This paper investigates the use of simulation-based learning in Engineering Management education. Building on prior research, it explores how students allocate R&D budgets between disruptive and sustaining technologies under dynamic market conditions. Conducted with diverse student groups, the study aims to validate earlier findings, which emphasized disruptive innovations as key drivers of success and highlighted the educational benefits of repeated simulation runs. The research extends previous work by adding a longitudinal dimension, examining how decision-making patterns and learning outcomes evolve over time. The findings confirm consistent trends favoring disruptive technologies across cohorts while revealing some variations in strategies influenced by changing contexts. This study underscores the value of simulation-based learning in fostering critical thinking and preparing students for innovation challenges in SMEs and other STEM fields.

The declining interest in Science, Technology, Engineering, and Mathematics (STEM) careers among young students, particularly the persistent underrepresentation of women, has become a significant global concern. While earlier studies highlighted an achievement gap in mathematics and science between boys and girls, recent international assessments, such as PISA, suggest that this gap has largely closed. However, gender disparities in attitudes towards STEM careers and the persistence of stereotypes continue to impede gender equity in these fields. The primary school years appear to be a critical period for addressing these issues. This study investigates the impact of a targeted STEM intervention focused on modern physics on students' perceptions of science, attitudes towards STEM subjects, and the persistence of gender-related stereotypes. Preliminary findings suggest that the intervention significantly improved female students' self-efficacy in science and led to notable reductions in stereotypical beliefs about gender and STEM abilities.

The rise of Artificial Intelligence (AI) in education is reshaping traditional learning environments, with AI-powered tools increasingly being integrated into teaching and learning processes. AI chatbots are being used in engineering education for personalized concept explanations, generating practice problems, and assisting students in formulating their thoughts on complex engineering topics [1]. AI tools offer opportunities to enhance learning outcomes and teaching strategies, yet they also present challenges. This study focuses on the integration of AI-driven learning in engineering education at an English-speaking university, examining both student and faculty perspectives across various engineering disciplines, including, but not limited to chemical, civil, electrical, mechanical engineering and engineering management. While AI tools can enhance educational experiences by providing personalized feedback, generating content, and assisting with research tasks, they also pose risks of plagiarism and misuse, as students may rely on AI-generated outputs without proper oversight or attribution [2]. Recent studies [3] discuss that the rapid adoption of AI tools in education presents a significant challenge in maintaining academic integrity, with concerns over the fabrication of information and the ethical use of AI-generated content, prompting the need for clearer guidelines and frameworks to support responsible usage. Previous studies have demonstrated the efficacy of AI tools in enhancing language skills and supporting English for Specific Purposes (ESP) courses. Our research extends this focus to the engineering field, where both technical and communication skills are critical. This research investigates the use of AI tools for educators and learners and how they affect the learning outcomes, their critical thinking, the student engagement, and how this affects the offering of personalized (or the lack thereof) learning experiences. By focusing on the perspectives of both students and faculty, the study seeks to understand how these tools impact educational outcomes and shape teaching methodologies. In particular, this research investigates the following question: How do students and faculty perceive and use AI chatbots in academic settings? A survey was used to gather data from both groups where descriptive and inferential statistics were performed to evaluate the broader implications of AI integration in educational contexts. The study was conducted in the context of the university's commitment to integrating AI tools into higher education, focusing on developing skills for effective and ethical AI use. In conclusion, this study provides valuable insights into both the benefits and limitations of AI-driven tools in engineering education. It highlights the opportunities these technologies present, while also addressing the need for much needed ethical considerations and digital literacy training for both students and educators. However, it's important to note that the survey method may not fully capture the complex impact of AI, and the focus on a single institution may limit the generalizability of the findings. Despite this, the findings contribute to ongoing discussions on how AI tools can be effectively integrated into higher education to foster innovation, enhance learning, and maintain academic standards.

In the context of STEM education, particularly in engineering, a foundational emphasis is traditionally placed on solidifying theoretical knowledge. However, the dynamic nature of industry-oriented disciplines like Engineering Management necessitates a more practical approach to learning. This paper extends the understanding of such learning methods by investigating the application of simulation-based tools to teach complex concepts inherent in Engineering Management. The primary objective of this research is to analyze and understand the factors influencing students' strategic decision-making processes under these simulated, yet realistic, conditions. Furthermore, the study aims to evaluate how such simulation-based learning impacts students' comprehension of both sustaining and disruptive innovations. The results reveal a strong inclination towards disruptive technologies as key drivers of success in the simulated environment. Notable improvements in students' performance over repeated trials indicate that immersion in a simulated, practical environment substantially reinforces the theoretical concepts taught in the classroom.

Science education is becoming increasingly vital, providing essential critical thinking skills for young people to navigate a world inundated with information, new technology, and AI capabilities. While the future impact of these developments remains uncertain, science, with its methods and culture, can empower youth with the abilities to assess them critically and engage responsibly with their potential offerings. However, science is neither their strongest nor their most popular subject, causing society and policymakers to be highly concerned about the availability of a skilled workforce to confront the problems facing our world. Bringing current science to school curriculum as early as in primary school has been researched as a probable solution to this issue. This paper presents a K-6 three-year study on conventional concepts, future choices, and perspectives on science after a STEM action plan, revealing promising and unexpected results that could lead to influence science identity and build science capital to young learners.

Science education has been entrusted with the responsibility to improve young learners' scientific literacy and enhance their ability to think, behave and act in a manner of a scientist. Scientists have frequently been conceived as professionals, critical thinkers, creative talents, and experts providing scientific information. This study ventures into the critical examination of young learners' perceptions of scientists, probing whether these views are static or evolve with educational engagement. Through the participation of 140 elementary students in Greece, it is aimed to unravel the influence of gender stereotypes and media portrayal on learners' conceptualization of scientists, comparing contemporary perceptions to historical data. The approach includes a “Draw a Scientist” activity and surveys administered before and after exposure to educational media, offering a unique lens on the stereotypes and the potential transformative power of targeted educational interventions. Initial findings point toward a malleable understanding of scientific roles among young learners, influenced significantly by media and role models. This research investigates into the initial perceptions of scientists held by students and examines if these perceptions evolve following engagement in a systematic educational setting while underlines the need for media literacy and diverse representation in STEM fields to foster an inclusive perception of science from an early age.

This paper investigates the impact of large language model (LLM) AI tools, such as ChatGPT and Copilot, on software development education, focusing on usability, efficiency, and effectiveness in real-world scenarios. The research employs a quantitative approach, utilizing a survey of 50 software developers with varying levels of experience. Preliminary findings suggest that AI tools have a positive influence on expediting coding tasks and automating text generation, particularly in the early stages of product development. Challenges related to customization, accuracy, and transparency, as well as concerns about their potential impacts on employment, personal privacy, and ethical boundaries, have been identified. Pointers and initial recommendations for transitioning to AI-enhanced teaching and optimizing interactions between learners and generative AI practices are provided.

Women bring a wide range of competencies and viewpoints, mindsets, and ideas both at the executive and the R&D levels and consistent evidence over the past decade demonstrates the positive impact of gender diversity on innovation performance. Yet, there are significant handicaps for women's career paths in innovation, from studying STEM subjects to entering in and remaining on the workforce of so-called “male-oriented” industries. Indeed, women are more prone to abandon a research career than men. In this context, the objective of this study was to investigate the effect of a set of factors on forming the perceptions (and thus shaping future career choices) of female STEM students of a leading university in Kazakhstan. In Kazakhstan, an impressive 52 % of researchers are women but females are distinctly underrepresented in “male-oriented” sectors as manufacturing, construction, and oil & gas respectively. The subjects were surveyed on twelve observable variables and the collected data were used for the deployment of a Structural Equation Model (SEM), the statistical significance of which was verified via the non-parametric technique of bootstrapping. The first key outcome obtained is that the presence and support of women professionals in the academic and social environment increases awareness about the problems that female students in STEM are expected to face in their professional careers. The second outcome is that increasing awareness about gender inequality often leads females to an early exit from a STEM career. This is a novel observation that raises a spectrum of important policy issues. It appears that public awareness campaigns on issues related to gender should be coupled with palliative measures to make sure that they do not accelerate the “leaky pipeline phenomenon” in STEM which they purportedly attempt to stop.