2025 Conference Program

OVERVIEW

Bridging Digital Skills and Heritage Education for Inclusive Citizenship: The FIGHTER Project

Antonella Poce, Ph.D., Carlo De Medio, and Mara Valente, University of Rome Tor Vergata, Rome, Italy

The FIGHTER project (Fighting Inequality through Digital Skills and Heritage Enhancement for Responsible Citizenship) tackles educational and social disparities by integrating digital tools into tangible and intangible heritage experiences. Its primary aim is to foster transversal competences—critical thinking, collaboration, communication, and creativity—and digital skills among various groups of displaced children (including those with migrant backgrounds, disabilities, or special educational needs), thus promoting active citizenship and social inclusion.

Methodologically, the project adopts a Design-Based Research (DBR) approach, combining the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) with Asset Based Community Development (ABCD). Five Work Packages structure its activities. WP1 conducts a literature review and develops an intervention model to strengthen digital competences and civic skills through heritage. WP2 pilots innovative methodologies—Object-Based Learning, Digital Storytelling, and Virtual Reality—with teachers, tutors, and museum operators. WP3 creates an interactive digital environment featuring open educational resources and real-time data analytics. WP4 defines a quality framework and designs evaluation tools to measure the impact on participants’ digital and transversal skills. WP5 manages the overall project, dissemination, and the establishment of an inter-institutional center dedicated to fostering well-being, critical technology use, and cultural participation…

Keywords: inclusive education, competences, enhancement, social inclusion, active citizenship

Empowering Digital Citizens: AI Tools for Teaching Democratic Participation

Nina Bamberg, PedagogyVentures, New York, New York, USA

As Artificial Intelligence (AI) continues to proliferate our world and impact how we engage with information, it is critical for schools to meet the moment by preparing students for the ways that this technology will shape their lives as citizens in democratic societies. Likewise, AI is becoming a widely used tool by educators because of its ability to aid in developing engaging lessons and materials, and personalizing content to meet diverse student needs. By employing AI tools in the teaching of digital literacy and civic participation, educators can equip students with the knowledge and skills to actively engage in the democratic process in a way that meets their learning needs.

This hands-on workshop will introduce educators to innovative approaches for teaching digital literacy and democratic participation using AI tools. Participants will explore practical strategies for incorporating AI-assisted learning activities that help students critically evaluate political information, understand democratic processes, and develop informed civic engagement skills…

Keywords: artificial intelligence, digital citizenship, AI literacy

Integrating Generative AI in Active Learning: A Case Study in Project Management Education

Matti Koivisto, Ph.D., South-Eastern Finland University of Applied Sciences, Mikkeli, Finland

In today's rapidly evolving educational environment, the fusion of technology and pedagogy shapes in many ways how we approach learning. In recent years, different ways of combining the possibilities of generative AI and different learning and teaching methods have been of particular interest. This paper focuses on the application of AI in active learning. Active learning is a teaching method that activates students in the learning process through various activities such as discussions, problem solving, and practical projects. This method can manifest itself in many forms, such as group works, case studies, interactive lectures, and digital simulations. By promoting participation and critical thinking, active learning helps students to better assimilate and apply knowledge. The empirical part of the paper presents an active learning task based on a simple but effective method developed at a Finnish University of Applied Science…

Keywords: active learning, AI, project management

A Multi-Stage VR Approach to Boosting Student Engagement and Learning in Engineering

Daria Mizza, Ph.D., American University in Cairo, New Cairo, Cairo Governorate, Egypt

This study investigates the impact of a multi-staged virtual reality (VR) experience, including an immersive CAVE demonstration, on undergraduate engineering students' situational interest. By focusing on the dimensions of presence, involvement, and representation fidelity, we aim to understand how the VR experience can enhance learning and engagement.

To address this research question, we conducted a mixed-methods study involving both quantitative and qualitative data collection among a cohort of university students enrolled in an engineering course on stress computation. Quantitative data was analyzed using statistical methods, including Cronbach's alpha to assess the reliability of the Presence scale. This scale measures the degree to which students feel engaged in the VR environment…

Keywords: virtual reality, situational interest, instructional design, undergraduate education

From Prompts to Scores: Generative AI vs. Human Grading in Writing for Standardized Language Testing

Rohib Sangia, University of Aberdeen, Aberdeen, United Kingdom

Rapid advancements in GenAI have revolutionized language learning particularly in standarized language test preparation by providing learners with immediate, adaptive, and data-driven feedback on writing performance, enabling them to refine their linguistic accuracy, coherence, and argumentation through tailored guidance that closely mirrors the evaluation criteria of high-stakes assessments, such as the IELTS. Therefore, this study compared language test scoring by human evaluators and GenAI for the IELTS Academic writing module. The research assessed four models—ChatGPT, Claude, Gemini, and DeepSeek—using 110 IELTS Task 1 and Task 2 essays and compared their performance to human markers through statistical analyses, including PCC, ICC, and MAE. The findings indicated varying degrees of alignment between GenAI and human scores, with DeepSeek exhibiting the highest correspondence with human assessments. A qualitative content analysis of the GenAI-generated comments on details, organization, and utility was performed. Notably, the ChatGPT provided comprehensive, well-organized, and actionable feedback. Claude offered a balanced approach, Gemini focused on strengths, and DeepSeek delivered more concise feedback, although less actionable. This study underscores the potential of GenAI as a supplementary tool for SDL in IELTS preparation and assessment while also highlighting limitations such as the depth of feedback and the risk of over-reliance on technology…

Keywords: generative artificial intelligence, language assessment, self-directed learning, IELTS writing module

Automotive Students' Performance Attitudes in a Virtual Reality Learning Environment with Active and Passive Haptic Interaction

Turhan Civelek, Ph.D., and Arnulph Fuhrmann, Ph.D., TH Köln, Cologne, Germany

This study examined the impact of a SensGloves-supported virtual reality learning environment (VRLE) on automotive students' interaction with virtual objects, assembly of vehicle parts, user motivation, mate-rial richness of the learning environment, improvement of vehicle maintenance processes, and usage in the car workshop.

Students experienced two versions of the VRLE environment: active haptic, which includes force feedback, and passive haptic, which does not. After completing the experience, they answered a 21-question survey.

The study involved 20 randomly selected students from TH Köln in Ger-many. The data was collected through an attitude survey and analyzed using a Paired-Sample T-Test.

The t-test results indicate that the active haptic group scored significantly higher in interaction with virtual objects (t (19) = 3.228, p = 0.004) and assembly of motor parts (t (19) = 2.298, p = 0.033) compared to the passive haptic group. However, no statistically significant differences were found between the groups for the other factors.

Keywords: haptic interfaces, mixed/augmented reality, human-computer interaction, virtual training

Changing the Evaluation Game

Graham Glass, CYPHER Learning, Plano, Texas, USA

With AI-powered cheating software sprouting like kudzu among student populations, educators are responding by unholstering dozens of purported AI-detection weapons of their own. It’s an escalating classroom standoff impossible to resolve. But perhaps, to paraphrase Cold War leaders, it’s an arms race that can never be won and should not even be fought.

Yes, AI writing agents readily disgorge rivers of glib essay language feckless students are claiming as theirs. But rather than try to fix that – banning AI from academia would be as pragmatically futile as outlawing search engines or scientific calculators – let’s rethink the whole act of evaluation itself.

Let’s use this opportunity as a spark for new, smarter evaluation frameworks. Why make students produce busy-work papers they regard as tedious torture – that’s why they resort to AI in the first place – when we can design live-interview rounds, peer interrogation formats, even quiz games? We can and should develop testing tactics that put a student out of reach of AI helpmates. They might even be – although it’s sometimes a taboo notion in this space – fun…

Keywords: artificial intelligence, evaluation frameworks, AI in workplace, AI in education

AI-Powered Career Guidance: Enhancing Student Workforce Readiness through Machine Learning and Large Language Models

Sherif Abdelhamid, Ph.D., and Jude Roberts, Virginia Military Institute, Lexington, Virginia, USA

Preparing students for the workforce requires aligning their skills and interests with career opportunities. This research presents an AI-driven system using machine learning and multimodal language models to support workforce development. The system automates resume classification and provides personalized feedback, including course recommendations, skills gap analysis, learning pathways, and training suggestions. It identifies best-fit roles for students and offers actionable insights to boost career readiness.

The system consists of two main phases: resume classification and workforce analysis. After using machine learning for resume classification to identify the best-fit role, the system utilizes the Generative Pre-trained Transformer (GPT-4) to provide contextual feedback on skills gaps, recommend learning pathways, and identify training opportunities. Two different GPT-4 instances are used simultaneously in the system. One with general knowledge of various fields and information on the required skills, training, and career development knowledge. The other GPT-4 instance has domain-specific knowledge of specific university programs, courses, internal policies, and procedures. The domain-specific GPT-4 knowledge base is a pluggable component that can easily integrate and change from one institution to another, allowing tailored, customized support for each school and its students…

Keywords: workforce readiness, machine learning, large language models, GPT-4

AI as a Tool for Humanizing Liberal Arts Education: Engaging Students in the Age of Automation

Priten Shah, Pedagogy.Cloud, Haverstraw, New York, USA

As artificial intelligence continues to advance, liberal arts educators face the challenge of adapting their teaching practices to harness the benefits of AI while preserving the human-centered values that define the liberal arts. This session aims to empower participants with strategies to leverage AI technologies to center the human experience and engage students in meaningful learning within the context of liberal arts education. The relevance and value of this content to the higher education community lie in its potential to help liberal arts educators integrate AI technologies into their teaching practices to create student-centered learning experiences that foster critical thinking, creativity, empathy, and interdisciplinary collaboration – skills that will be essential for students' success in the age of AI.

Key points that will be presented include:

• The role of the liberal arts education in the age of AI;

• The potential for AI to help us meet the goals of liberal arts education more effectively;

• Strategies for integrating AI technologies into teaching practices to foster student engagement and collaboration..

Keywords: AI & education, liberal arts, student engagement, ethics

One Size Fits One: The Impact of Strength-Based Development on the Bottom Line

Breanna Jackson, The Refining Company, LLC, Gresham, Oregon, USA

Driving for results in an organization is essential to maintaining a successful business. The best way to achieve those results comes from a committed and engaged workforce, but we often settle for committed employees alone. Maybe because the level of productivity seems to overpower the threat of disengagement or perhaps the process to overhaul the current culture of not checking in beyond the work to be done seems too time consuming. Either way, the health of the organization suffers when employees are not engaged. This workshop focuses on how adding the equitable lens of strength-based development can positively impact employee engagement and help build a committed and engaged workforce.

Keywords: strength-based development, equity, belonging, transformation, engagement

Future-Proofing Leadership: Leveraging Blended Learning, AI, and Generational Strategies for Workforce Development

Tonia Young-Babb, Ed.D., Nationwide Children's Hospital/Abilgail Wexner Research Institute; Franklin University, Elwood, Indiana, USA

As organizations navigate the complexities of a globalized workforce, leadership agility and professional development are essential to future-proofing operations. This study examines the interplay between leadership practices, professional growth, and organizational success, emphasizing the importance of innovative approaches, including blended learning, artificial intelligence (AI), and progressive learning strategies. These methods address the diverse and evolving needs of a multigenerational workforce while fostering leadership development that is adaptable and resilient in dynamic environments.

The research highlights the importance of tailoring professional development to generational differences, recognizing that each cohort—from Baby Boomers to Generation Z—has distinct preferences and expectations for learning. While older generations may prioritize structured and formal training programs, younger generations often value flexibility, technology-driven solutions, and opportunities for continuous, on-demand learning. Blended learning and AI-driven personalization create scalable and inclusive strategies to meet these varied needs, ensuring all employees can access relevant and impactful development opportunities…

Keywords: professional development, leadership agility, blended learning, artificial intelligence, progressive learning strategies