems and uses complexity theory to inform two new frameworks for facilitating organisational learning and change.

In order for organisational learning to occur we need to change our mind-set of how we see organisations and to think of learning not just as individual but also as generative “communicative action” that emerge out of collaborative relationships.

The frameworks proposed are grounded in organisational learning literature and the experience of the author. The proposed agenda for organisational learning has yet to be acted upon and evaluated.

The frameworks can be used to enhance understanding of learning and change in organisations. The agenda for enabling organisational transformation identifies key steps to put the ideas developed in the paper into practice.

The approach advocated for use within organisations is one of empowerment and collaboration rather than top down direction.

The paper introduces new frameworks and a practical agenda to bring about organisational transformation through work-applied learning.

This study aims to examine the perceptions of students about learning science and physics using the engineering design process (EDP).

The study employed a mixed-methods research design: The quantitative session features a pre–post-test control group study. In the qualitative aspect, the study conducted semistructured interviews for data collection. In the experimental group, the flipped classroom (FC) model and an instructional design are combined to design, develop and implement a physics course using the steps of the EDP, while the conventional method was applied to the control group. The respondents are students of the Department of Mechanical Engineering at Cao Thang Technical College in Vietnam for the academic year 2022–2023. The control and experimental groups are composed of 80 students each. An independent sample Mann–Whitney U test is applied to the quantitative data, while thematic analysis is employed for the qualitative data.

The results demonstrate a statistically significant difference between the experimental and control groups in terms of perceptions about learning science and physics using the EDP, which, when combined with a FC, enhances physics learning for engineering students.

This study implemented the EDP in teaching physics to first-year engineering students in the Department of Mechanical Engineering using the combined FC and instructional design models. The results revealed that a difference exists in the perception of the students in terms of integrating the EDP into learning physics between the experimental and control groups. The experimental group, which underwent the EDP, obtained better results than did the control group, which used the conventional method. The results demonstrated that the EDP encouraged the students to explore and learn new content knowledge by selecting the appropriate solution to the problem. The EDP also helped them integrate new knowledge and engineering skills into mechanical engineering. This research also introduced a new perspective on physics teaching and learning using the EDP for engineering college students.

The research findings are important for teaching and learning physics using EDP in the context of engineering education. Thus, educators can integrate the teaching and learning of physics into the EDP to motivate and engage student learning.

Using the EDP combined with a FC designed under stages of the analyze, design, develop, implement and evaluate (ADDIE) model has enhanced the learning of physics for engineering college students.

Issues around informal, non-formal and formal learning, intended and unintended learning and competencies and capabilities have been considered in work-based learning (WBL). However, demarcated modes of learning, or what can be called strategies or pedagogies of learning, associated with experience of work environments have yet to be examined. One mode of learning which has been highlighted in relation to work is reflective practice, and its centrality to learning at work has been established. But reflective practice as a core skill, and its relation to other approaches to learning and research in WBL, remains uncovered. The purpose of the present study therefore is to identify different modes of learning as they appear in the literature and to present a proto-theoretical “learning by …” model for WBL and research founded on learning by reflection.

Proto-theoretical modelling and qualitative descriptions of each mode of learning.

Work environments, and the higher degree WBL programmes which support them, should provide learning via every available mode of learning, thereby allowing students to find their own best orientation to learning and encourage it by any means.

The proto-theoretical model and 12 modes of learning applied to WBL are unique to this study. WBL provides participants of work with multiple opportunities and approaches to learn and similarly provides multiple modes through which learning can occur on the basis of knowledge and skills in reflective practice.