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            <title><![CDATA[Fostering AI Literacy in Schools: An Analysis of Pre-service Teachers’ Perceptions of AI Literacy in Initial Training]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.296</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The integration of Artificial Intelligence (AI) in education prompts the need for an AI literacy program for pre-service teachers, essential for the ethical implementation of these technologies in early education. This study investigates pre-service teachers' perceptions, attitudes, and perceived challenges regarding the integration of AI literacy within kindergarten and primary school settings. Employing a qualitative approach, data were gathered from 51 university students following a training module at the University of Verona. Analysis involved inductive content analysis of open-ended reflections. Respondents identified a lack of basic skills and, indeed, the key role of AI literacy training path for an effective integration of AI in classes. Besides this, they highlighted the need to develop a critical awareness that allows them to promote a responsible and critical use of this tool. Finally, they note that ethical principles and practical actions are core elements of relevant guidelines. In conclusion, the study shows pre-service teachers are developing a human-centred approach to AI. However, transitioning these "directional hypotheses" into classroom reality requires institutional support that empowers teachers as active agents of curricular innovation.]]></description>
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            <title><![CDATA[Generative Artificial Intelligence in the Continuous Professional Development (CPD) of Spanish Teachers in Portugal]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.295</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Introduction: Generative AI has shifted attention toward pedagogical integration, risks, and relevance for Spanish language teaching and continuing professional development. Objective: To analyse teachers’ perceptions of AI in pedagogy, personalization, and future integration. Methods: Qualitative documentary and reflexive thematic analysis of 30 final reports from an accredited b-learning CPD course for Spanish teachers in Portugal. Results: Teachers valued AI for planning, materials design, assessment, efficiency, personalization, inclusion, and autonomy, but rejected teacher replacement and called for stronger literacy, ethics, and training. Conclusion: AI is useful pedagogical support, but its value depends on mediation, critical use, and contextualized integration.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Co-Creating Open Learning Materials for the Digitalisation of Energy: A Collaborative Model for Public and Expert Engagement]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.292</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The Every1 project has developed a large, openly licensed collection of learning materials to support citizens and professionals engaging with Europe’s digitally mediated energy transitions. The project adopted an iterative methodology that combined a cyclical production pipeline, embedded co-creation, and multimodal user testing across six development cycles. Stakeholders from fourteen countries contributed through interviews, workshops, surveys, webinars and roadshow activities, generating insights that shaped both the content of the learning materials and the design process. Findings highlight the value of relational engagement, linguistic and contextual localisation, and of offering a diverse portfolio of materials to meet varied learner needs. The resulting Every1 model provides a transferable framework for co-creating open learning materials in complex sociotechnical domains. While the learning materials consistently improved understanding, the evaluation findings revealed a persistent gap in behavioural activation, indicating the need for future work that integrates motivational and structural factors. The model also contributes to wider debates on digital learning design, public engagement and the role of openness in supporting equitable energy transitions.]]></description>
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        <item>
            <title><![CDATA[Human–AI collaboration to enhance reflective teaching practice: A rapid review]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.294</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Artificial intelligence is rapidly reshaping teacher education, raising new questions about how reflective and reflexive practice can support teachers’ professional identity, and pedagogical decision‑making in AI‑mediated environments. This study conducts a rapid review following PRISMA 2020 guidelines, analysing 54 publications from Web of Science and Scopus through thematic analysis to examine how research addresses AI‑mediated teachers’ reflective practice. The results show that although AI use as a significant impact on teacher competence, pedagogical innovation and explicit engagement with reflective practice are still scarce, highlighting the need for structured, human‑centred reflective frameworks in future research.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Revisiting the Online Learning Experience: a conceptual and visual framework for online education]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.291</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The extensive experience of the Learning for Life Centre (LfLC) in designing and delivering online education has consistently been underpinned by the Online Learning Experience (OLE) as our pedagogical model. Invariably, the constant evolution of the educational landscape prompted a fresh look at the principles that support this model, and a re-assessment of the way we collaborate with different actors at the early stages of course design. As a result,&nbsp; this experience paper puts forward a revised conceptual framework, where the OLE principles are formally embedded within quality assurance standards. We also introduce a tool that both works to visually represent the OLE principles, and as a reflection instrument to help human creativity and originality in course design flourish.]]></description>
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            <title><![CDATA[Rethinking Mathematics Classrooms in Higher Education]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.280</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Within the scope of the Applied Mathematics course taught at the School of Technology and Management of the Polytechnic Institute of Bragança, an active learning methodology was implemented, incorporating key elements such as: Continuous and constructive feedback during classes; Annual adaptation of the methodology based on student suggestions; Group-based learning, promoting collaboration and social comfort; A safe environment for questioning, essential for teaching advanced mathematics; Diversification of assessment tools, ensuring fairness and inclusion; Integration of international students, with flexible use of languages and bilingual materials; Encouragement of the conscious use of Generative Artificial Intelligence tools; Use of collaborative digital platforms that promote transparency, co-authorship, and resource sharing. This pedagogical practice fosters skills associated with the Individual Development Goals, such as autonomy, critical thinking, creativity, and collaboration, while also aligning with European standards. This practice not only promotes academic success but also actively contributes to students’ personal, professional, and scientific development, creating a solid foundation for lifelong learning and their integration into an increasingly demanding and technology-driven job market.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Leading Digital Transformation in Higher Education: A Practitioner Framework Grounded in a Decade of Evidence]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.284</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The digital transformation of higher education has accelerated rapidly, leaving institutions grappling with common questions: How does one build an online campus that is both scalable and academically rigorous? How does one prepare thousands of faculty for an environment in which many were never trained to teach? This paper draws on eighteen years of executive leadership across four institutional contexts in the United States and Puerto Rico, spanning more than 350,000 student records with retention sustained at 89–96% across twelve consecutive semesters. A four-pillar framework — Strategic Planning with Data, Culture and Talent Development, Responsible AI Integration, and Human-Centered Change Management — is presented alongside a three-dimensional AI integration model developed by the author.]]></description>
            <category>ARTICLE</category>
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            <title><![CDATA[AI-TPACK in Formal Education: A Qualitative Systematic Review]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.289</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This qualitative systematic review synthesizes empirical research that uses the TPACK framework to examine AI integration in formal education. PRISMA-guided procedures were applied to Scopus-indexed, peer-reviewed journal articles published in English between 2021 and 2026. The search yielded 278 records; after eligibility checks and manual screening, 116 empirical studies were included for full-text analysis. Deductive coding, aligned with TPACK components, was combined with inductive reflexive thematic analysis to identify patterns in conceptualization and enactment. Results indicate substantial variation in AI-TPACK operationalization, ranging from psychometric self-report measures and predictive models to professional learning accounts, practice-oriented design tasks, and critiques of traditional instruments. Reported challenges extend beyond technical proficiency to pedagogical alignment, ethical judgment and accountability, assessment and feedback validity, and institutional policy constraints. A recurring theme is divergence between perceived competence and enacted classroom use, emphasizing the need for practice-proximal evidence and context-sensitive support. These insights guide future research priorities.]]></description>
            <category>ARTICLE</category>
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            <title><![CDATA[A methodology for an inclusive and accessible digital curriculum]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.285</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[In today's educational landscape, an inclusive and accessible digital curriculum is essential for supporting diverse students and equitable learning environments. An inclusive curriculum not only accommodates students’ needs but also promotes engagement, participation, growth and empowerment among students, enhancing academic success and wellbeing. This paper presents a participatory methodology for creating an inclusive curriculum framework, embedding it in processes and practice, and reviewing digital curricula in order to enhance inclusive practice.
The Arden Inclusive Curriculum Framework was developed using a participatory approach with diverse staff and students. Once approved, it was embedded in validation, quality and learning design processes for all new programmes and modules. The Arden EDI team then conducted an extensive review of the 225 modules that pre-dated the framework but were still being delivered to students. This involved page-by-page analysis to identify barriers to accessibility and inclusivity, and suggest changes in accordance with the framework. The review identified 43,378 areas where current practice is not aligned with best practice in accessibility and inclusion. These areas align to specific EDI themes, including issues with digital accessibility, lack of diverse representation in certain curriculum areas, non-inclusive language, lack of trigger warnings on distressing content, and areas where activities or content should be more accessible for disabled or neurodivergent learners.
The findings of this study show that diversity of academic staff alone does not guarantee inclusive curricula; there is a need for a purposive approach to inclusion and accessibility. By sharing our methodology and findings, we aim to provide a replicable framework for institutions seeking to enrich their own curricula towards a more inclusive educational environment.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Exploring Representational and Liminal Digital Spaces in Teacher Education]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.287</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This study explores how digitally mediated learning environments designed as representational and liminal spaces (Galamba 2025) can support collaboration, peer learning, and formative assessment in postgraduate teacher education. Building on Lefebvre’s (1991) theory of the social production of space and contemporary work on liminality in higher education, the research investigates the use of visually structured digital boards to represent the learning journey of each session and enable participants to access full session content, interact with them, contribute ideas, responses, and make reflections in a shared environment.
Data were collected through a mixed-methods approach, including a questionnaire and focus groups with trainee teachers. This research data analysis is being finalised. Preliminary findings from the questionnaire suggest that the use of representational digital boards supported both engagement and peer learning. A majority of participants reported that the boards helped them understand the structure of the sessions (54% helpful or very helpful) and made the learning experience more engaging and easier to follow (68% slightly engaging or engaging). The collaborative dimension of the environment emerged as a key feature: 76% agreed that the boards helped them learn from their peers, while 70% found peer contributions useful for understanding the content. Seeing peers’ responses appear on the board during sessions was perceived as motivating (63%), and 62% reported that the boards increased interaction with both tutors and peers. In addition, 69% agreed that the platform increased the amount of feedback provided by the tutor during the sessions.
The preliminary findings suggests that representational digital spaces may extend the pedagogical possibilities of teacher education by making learning processes visible and by enabling forms of collaborative participation that are often difficult to achieve in conventional lesson formats.]]></description>
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        <item>
            <title><![CDATA[Bridging Technology Quality and Pedagogical Quality: A Two-Level Quality Assurance Stack for Human–AI Collaboration in Digital Learning]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.286</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The rapid integration of artificial intelligence into digital learning has surfaced a consequential challenge: quality assurance frameworks are evolving far more slowly than the technologies they are meant to govern. This experience paper reports on two complementary inquiries examining quality assurance in AI-enabled digital learning at two distinct but interdependent levels. The first, conducted through a multimodal engagement with the Quality Matters AI Working Group culminating in a design sprint at the QM Board Retreat in November 2025, examined quality assurance at the system level, exploring how organizations might govern, guide, and improve AI adoption in ways that preserve educational integrity. The second, conducted in partnership with D2L between November and December 2025, examined quality assurance at the artifact level, investigating where current evaluation frameworks fall short when applied to AI-generated educational content.
Together, these bodies of evidence converge on a shared insight: quality assurance in AI-enabled environments cannot be reduced to checklists, automated scores, or static rubrics. Artifact-level evaluation without system-level governance produces inconsistent, acontextual judgments; system-level governance without artifact-level evidence produces policy untethered from practice. Drawing on human-centered AI (Shneiderman, 2022), TPACK-informed perspectives on educator knowledge (Gunder &amp; Ford, 2025; Koehler &amp; Mishra, 2009), peer-review approaches to online course quality (Legon &amp; Garrett, 2018), and Hau's (2025) concept of Relational Quotient, the paper argues that quality assurance is an ecosystem problem whose relational dimensions form the load-bearing structure on which technical and pedagogical quality both depend.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Remixing the Future: A Longitudinal Study of Crowd-Sourced Scenario Design in Educational Technology]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.281</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Educational futures work tends to be bounded by short planning horizons, shaped by narrow circles of decision-makers, and disconnected from the communities whose learning those plans are meant to serve. Participatory, narrative-driven methodologies offer a way to close this gap by collapsing the distance between speculative imagination and operational strategy. Across four iterations (2023–2026), the 100 Year EdTech Project has convened cross-sector participants in a crowd-sourced scenario design initiative grounded in futures literacies, narrative digital learning practices, and open remix. The methodology functions as infrastructure for collective imagination, producing immediate, actionable outputs adapted by partner organizations for varied audiences, timelines, and thematic foci. Thematic analysis at two levels, of the eight scenario videos opening the 2026 Design Summit and the eight community presentations closing it, identifies an evolution from speculative narrative to operational strategy: more shared common ground emerged across scenarios while distinctive concerns remained networked. Implications for distance education center on how crowd-sourced foresight methodologies democratize strategic imagination across institutional, geographic, and role-based boundaries.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Eyes, Ears, Mouth, and Presence: Designing a Human-Centered Hybrid Classroom for Natural Interaction]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.293</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Hybrid classrooms that feel genuinely human remain difficult to achieve despite sustained post-pandemic investment. Most current solutions still privilege content delivery over social presence, with remote participants positioned as observers rather than participants in a shared learning space.
This paper presents the design philosophy and interim evaluation of the All the DHBWorld is One project, a multi campus initiative across four DHBW sites. It is organized around a simple but operational principle: remote participants require Eyes (visual access to the room), Ears (reliable audio), a Mouth (the ability to speak and be seen), and a Presence (a defined location within the room’s social geometry). A central assumption of the design is that these elements must not be fragmented across devices and interfaces. When visual, auditory, and expressive channels are separated, interaction becomes effortful and unnatural. The new design therefore brings these elements together into a single coherent representation of the remote participant within the room.
Rather than treating presence as an abstract requirement, the system implements them through a dual display setup, a central orchestration unit referred to as the Brain, and a persona based AV model with distinct teaching/learning modes.
Findings from two pilot sessions suggest that technical predictability, especially automated AV switching, is a precondition for teacher adoption. More importantly, the display-as-body concept appears to shift how remote participants are perceived, promoting them from peripheral viewers to socially situated actors. The implications are less about adding technology and more about rethinking how presence is constructed in hybrid environments. The paper concludes by outlining design principles for scalable, low cost hybrid classroom implementations in higher education.]]></description>
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        <item>
            <title><![CDATA[Evaluating digital learning environments in online post-graduate courses: A mixed-method study of learners’ perceptions]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.288</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper investigates learners’ perceived quality of two online inter-university post-graduate courses in heritage education, delivered in distance learning mode in the academic year 2024/25. The study is framed within current debates on digital and distance learning in higher education, with particular attention to the role of online environments, digital tools, and reflective practices. A convergent mixed-method design was adopted, combining quantitative data from an end-of-course questionnaire (Likert-scale items) with qualitative data from self-evaluation notes included in learners’ final assignments. The analysis focuses on key dimensions of the digital learning environment, including online materials, platform organization, course structure, and learning activities, as well as on participants’ reflective interpretations of their learning experience. Quantitative results show a consistently positive evaluation of the courses, particularly in relation to platform organization and module structure. Qualitative findings confirm this overall appreciation, highlighting the perceived relevance of digital tools and the contribution of the courses to professional development. At the same time, participants expressed a need for more practice-based and experimentally oriented learning opportunities. The study suggests that evaluating online post-graduate education requires integrating structured survey data with reflective learner-generated texts. This combined approach allows moving beyond satisfaction measures towards a more nuanced understanding of perceived educational quality in digital learning environments.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[SceneSnap, An AI-enhanced platform for learning in an engineering course: the case study at the Politecnico di Milano]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.279</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[SceneSnap is an AI-enhanced platform designed for university students and faculty. It features functionalities for video lecture summarization, flashcard generation, and personalized tutoring support. This experiential paper presents the first integration of the platform into a blended master’s-level course at the Politecnico di Milano. The researchers adopted a mixed-methods approach to investigate how an AI tool can support the learning process of an experimental group of 24 students. In particular, the study examines the role of this AI platform in improving the quality of learning through video lectures. The research results are encouraging, as they show that the use of the platform had a positive effect on students' perceptions of their study activities and of AI in general.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[AI-Enabled Student Relationship Management: A Conceptual Framework for Digital Transformation in Higher Education]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.278</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper develops a conceptual framework of AI-enabled Student Relationship Management (SRM) as a driver of digital transformation in higher education. Grounded on relationship marketing theory, the framework integrates the Nordic School perspective of value co-creation with the Industrial Marketing and Purchasing (IMP) network approach and extends the traditional Customer Relationship Management (CRM) framework to higher education. The proposed model conceptualises students as both customers and partners and positions artificial intelligence (AI) as an integrative layer connecting the strategic, operational, and analytical dimensions of SRM. The framework suggests that AI enhances predictive decision-making, personalised engagement, and adaptive relationship management, transforming SRM into a data-driven ecosystem. The study contributes an integrated theoretical perspective linking AI, SRM, and digital transformation and provides a foundation for future empirical research.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Designing Context-Responsive Online Learning: the case of a postgraduate transnational teacher development programme in challenging contexts]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.283</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper examines how context-responsive online learning can be designed through participatory, co-creative approaches in transnational education. Drawing on the development of a fully funded Postgraduate Certificate in Online Learning &amp; Teaching for educators in Sub-Saharan Africa, the paper explores how local knowledge, lived experience and contextual constraints can inform pedagogical design of a UK-hosted transnational education programme aimed for learners in Africa. The paper discusses co-creation strategies used to design a transnational online programme, starting with a co-creation workshop involving 27 educators from four countries. Using an adapted curriculum design method, participants collaboratively storyboarded an online module, generating artefacts that reflect their pedagogical priorities. The paper uses the preference for clear, repetitive learning structures, asynchronous discussion as a flexible mode of engagement, limited use of synchronous seminars and concise, modular content that were surfaced during the co-creation workshop to argue that dominant models of online learning require re-examination while demonstrating how co-creation can support more inclusive and contextually relevant pedagogies for online and transnational programmes.]]></description>
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            <title><![CDATA[Reconfiguring to Teach: Pedagogical Responses to the Integration of Artificial Intelligence in Teacher Professional Development]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.276</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper analyses a continuing professional development experience for teachers and educators, centred on the responsible pedagogical integration of Artificial Intelligence (AI) into teaching practice. The programme, developed at Colégio Alfacoop in Portugal during the 2025/2026 academic year, involved 143 participants and was structured around three thematic modules totalling 25 hours in a blended learning format. Grounded in a critical and humanistic perspective, the programme aimed to redefine the teacher’s role as an active mediator and curator of meaningful learning experiences, within a context of increasing automation and the widespread availability of generative AI tools. Preliminary findings suggest that structured professional development, underpinned by sound ethical and pedagogical principles, can contribute to the development of robust AI literacy among teachers, fostering more differentiated, inclusive and learner-centred practices. The paper also discusses the tensions inherent in integrating AI into educational contexts, particularly with regard to assessment, intellectual authorship and digital equity.]]></description>
            <category>ARTICLE</category>
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            <title><![CDATA[Human-AI Collaboration at German-Speaking Universities: Identifying Critical Gaps for Targeted Improvements]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.275</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Generative AI applications are increasingly being used at universities to support both teachers and students and to take on tasks in the areas of teaching support and administration. At the same time, AI applications require far-reaching adjustments to institutional strategies at universities, the development of suitable technical infrastructures, skills development and processes in teaching and learning in order to ensure successful collaboration between humans and AI. Such adjustments are met with very different conditions at universities and are handled and promoted to varying degrees in different areas of universities, at different types of universities and in different countries. A survey conducted by the HIS Institute for Higher Education Development in spring 2025 among all universities in German-speaking countries provides information on the current state of universities‘ engagement with the potential of generative AI systems. The AI-related findings of this survey are examined in more detail in this article with regard to the question of how human-AI collaboration in the field of learning and teaching can be organised for the benefit of universities.]]></description>
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            <title><![CDATA[Embedding AI Competence into the Curriculum: The ADM-AI Model for European Higher Education]]></title>
            <link>https://reference-global.com/article/10.5334/uproc.277</link>
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            <pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Artificial intelligence is reshaping disciplinary practices and academic work, moving higher education beyond technical adoption towards human–AI collaboration as a core graduate capability. This raises a central challenge: how can AI-related human competences be systematically integrated into teaching and learning in ways that foster future-ready skills, while aligning pedagogical transformation with evolving teaching roles and institutional governance?
This paper introduces the Agile Curriculum Development Model (ADM-AI), a governance-compatible framework for systematically integrating AI-related human competences into higher education programmes. Its core contribution is to address the implementation gap between AI competence frameworks and programme-level curriculum transformation under formal higher education governance conditions. The model combines competence clarification, constructive alignment, curriculum mapping, and iterative implementation cycles, enabling continuous curriculum transformation within Bologna-type systems. AIComp serves as a conceptual starting point, providing an empirically grounded competence framework that defines AI competence as a multidimensional capacity for reflective, ethical, and collaborative engagement with AI. The model conceptualises curriculum transformation as a multi-level process linking institutional strategy, programme design, and pedagogical practice.
AI competences are enacted in situated learning environments where learners engage with AI systems as partners in inquiry, problem-solving, and knowledge construction, accompanied by a shift in academic roles towards learning design and facilitation. The model enables embedded, iterative innovation and positions implementation as institutional learning, offering a scalable approach to curriculum transformation in AI-mediated higher education.]]></description>
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