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30 April 2026

16 Pages

Integrating Artificial Intelligence and Assistive Technologies in Higher Technical Education: The Role of Spoke 4 at Rome Technopole

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Centro IATIS, Istituto Superiore di Sanità, Via Regina Elena 299, 00161 Rome, Italy
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Servizio Fast, Istituto Superiore di Sanità, Via Regina Elena 299, 00161 Rome, Italy
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Dipartimento Neuroscienze, Istituto Superiore di Sanità, Via Regina Elena 299, 00161 Rome, Italy
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Author to whom correspondence should be addressed.
AI2026, 7(5), 158;https://doi.org/10.3390/ai7050158
This article belongs to the Special Issue Development of Artificial Intelligence and Computational Thinking: Future Directions, Opportunities, and Challenges
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Abstract

Higher technical and professional education is increasingly discussed in relation to workforce readiness, innovation, and societal inclusion. In Italy, the PNRR-funded Rome Technopole operates as a multi-institutional ecosystem in which universities, research organizations, industry, and public bodies interact through a Hub & Spoke model to support training and innovation activities. Among its components, Spoke 4 addresses professional higher technical education through the co-development of modular learning initiatives involving multiple stakeholders. This commentary examines the role and activities of the Italian National Institute of Health (ISS) within this context, with particular reference to the development of two pilot modules: one on Artificial Intelligence and Algorethics, and one on Accessibility and Assistive Technologies, including applications supported by AI. The paper combines a conceptual discussion of the approach with selected empirical insights derived from pilot implementation, including stakeholder engagement processes, structured evaluations, and thematic prioritization exercises. The findings suggest the perceived relevance of multi-stakeholder co-design, the use of flexible and modular learning formats, and the integration of technical and ethical dimensions in higher technical education. At the same time, they point to challenges related to coordination, scalability, and alignment across institutional actors. Rather than proposing a definitive model, the Spoke 4 experience is discussed as a context-specific case that may offer insights contributing to ongoing debates on the design and implementation of higher technical education in complex, multi-institutional settings.

1. Presentation of the Study

Higher technical and professional education is increasingly recognized as a key driver of workforce readiness, innovation, and societal inclusion. In Italy, the Piano Nazionale di Ripresa e Resilienza (PNRR)-funded Rome Technopole provides a collaborative ecosystem where universities, research institutions, industry, and public bodies interact through a Hub & Spoke model to develop future-oriented training programs. Spoke 4, dedicated to professional higher technical education, engages multiple stakeholders in co-developing modular learning experiences that combine technical rigor, ethical reflection, and applied problem-solving.
This commentary presents the conceptual role of the Italian National Institute of Health (ISS) within Spoke 4 and discusses the development of two pilot modules: the first addressing Artificial Intelligence and Algorethics, and the second focusing on Accessibility and Assistive Technologies, increasingly enhanced by AI for personalized applications.
In addition to conceptual discussion, the commentary incorporates selected empirical insights derived from pilot implementation, drawn from stakeholder and educator evaluations, quantitative Likert-scale assessments, and thematic feedback. These insights indicate positive perceptions regarding the relevance, clarity, and applicability of the modules, as well as the sectors and priorities identified by participants, while also pointing to broader challenges and limitations, including implementation constraints, diverse learner needs, evolving AI and Assistive Technologies, and the complex interplay of ethical, technical, and pedagogical considerations.
By combining conceptual reflection with these exploratory data points, the study aims to contribute to broader debates on the design and implementation of higher technical education in complex, multi-institutional contexts. The work is supported by the extensive bibliography [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105] reported in the references section.

2. Introduction

Technical education beyond secondary school has become a cornerstone for workforce development in the 21st century, responding to the accelerating demand for specialized skills in rapidly evolving labor markets [1,2]. Unlike traditional academic pathways, post-secondary technical education (hereafter referred to as higher technical education) emphasizes application-oriented training that equips learners with practical and transferable skills. Globally, there is a growing reliance on flexible, modular, and technology-enhanced programs that support lifelong learning, reskilling, and upskilling across industries [3,4].
The integration of artificial intelligence (AI) and digital technologies into vocational and technical training is increasingly recognized as essential for preparing students for future workplaces [21,22,23,24,25,26]. AI literacy, interdisciplinary approaches, and ethical considerations are now core components of curricula, helping learners navigate complex socio-technical systems responsibly [22,23,25,28,29,30]. Collaborative co-design involving academia, industry, and policy stakeholders further enhances relevance and adaptability, but also introduces challenges, including alignment of priorities, integration of diverse perspectives, and evaluation of educational impact [24,26,31].
Countries such as Germany and Switzerland exemplify dual models combining classroom instruction with in-company training, while nations like Singapore and South Korea align curricula with emerging sectors such as AI and green innovation [4,16,18]. The United States emphasizes accessible, community-based technical education responsive to local labor market needs [16,17]. These international experiences illustrate both opportunities and potential pitfalls in implementing multi-stakeholder, modular programs, providing context for reflection on the Spoke 4 approach.
Modern technical education increasingly emphasizes multidisciplinary learning, stakeholder co-design, and the integration of AI and digital skills into curricula [21,22,23,24,25,26,31]. While these approaches hold promise, challenges such as resource constraints, variable stakeholder engagement, and adaptation to evolving technology and labor markets must be critically considered. Embedding ethics, responsible innovation, and critical thinking alongside technical training can help navigate these challenges, preparing graduates to implement advanced technologies responsibly and adaptively [22,23,25,28,29,30].

3. Aim and Organization of the Commentary

The aim of this commentary is to frame the evolution of higher technical education within the Italian innovation ecosystem, in particular in the so-called Istituti tecnici superiori (ITS) academy, focusing on the conceptual contributions developed through Rome Technopole under the PNRR framework, with particular attention to Spoke 4 and the participation of the Istituto Superiore di Sanità (ISS). This work seeks to critically reflect on how multi-stakeholder collaboration, modular learning, and the integration of AI and advanced technologies can shape future-ready technical education. In doing so, it highlights both the opportunities and the conceptual challenges of implementing such initiatives in complex, multi-institutional contexts.
Specifically, the commentary discusses the strategic positioning of Rome Technopole within the PNRR, emphasizing its potential role in driving research-informed innovation and fostering advanced professional training. It also reflects on the institutional and scientific contributions of ISS, including its regulatory, biomedical, and translational expertise, which support the design and implementation of AI-oriented, ethically informed learning experiences. Finally, the discussion considers how Spoke 4’s structure and approach may help inform broader efforts to integrate interdisciplinary competencies, ethical awareness, and AI-enabled technologies into higher technical education, while acknowledging potential limitations and challenges in multi-stakeholder engagement.
The manuscript is structured to guide the reader through these reflections. Following the introduction reported in Section 2 and this Section 3, the Section 4 presents Rome Technopole as a PNRR-funded innovation ecosystem, describing its objectives in research and technology transfer.
Section 5 focuses on the role of the Istituto Superiore di Sanità (ISS) in Spoke 4, highlighting both its participation in co-designing AI- and Assistive Technology-integrated curricula (Section 5.1) and the empirical insights, reported in a nutshell, gained from pilot module evaluation (Section 5.2), offering insights on educational design, translational approaches, and the alignment of professional training with regulatory, ethical, and sectoral priorities.
Section 6 engages in a critical discussion, structured around three complementary perspectives: Section 6.1 interprets findings and explores their educational implications, Section 6.2 compares the Spoke 4 approach to existing literature on co-design and multidisciplinary strategies, and Section 6.3 outlines future directions, limitations, and practical implications for AI and Assistive Technology education.
The final Section 7, the conclusions, summarizes key insights and considerations, highlighting lessons that may inform the potential replicability of the Spoke 4 model at national and international levels.

4. Rome Technopole Within the PNRR Framework and the Role of ISS

The transformation of higher technical and professional education and innovation ecosystems occurs within broader national and European policy frameworks addressing digital transition, industrial competitiveness, and workforce reskilling [1,2,3,4,6]. In Italy, this approach has been embedded in the Piano Nazionale di Ripresa e Resilienza (PNRR) [7], financed through the European NextGenerationEU program [8]. Mission 4 of the PNRR specifically targets education, research, and innovation ecosystems as structural levers for long-term socio-economic resilience.
Within this context, Rome Technopole (https://www.rometechnopole.it/ (accessed on 11 August 2025)) has developed as a regional innovation ecosystem that brings together universities, public research organizations, industrial partners, and governance institutions. Rather than functioning as a traditional consortium, it operates as a coordinated platform facilitating interactions across multiple institutional layers. Participation spans major universities in the Lazio region, national research institutions—including the Italian National Institute of Health (ISS), CNR, ENEA, and INFN—regional and municipal bodies, and industrial stakeholders across sectors from aerospace and energy to digital technologies and advanced manufacturing. This configuration reflects a multi-actor environment where educational, research, industrial, and public governance perspectives intersect. For the complete list of participating entities, readers can refer to the official Rome Technopole website.
Rome Technopole is structured around six thematic Spokes, each addressing a distinct dimension of the innovation and training ecosystem. These encompass applied research, technology transfer and entrepreneurship, university education and industrial PhDs, professional technical education, outreach and lifelong learning, and open research infrastructures with industrial collaboration. The initiative is structured into six complementary “spokes,” each focusing on a different dimension of research, education, and innovation [9,12,62]. Spoke 1 is dedicated to applied research, technological development, and fostering innovation. Spoke 2 focuses on technology transfer, promoting new entrepreneurship, and supporting business incubation and acceleration. Spoke 3 addresses university-level education, including industrial PhD programs and efforts to enhance internationalization. Spoke 4 is centered on professional university education in technology, aiming to develop practical skills aligned with industry needs. Spoke 5 emphasizes outreach, public engagement, and lifelong learning opportunities to broaden societal impact. Finally, Spoke 6 is devoted to open research infrastructures, joint laboratories, and higher education initiatives that involve industrial collaboration, creating synergies between academia and industry.
The ISS is actively involved across all six Spokes, contributing to educational initiatives, applied research projects, technology development, and co-design activities. This broad engagement supports ISS in providing regulatory, biomedical, and public health perspectives while interacting with multiple stakeholders, ensuring that initiatives across the ecosystem are designed to integrate technical, societal, and ethical considerations. The polyhedral structure of Rome Technopole facilitates opportunities for multi-stakeholder collaboration, co-design processes, and integrated planning, creating a framework where education, research, and project-based activities can be aligned with industrial needs, public priorities, and strategic national objectives [21,22,23,24,25,26,32].

5. The Role and the Activities of the Istituto Superiore di Sanità (ISS) in Spoke 4

5.1. ISS Participation in Spoke 4

Within Spoke 4, which focuses on professional higher technical education, ISS has been active in co-designing multidisciplinary and AI-integrated curricula.
The educational development proceeded in two phases. The first phase implemented a pilot module Artificial Intelligence between History and Innovation: A Multidisciplinary Teaching Approach, co-developed with universities, ITS institutions, industry partners, and public health professionals. This module integrated AI literacy with ethical reasoning, combining historical perspectives, technical concepts, and social responsibility, and was iteratively refined based on stakeholder feedback [78]
The second phase expanded the curriculum to include Assistive Technologies and accessibility. Stakeholders contributed to defining thematic priorities, suggested content, and shaping teaching and assessment methods, ensuring a focus on inclusive design, user-centered approaches, and transparent AI applications. ISS provided regulatory and biomedical guidance throughout, anchoring the curriculum in scientific and ethical standards [78,79,80,81,82,83].
ISS’s involvement across all Spokes supports a coordinated, multi-stakeholder, co-design approach, which aims to link educational activities with research, technology transfer, and public governance while embedding AI literacy, ethical considerations, and regulatory perspectives into professional technical education [78,79,80,81,82,83].

5.2. Empirical Insights from Pilot Module Evaluation

To contextualize the practical implementation of Spoke 4’s educational interventions, the pilot module, in Phase One, Artificial Intelligence between History and Innovation: A Multidisciplinary Teaching Approach was developed and evaluated according to a structured, phased methodology originally described by Esposito et al. (2025) [78]. A second module was subsequently designed using a similar approach in Phase Two [79]. The evaluation framework combined multi-layered stakeholder engagement with mixed-method data collection, enabling reflection on perceived relevance, clarity, and potential applicability of the curriculum within higher technical education.

5.2.1. Module 1: AI Between History and Innovation

The first module comprises 18 thematic “cards”, each representing a self-contained, modular learning unit. Each card is designed to be independently accessible, allowing learners to navigate topics in any sequence based on their prior knowledge, interests, or professional priorities. This non-linear design encourages personalized learning paths, where students can focus on areas most relevant to their context or curiosity.
Each card includes multiple-choice questions to support formative assessment and reinforce learning, brief didactic content, visual or textual examples, and references for further in-depth exploration. Some cards present case studies that link historical AI developments to contemporary applications, while others integrate ethical considerations, practical tools, or sector-specific scenarios. This approach is intended to foster critical reflection and help learners connect theoretical insights with practical contexts.
The card-based format also supports flexible delivery modes. Modules are suitable for in-person instruction, fully online sessions, or blended learning environments, providing instructors with adaptable teaching options and learners with self-directed study opportunities. This structure is particularly advantageous for professionals in continuous education or those balancing work and study, allowing for incremental engagement and modular completion.
Development of the first module followed four steps: Step 1 involved needs identification through thematic roundtables with educators, trainers, industry representatives, and public health professionals, establishing a consensus-driven framework for transversal AI-and-ethics content. Steps 2–4 included collaborative module design, delivery via a Computer-Assisted Web Interview (CAWI) focus group, and a mixed-method evaluation combining quantitative scales with open-ended feedback [78]. This approach balanced structured guidance with qualitative insights, enabling exploratory assessment of the module’s educational contributions.
A total of 37 participants voluntarily completed the CAWI evaluation, representing ~94% of those directly involved. The cohort consisted primarily of professional educators and trainers, supplemented by experts in digital technologies, innovation, and policy advisory roles. ISS members were excluded to prevent bias, and responses were collected anonymously to reduce social desirability and hierarchical effects.
Quantitative assessment used Likert-scale items (1–5) addressing relevance, clarity, coverage, quality of examples, employability impact, and overall module quality. All mean scores exceeded the neutral midpoint (3.0, p < 0.001), indicating strong positive perceptions. Relevance to learners’ needs scored 4.19 on average, overall quality 4.14, and the Net Promoter Score (NPS) exceeded 72, indicating high satisfaction [27,60,69], reflecting high perceived endorsement and potential for positive peer recommendation.
Sectoral applicability indicated Healthcare and Industry as universally relevant (100%), with Digital Transformation (78%) and Consumer Applications (73%) also frequently cited, highlighting the module’s transversal value. Qualitative feedback emphasized the interdisciplinary nature of the content, integration of historical and ethical perspectives, and clarity of pedagogical elements. Suggestions for improvement included expanding real-world case studies, fostering collaborative online forums, and promoting international academic partnerships [78]. These insights suggest potential to stimulate reflective practice and cross-sectoral knowledge transfer.

5.2.2. Module 2: Accessibility and Assistive Technologies (AT)

In Phase Two, 37 participants prioritized thematic areas for further development. Among five options—including Cybersecurity, Sustainability, Transversal Soft Skills, and Digital Literacy—Accessibility and Assistive Technologies (AT) emerged as the most selected (χ2 test, p < 0.01), highlighting its perceived strategic importance in combining technical innovation, socio-organizational impact, and multidisciplinary educational potential [79].
The second module adopted a similar card-based structure, consisting of 10 thematic cards. Each card presents self-contained content, multiple-choice questions, and suggestions for deeper exploration. The focus of the module is on AI-enabled accessibility solutions, illustrating how intelligent technologies can enhance assistive devices, inclusive design, and personalized user experiences. Like the first module, it supports in-person, online, or blended learning, enabling flexible engagement and modular completion. The card design encourages learners to experiment with real-world scenarios, analyze ethical implications, and understand the societal impact of technological innovation in accessibility.
The NPS for the AT-focused module was +54.1, considered high. Promoters (scores 9–10) were 64.9%, passives 24.3%, and detractors 10.8% [79], reflecting a perceived satisfaction and alignment with participant expectations. Thematic feedback emphasized the perceived applicability of AI in real-world assistive contexts, the clarity of case studies, and usefulness of self-directed exploration.

5.2.3. Combined Overview

Together, these modules demonstrate how structured, card-based, multi-stakeholder educational design may create flexible, self-directed learning experiences while maintaining alignment with strategic educational and professional goals. The card approach supports autonomy, personalized learning paths, and incremental engagement, allowing learners to navigate topics independently, engage with formative assessments, and pursue in-depth inquiry.
Quantitative metrics, sectoral relevance, thematic preferences, and satisfaction data are presented as indicative insights of the modules’ potential utility and pedagogical contribution. Importantly, the card-based structure is designed to bridge theory and practice, support diverse learning contexts, and encourage interdisciplinary understanding, key elements for developing contemporary technical and ethical competencies in higher technical education.

6. Discussion

6.1. Interpretation of Findings and Educational Implications

Spoke 4 implements a multidisciplinary approach, integrating AI and ethics into professional university education to prepare learners for complex, technology-driven environments. The educational pathway is structured in two phases: Phase 1, the pilot AI-and-Ethics module, and Phase 2, the co-development of an Assistive Technologies (AT) and accessibility module [78,79]. Active stakeholder engagement—including universities, ITS institutions, industry, and public health professionals—helped ensure that the curriculum is aligned with perceived real-world demands, supporting exploratory development of technical skills, ethical reasoning, and inclusive perspectives [28,32].
Despite rapid AI adoption, a persistent digital and skills divide limits students’ ability to integrate AI responsibly [84,85,86]. While many young learners actively use generative AI tools, a significant portion lacks digital literacy, critical thinking, and problem-solving skills, increasing the risk of over-reliance and negative psychosocial outcomes [86,87,88,89,90,91,92]. Phase 1 addressed these gaps by embedding ethical reflection and responsible AI use within practical exercises [29,30].
Phase 2 emphasized AT and accessibility, guided by international standards [28,29,32,33,34]. Inclusion was considered a foundational principle, shaping curriculum design, technology deployment, and assessment strategies. Iterative suggests that accessibility-focused modules may improve learners’ understanding of technological applications and their societal implications, while remaining exploratory [46].
Implementation experience highlights several key points. Skill gaps in AI literacy and familiarity with AT remain uneven, and unmonitored AI use can affect cognitive autonomy, self-regulation, and wellbeing, underscoring the value of structured guidance and reflective exercises [87,88,89,90,91,92,93,94,95]. Early stakeholder engagement proved crucial for shaping curriculum content, pedagogical strategies, and learning objectives [28,32]. Similarly, ongoing professional development for instructors was essential to translate AI and AT innovations into meaningful educational experiences [80,81,86]. Furthermore, accessibility and inclusivity should be treated as fundamental design principles rather than secondary considerations [28,32]. Finally, embedding ethical reflection and societal awareness in learning activities may support the development of a professional identity grounded in responsible decision-making [29,34].
Collectively, these insights indicate that integrating AI literacy, responsible AT use, and inclusive design has the potential to foster learners’ technical, ethical, and social awareness, preparing them to navigate interdisciplinary, technology-rich professional contexts in an exploratory and formative sense.

6.2. Comparison to Existing Literature: Insights from Co-Design and Multidisciplinary Approaches in Educational Innovation and AI Integration

Comparing co-design and multidisciplinary approaches provides a lens to understand how educational innovations and technology development may be participatory and intellectually integrative, ensuring solutions are contextually grounded, methodologically sound, and aligned with perceived user needs.
In recent years, research in educational innovation and AI integration has highlighted two complementary but distinct approaches: co-design with stakeholders and multidisciplinary collaboration. Both aim to enhance learning outcomes and develop solutions that are robust, context-aware, and relevant to real-world needs. Comparing these approaches allows us to see how they differ in focus while remaining mutually reinforcing, and provides a framework to evaluate how structured educational programs—like those implemented in the Spoke 4 initiative—can support these principles in practice.
The co-design approach emphasizes the active engagement of multiple stakeholders in the creation process. For example, some studies explore collaboration between academia and industry to manage curriculum changes [24], while others use multi-stakeholder, experience-based design processes to develop educational frameworks [28]. Theoretical models have been proposed for integrated co-design across diverse groups [44], and design thinking combined with developmental evaluation has been applied to co-construct educational innovations in schools [46]. Beyond formal education, co-design can also guide workforce readiness strategies, aligning education with future labor market needs [77]. Overall, co-design focuses on understanding user needs and creating participatory structures that allow diverse voices to shape solutions. In comparison, while multidisciplinary approaches may also involve collaboration, their primary emphasis is on integrating expertise rather than facilitating stakeholder participation. Spoke 4 explicitly aligns with these principles, structuring learning modules and pilot activities so that students, educators, and industry partners can iteratively co-create content and projects, supporting perceived relevance and practical applicability.
A multidisciplinary or integrated approach emphasizes combining knowledge and methods from different fields to address complex challenges. Studies have explored interdisciplinary frameworks for AI literacy in education [21,22,42,45,49,50], showing how integrating technological, pedagogical, and ethical perspectives may foster holistic learning and innovation. Collaborative learning and skill development are emphasized in educational contexts [52,64,65], while ethical considerations benefit from a multidisciplinary lens [68,73]. This approach supports critical understanding and the capacity to design solutions that draw on diverse expertise, making it particularly suited to complex, systemic problems. In our Spoke 4 modules, this multidisciplinarity is reflected in the combination of AI, digital literacy, ethics, and technical problem-solving exercises, encouraging learners to integrate perspectives across fields.
While these approaches share common ground—both value collaboration and active participation—their emphases differ. Co-design primarily focuses on social dynamics and stakeholder engagement, aiming to surface real needs and preferences. Multidisciplinary approaches, in contrast, focus on cognitive and methodological integration, leveraging expertise from multiple fields to tackle complex challenges. When combined, they complement each other, producing approaches that are both contextually grounded and methodologically robust. The Spoke 4 experience illustrates how these approaches can be operationalized together, with iterative co-creation embedded within a multidisciplinary curriculum, supporting exploratory educational outcomes.
Importantly, co-design and multidisciplinary strategies extend beyond classrooms and laboratories. They offer a methodological lens to address complex challenges across digitally mediated and technology-intensive environments. By emphasizing iterative stakeholder engagement, diverse perspectives, and the integration of ethical, technical, and human-centered considerations, these approaches can inform the design of AI systems, assistive technologies, and educational programs, supporting learners in navigating complex, technology-rich environments.
Recent studies illustrate this breadth. Research on autonomous taxis in China demonstrates the importance of co-design and stakeholder-centered methods in technology adoption [96,97,99]. Mustafa et al. [96,97,99] use mixed-method analyses to examine how demographic differences, trust, and behavioral dynamics influence urban adoption of AI-driven cabs, highlighting the need to consider multiple user perspectives in system design. Similarly, studies of online communities show how social cohesion, reciprocity, and communication climate drive participation and information sharing [98,100]. Jamil et al. [98,100] reveal that these factors may affect collaborative learning and knowledge dissemination, providing insights that extend directly to educational and assistive technologies. These findings align with our approach in Spoke 4, where digital collaboration platforms and AI-driven tools support participatory learning and knowledge exchange.
These examples underscore that co-design and multidisciplinary approaches are not limited to classroom settings. Instead, they provide a structured framework for bridging human-centered design with technical feasibility and ethical reflection. Applying these principles can help educators and technology developers create AI-driven tools, learning environments, and assistive systems that are responsive to user needs, contextually informed, and socially robust.

6.3. Future Directions, Limitations, and Implications

The pilot development of the “AI and Algorethics” module [78] demonstrates that a card-based, modular structure may support flexible pedagogical delivery—including face-to-face, blended, and fully online e-learning formats. Each of the 18 learning cards integrates focused technical content, historical overview, ethical reflection prompts, and suggested research activities. This format is intentionally designed to support scenario-based and inquiry-oriented learning, enabling learners to engage with AI concepts, societal implications, and ethical dilemmas in ways perceived as adaptable to diverse educational environments. The complementary design of the Assistive Technologies (AT) module leverages similar principles, inheriting the modular card structure and its emphasis on interdisciplinary critical reflection while situating content in sector-specific contexts such as healthcare, accessibility, and user-centered design.
The modular, card-based format [78,79] supports learner flexibility and curriculum adaptability: instructors can select, sequence, and adapt cards according to local needs, institutional constraints, and learner profiles. This adaptability is particularly valuable in technical and vocational education systems, where learners’ time, prior knowledge, and professional expectations vary widely.
However, while the pilot evaluation indicated positive participant perceptions regarding relevance, clarity, and engagement, it is important to situate these findings within broader evidence and known limitations in AI education research. Recent systematic reviews of AI ethics education highlight persistent methodological gaps: many instructional interventions deploy progressive pedagogies such as case studies or projects, but they often lack robust, well-supported assessment techniques that can determine whether learners actually develop ethical reasoning skills or deeper conceptual understanding of AI and its socio-technical impacts [67,101]. Without standardized, outcome-oriented evaluations, high satisfaction scores—though encouraging—cannot reliably indicate learning gains or long-term competence development.
Moreover, the broader literature on AI integration in education [102,103,104,105]—including preprint studies [103,105] that provide early insights into emerging topics—highlights the continuous evolution of AI, documenting ethical and pedagogical challenges that extend beyond curricular design. Systematic reviews and analyses have identified risks such as privacy invasion, data leakage, algorithmic bias, and opaque decision-making in educational AI systems, alongside concerns about unintended consequences for student development and instructional practice [102,103,104]. These ethical risks suggest that embedding ethical reflection is necessary but not sufficient; curricula must also equip learners with tools to critically assess AI systems’ impacts on fairness, autonomy, and equity in real contexts. This continuous evolution also affects Assistive Technologies, which increasingly incorporate AI-driven features, requiring that both technical content and ethical considerations be regularly updated to reflect emerging capabilities and societal implications.
The rapid emergence of generative AI (GenAI) further complicates curriculum design. Recent systematic work shows that while GenAI tools can support personalized feedback and efficiency gains, they also present risks related to academic integrity, superficial learning, and teacher oversight, indicating gaps in current pedagogical frameworks for guiding responsible use [102,105]. These findings underscore that ethical and technical literacy about AI cannot be limited to introductory exposure but must engage learners with complex socio-technical dynamics of real AI deployments.
Another limitation of the current pilot is its evaluation design. The mixed-method survey captured perceptions from stakeholders directly involved in module development and review, but it does not yet provide longitudinal evidence or comparisons with control groups that would clarify actual learning outcomes or behavioral changes. Future work should prioritize developing rigorous assessment instruments—including performance-based tasks, reflective portfolios, and pre/post measures—to better explore ethical reasoning and AI literacy growth across diverse learner groups.
In addition, scaling and transferring the model internationally will require attention to contextual variations in institutional capacity, pedagogical culture, and resource availability. Practices that work in one network of vocational partners may need adaptation in contexts with different regulatory environments, faculty development structures, or digital infrastructures.
Taken together, these considerations suggest that while the modular, card-based approach offers a promising foundation for flexible and context-responsive AI education, continued refinement, empirical evaluation, and ethical grounding are needed to ensure that such educational innovations can produce reliable, transferable, and socially responsible learning outcomes. By aligning curriculum design with emerging evidence on both the potentials and limitations of AI in education, future iterations may better support learners’ preparation for complex, technology-rich professional environments [67,101,102,103,104,105].

7. Conclusions

The Spoke 4 modules, encompassing AI and Assistive Technologies (AT), are designed with the aim of supporting professional education. Stakeholder engagement—involving universities, industry partners, and public health professionals—helped ensure perceived alignment with technological trends, ethical considerations, and societal needs.
The modular design facilitates scenario-based and inquiry-oriented learning and is adaptable across delivery formats (face-to-face, blended, online) and institutional contexts. Ethical and interdisciplinary reflections are embedded in the structure, offering a potential foundation for responsible engagement with AI and AT. Inclusion and accessibility are emphasized, particularly through the AT module, highlighting perceived support for equitable participation.
Nonetheless, several challenges remain. The effectiveness of the card-based approach, the clarity and balance of ethical content, and integration across diverse institutional and cultural contexts require further investigation. The rapid and continuous evolution of AI technologies adds complexity, underscoring the need for curricula to remain flexible, iterative, and responsive to emerging tools, methods, and ethical considerations. Assessing alignment with evolving professional standards and refining content to maintain relevance are ongoing priorities.
Future work should focus on iterative refinement, rigorous evaluation, and the development of assessment strategies to support continuous improvement. This includes exploring modular sequencing, contextual adaptation, and strategies to enhance perceived ethical reasoning and technical understanding in professional settings.

Author Contributions

Conceptualization, D.G.; methodology, D.G. and G.E.; software, All authors; validation, All authors; formal analysis, All authors; investigation, D.G., F.F., M.S. and G.E.; data curation, All authors; writing—original draft preparation, D.G.; writing—review and editing, G.E., M.S., E.I., L.B., S.C., F.F., V.T. and D.G.; supervision, D.G. and M.S.; project administration, D.G., F.F. and M.S.; funding acquisition, D.G. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by the Italian National Recovery and Resilience Plan (PNRR), Mission 4—Education and Research, Component 2—From Research to Business, Investment 1.5, funded by the European Union—NextGenerationEU (PNRR project number ECS00000024, Rome Technopole).

Institutional Review Board Statement

Ethical review and approval were waived for this study because the activities were part of the Rome Technopole project, funded by the European Union through the NextGenerationEU initiative under the Italian National Recovery and Resilience Plan (PNRR—Mission 4, Component 2, Investment 1.5) and the National Complementary Plan (PNC). These activities were included in the original, approved project plan and are implemented as standard routine operations. Data collection was limited to structured information from planned focus groups, and all data were fully anonymised to enhance robustness. Given that the activities are routine, planned, and anonymised, ethics committee approval and individual informed consent were not required.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors wish to acknowledge that the ChatGPT Mini free version was used to assist with English language translation. All scientific content, interpretations, and conclusions are the sole responsibility of the authors.

Conflicts of Interest

The authors are the original developers of the interactive educational modules discussed in this commentary. The development of these modules was conducted as part of their institutional duties within the assigned work package at the Istituto Superiore di Sanità (ISS), as part of the Rome Technopole project (ECS00000024), which is publicly funded under the Italian National Recovery and Resilience Plan (PNRR) within the European Union’s NextGenerationEU programme. The authors did not receive any external commercial or personal financial compensation for this work. This relationship did not influence the objectivity or integrity of the reported work.

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