Special Sessions

Overview

Many leading managers worldwide, e.g. Jeffrey Bezos - Amazon; John Martin - Gilead Sciences; John Chambers - Cisco Systems; David Pyott - Allergan; David Simon - Simon Property Group have engineering background. According to Harvard Review in 2014, Twenty-four of HBR's 100 best-performing CEOs have undergraduate or graduate degrees in engineering. However, the continuous technological, economic and social changes of the last few decades have increased the need for managers to have a good understanding of these changes and the environment in which organizations function.

Cybersecurity is an increasingly interesting area for many engineers of diverse backgrounds. Moreover, many disciplines that are not primarily related to Computer Science and Electrical Engineering are affected by the recent advances in cybersecurity. Traditionally, cybersecurity was related to mathematics for building cryptographic primitives and engineering for building secure systems. This is not the case anymore, since cybersecurity is a much broader and more complicated domain involving many different areas of knowledge from Computer Science to several other sciences (e.g., Law). Beyond building technologies related to cybersecurity, it is also important to educate and train people that use systems and the Internet, in any level of interaction, about the recent advances of cybersecurity. Due to the diverse field of cybersecurity, which combines knowledge from different areas, and due to the very nonhomogeneous nature of the audience, educating professionals in cybersecurity matters is challenging.

Overview

Engineering programmes offered in the Transnational Education (TNE) present unique challenges in the context of rapid advancements in Generative AI, largely due to its inherently cross-border nature. One of the primary challenges lies in navigating pedagogical and cultural differences, as learners from various countries exhibit diverse learning styles, academic expectations, and educational traditions. Furthermore, language barriers can significantly hinder effective communication between educators and learners and among diverse learner groups. Additionally, aligning curricula, regulations, and assessment standards to satisfy the accreditation requirements of both countries is a complex task. Disparities in access to technology and resources pose further challenges, particularly when considering legal compliance and equity issues across regions.

Overview

The importance of ethics education within the engineering curriculum cannot be overstated. However, many of the typical examples used relate to generic issues in engineering, for example, failure to follow codes of ethics, rather than issues that are related specifically to engineering disciplines. We argue that while these generic issues are important, it is vital that discipline specific examples are also available for educators to embed ethics issues and concerns within technical classes. As part of the development of the Routledge International 
Handbook of Engineering Ethics Education, the facilitators wrote a chapter to highlight ethics issues and pertinent to Electrical Engineering (EE) [1].

Overview

Generative AI has taken the world by storm, influencing various fields across industries and society. As Large and Small Language Models, Diffusion Models, and other AI systems rapidly develop, they have sparked wide ranging discussions among scientists, educators, public administrators, lawmakers, and everyday citizens. While these technologies offer immense potential, their integration into domains like education, particularly in engineering disciplines, raises critical ethical\ concerns. This special session will explore how institutions can harness the power of AI for innovation while ensuring responsible use, focusing on ethical challenges such as bias, privacy, accountability, and explainability.

Overview

Engineering should attract, promote, foster and retain talents, considering that individuals are different, and they can have characteristics that can require flexibility in the education system in order to guarantee equal ] ] opportunities of anyone regardless their gender, race or condition. These characteristics can make the developing of their skills more challenging for the students and for the educational institutions and their professionals.

Overview

The rapid development of learning technologies has transformed education, particularly in hybrid learning environments and engineering fields. Hybrid learning, which blends in-person and virtual instruction, has become essential for flexible education, especially in the post-pandemic landscape. However, challenges persist in recreating the engagement, interactivity, and personalized assessment found in traditional classrooms. AI technologies, such as Large Language Models (LLMs) such as OpenAI's GPT, alongside multi modal AI tools, present innovative solutions to overcome these obstacles. LLMs and multi-modal AI offer transformative potential in both hybrid and engineering education. LLMs are capable of processing vast amounts of data and generating human-like responses, while multi-modal AI uses tools such as generative AI, natural language processing, image and video analysis, and speaker recognition to improve student engagement and learning outcomes. By analysing multimedia data—video, audio, and text—generated during virtual classes, AI technologies can provide real-time insights into student engagement, attention, and emotional responses, enabling educators to adapt teaching methods dynamically. 

Overview

Remote or Online Labs have been developed by several universities and offer flexibility in terms of place, time and learning pace. Additionally, they allow students to have access to more complex real experimental setups and offer the possibility for a more efficient sharing of resources across institutions. A well-known example for a Remote Lab is the already widespread VISIR platform, developed by Blekinge Tekniska Högskola (BTH) and used by various Universities in Portugal, Spain, Brazil, Sweden, and Austria.

Overview

STEM education for school-aged children is vital to our world economy. We must have a strong global STEM pipeline to meet the growing need for a high-skilled workforce.

• Due to technology-driven growth and the necessity to replace the senior STEM workforce
  as they return, the STEM labor market is projected to expand by 12.1% by 2025 in Europe.
  SOURCE: https://www.teknologisk.dk/_/media/64894_Does%20the%20EU%20need%20more%20STEM%20graduates.pdf
• In the United States, employment in STEM occupations has grown 79%—increasing from
  9.7 million to 17.3 million since 1990.
  SOURCE: Via a 2018 article from Pew Research Center