Conference Agenda

This paper focuses on the development of an innovative ap

plication that uses artificial intelligence (AI) and augmented reality (AR)

to create an authenticity detection system (ADS). It uses technologies

to analyze micro-expressions, transforming them into emotions based on

which it will indicate the type of sincerity of a person with whom one

is having a dialogue. Using AR, real-time feedback will be superimposed

on the user’s screen, and this technology will also help us offer live mon

itoring of facial movements during interviews or interactions. The ADS

purposes are diverse, from law enforcement (interrogations and state

ments verification), to human resources (hiring processes and honesty of

candidates, social interactions), providing valuable information in nego

tiations, counseling, and therapy. Using Haar Cascade Classifiers (HCC)

combined with Convolutional Neural Networks (CNN) allowed the de

velopment of a new algorithm for the ADS.

The Tec21 educational model is based on challenges posed to students through a training partner. Since Tecnologico de Monterrey introduced this new model in 2020, the importance of having more robust simulators or training partners was detected so that they could provide the necessary information for the students' projects. This was the reason for transforming CAETEC, which was born as an experimental agricultural field, into a living lab and data farm, where it generates information from different operations, such as the voluntary automatic milking system based on robots and intensive agriculture (greenhouse) and precision agriculture in open fields. The design and development of virtual and augmented reality lessons, as well as the use of metaverse, has allowed us to build a distance learning ecosystem for different training units at the Tecnológico de Monterrey and to be a training partner for the development of challenges of the students.

CONTEXT

The COVID-19 pandemic had a profound impact on higher education, resulting in a rapid global shift to remote learning. This transition posed challenges for curriculum design, technological infrastructure, and student and teacher preparation. While some institutions struggled, others seized the opportunity to explore new ways of teaching and responding to future educational challenges. Despite inadequate infrastructure and training, the urgent need for mass online teaching highlighted the importance of rethinking higher education's digital capacity. The pandemic exposed weaknesses but also revealed new opportunities for innovation and the integration of new teaching methodologies. As higher education moves forward, it faces a pivotal moment of adaptation, incorporating lessons from remote learning while preparing for future challenges.

PROPOSE/GOAL

This article investigates the transition to remote/hybrid teaching in Portugal during the COVID-19 pandemic, employing Actor-Network Theory (ANT) to examine the interaction of social, technical, and pedagogical factors. It focuses on determining how various actors—students, teachers, institutions, technologies, policies, and social norms—influence the success or failure of remote learning.

The research primarily investigates students' and technological perspectives, examining factors influencing students' preferences for remote learning, such as security, access to technology, and study conditions. It also assesses the impact on academic performance, digital skills, and learning perceptions, as well as how institutional policies and social conditions shaped the remote learning experience. Additionally, it analyzes the role of digital technologies in adapting to remote teaching and the associated challenges and opportunities.

APPROACH

The research is a case study focused on students' experiences in a Bachelor’s Degree in Computer Engineering in Portugal during the transition to remote learning amid the pandemic. ANT, it examines the complex relationships between human and non-human actors shaping distance learning. The methodology includes qualitative data collection through online questionnaires, gathering students' perceptions and experiences. The data is analyzed using content analysis to identify participant narratives' patterns and themes. ANT is applied to explore the interactions, translation of interests, and resource mobilization involved in implementing remote teaching.

OUTCOMES

Using Actor-Network Theory (ANT), the research aims to highlight the theory's effectiveness in analyzing the complex networks of remote teaching. ANT will be applied to: Map interaction networks, identifying human and non-human actors and their interdependencies; Understand translation dynamics, showing how interests are negotiated and meanings evolve as networks adapt; Identify crucial convergence points (OPP) necessary for remote education participation; Analyze enrollment and mobilization processes, observing how actors align to strengthen the network; Investigate how practices, technologies, and norms shape the remote education system. The research aims to enhance understanding of remote teaching complexities and support future education strategies.

CONCLUSIONS

The research underscores the need for a holistic view of remote learning, emphasizing the complex interplay between human and non-human actors. It highlights the importance of diverse perspectives—students, teachers, institutions—and technical aspects. The study suggests hybrid models can provide flexibility and meet varied student needs, especially during crises, while also stressing the influence of social, cultural, and socioeconomic factors, access to technology, and government policies on remote learning.

In today’s fast-evolving educational landscape, it is increasingly essential for entrepreneurship to be molded into STEAM. This expansion to "STE2AM" seeks to equip learner-students with the skills to innovate, solve sophisticated problems, and build sustainable solutions. Unfortunately, the absence of commonly defined frameworks on the teaching of entrepreneurship as a subject in the STEAM curricula has resulted in a gap in skills acquisition and knowledge transfer.

The project funded under Erasmus+ titled "Defining Standards in STE2AM Education" will help bridge this gap, working to establish cross-border standards and best practices to the effective integration of entrepreneurship across STEM and Arts disciplines. The project's main aim is to develop clear, adaptable, and inclusive standards for STE2AM education intended to foster the acquisition of relevant, actionable, and transferable entrepreneurial skills by students throughout Europe and beyond. The project also intends to promote a common STE2AM educational approach enabling institutions to develop robust frameworks for the nurture of future-ready entrepreneurial talent in a structured manner.

The current paper explores emerging technologies used in online exam su-pervision. Utilizing a qualitative approach through examining recent litera-ture and detailed case studies of major testing service providers, the paper highlights advances in artificial intelligence (AI), machine learning (ML), deep learning (DL), biometric verification, and blockchain-based meth-ods. These technologies collectively aim to enhance the integrity, fairness, and security of remote examinations by automating identity verification, de-tecting suspicious behaviors, and ensuring tamper-evident data management. Emerging technologies in online exam supervision have reached a high de-gree of sophistication and maturity, and online proctoring providers are con-stantly investing in innovation, regulatory compliance, and improving can-didate experience. While these technologies can offer promising improve-ments in detecting and preventing cheating, they also present particular challenges. These challenges are related to resource requirements, scalability, and ethical considerations. A hybrid approach combining technological solu-tions with human oversight seems to be the most effective strategy current-ly. There is also a need for standardized frameworks along with recommen-dations and guidelines to address privacy concerns and ensure the ethical use of these technologies in online exam settings.