ABSTRACT:
In the context of expanding digital education and persistent global disparities in access, this study explores how learning analytics (LA) can enhance teaching effectiveness and student success in open and distance learning (ODeL) environments. Focusing on Mineral Exploitation IA, a first-year engineering module offered in a South African university’s Diploma in Mining Engineering program, the study exemplifies the use of data-driven methodologies to address systemic educational challenges such as low pass rates, high dropout rates, and poor learner retention.

This case study employs an interdisciplinary and mixed-methods research design, integrating educational data mining (EDM), behavioral analytics, and comparative analysis to assess student engagement, performance, and demographic context. Drawing on data extracted from the institution’s Moodle learning management system, the study examines how students interact with online materials (e.g., video content, discussion forums), complete assessments, and vary in performance across geographic and socioeconomic boundaries.

Findings reveal that students from remote or under-resourced regions—primarily in developing countries—face significant challenges in accessing digital platforms, often due to infrastructural and technological limitations. These constraints negatively impact their participation and performance, highlighting the interdependence of technological, pedagogical, and socio-economic systems in ODeL contexts.

Methodologically, the study aligns with an applied research paradigm, while demonstrating adaptive methodological flexibility. It incorporates a comparative framework that crosses disciplinary boundaries—drawing from education, data science, development studies, and digital communication. In doing so, it situates learning analytics not merely as a technical tool, but as a transdisciplinary research instrument capable of responding to context-specific educational realities.

The study recommends targeted pedagogical interventions, including the integration of low-bandwidth, high-accessibility tools such as WhatsApp-based academic support and e-tutoring. These interventions reflect a culturally and technologically responsive design logic, emphasizing methodological pragmatism rooted in lived student experiences.

By connecting data-informed research, methodological innovation, and context-sensitive teaching practices, this study contributes to the growing field of transdisciplinary education research. It argues for a shift from content-centred instructional design toward learner-responsive, equity-oriented strategies. It demonstrates how the thoughtful use of learning analytics can foster inclusive and effective online learning environments.

ABSTRACT:
This paper offered a systems-theoretical analysis of large language models (LLMs) in the context of higher education. It began by first clarifying the conceptual landscape, then introducing key definitions to frame LLMs, not as revolutionary threats, but as evolutionary developments, grounded in decades of natural language processing and machine learning. Then, it examined how the integration of LLMs prompted institutions to seek new forms of homeostasis, balancing innovation with stability through adaptive regulatory feedback loops.

Next, the analysis explored intersections with broader concepts such as agency, authorship, commodification, and cybernetic governance. It argued that LLMs act as boundary objects whose meanings are negotiated across educational, industrial, and policy domains. It then responded to critiques framing LLMs as epistemically corrosive or ethically destabilizing by emphasizing the role of institutional reflexivity in mitigating risks.

Finally, the study concluded that LLMs do not fundamentally disrupt the mission of higher education; instead, they reveal its structural inertia. Their integration highlights the need for recalibrated pedagogical and assessment frameworks on learning processes. Instead of resisting technological change, institutions should evolve into feedback-responsive ecosystems that uphold human-centered values while embracing permissible forms of automation to enhance, rather than displace, intellectual and creative engagement.

ABSTRACT:
In this article, we explore the implicit yet foundational cybernetic relationships among three of the most transdisciplinary conceptual constructs: Education, Research, and Methodology. It argues that these three domains are not merely interconnected but form a Cybernetic Triad whose interactions generate emergent properties, such as deeper understanding, creativity, and systemic synergy, when made explicit. By using a top-down approach, the article models these relationships through feedback loops and mutual influence, highlighting how each domain serves as both input and output to the others. The discussion incorporates examples from various disciplines, distinguishing between systematic (closed) and systemic (open) methodologies, and proposing a knowledge framework that includes not just "know-what" and "know-how" but also "know-why", "know-when", and "know-where". It concludes that engaging with this triadic system reflexively enhances individual and collective effectiveness, particularly in transdisciplinary contexts. In this context, a gap is identified in regard to making transdisciplinary communication a practical skill within academia. Consequently, a structured model is proposed to embed it systematically into education, research, and methodology, recommending curricular, project, and institutional integration for greater impact.

ABSTRACT:
This paper presents the ETCOP Model, a transdisciplinary framework designed to enhance educational effectiveness through stakeholder co-design, critical reflexivity, and impact-oriented curriculum development. Developed by the ETCOP Institute, the model integrates educational science, digital innovation, and ethics, and has been applied across diverse domains including digital transformation training for SMEs, AI literacy in teacher education, and entrepreneurship education in secondary schools. Anchored in design-based research and structured around five core principles, the model promotes the use of open educational resources, modular learning architectures, and continuous, mixed-methods evaluation.

Empirical findings from internal and external assessments indicate increased learner engagement, competence acquisition, and evidence of institutional transformation. By operationalizing transdisciplinarity at the levels of pedagogy, governance, and evaluation, the ETCOP Model contributes a scalable, ethically grounded approach to educational design. The paper advances the field of transdisciplinary educational research by offering a practice-based model that supports systemic innovation and alignment with evolving societal and policy demands.

ABSTRACT:
As workforces grow increasingly age-diverse, designing learning environments that foster meaningful engagement across generations has become a practical necessity and a conceptual challenge. This paper argues for a shift from traditional, hierarchical models of instruction toward reflexive, interaction-driven approaches to learning design. The study repositions intergenerational learning as a relational and communicative process, where learners are not passive recipients of knowledge but active participants in co-constructing meaning. Reflexivity, understood as a continuous, critical awareness of one's position, assumptions, and influence within the learning system. It is presented as a core methodological and pedagogical tool for designing inclusive, adaptive, and reciprocal learning experiences. Rather than viewing generational differences as barriers, this perspective embraces them as sources of diversity that enrich collaborative inquiry and innovation. The paper explores key design principles such as dialogic learning, emotional safety, shared agency, and mutual respect, emphasizing the importance of feedback loops and non-linear knowledge exchange. By moving beyond age-based stereotypes and fixed instructional models, reflexive learning design opens possibilities for sustaining lifelong learning and fostering more human-centered organizational cultures. Ultimately, this work advocates for intergenerational learning environments that are educational and transformative.

ABSTRACT:
The Aquae Strength initiative is an international cooperation project between countries, whose activities include the realization of an e-learning course on Geographic Information Systems (GIS) and veterinary epidemiological surveillance in aquaculture. The course is an example of a synergetic relationship between training, research and methodological innovation that makes the knowledge, acquired by experts during the project, available to international learners through user-friendly technology. The advanced training proposal is not based on pure theory, but integrates practical applications that learners are likely to encounter in their daily work. The initiative contributes to a future-ready veterinary workforce equipped with the tools to navigate both digital and ecological complexity.

ABSTRACT:
This narrative analysis explores how the European Union’s Artificial Intelligence Act (EU AI Act) holds the potential to shape institutional discourse of U.S. higher education. As artificial intelligence becomes deeply embedded in university operations, from admissions and instruction to monitoring and assessment, it raises urgent questions about institutional purpose, power, and accountability. Drawing on Kantian ethics, the analysis highlights the tension between external regulatory structures and internal moral reasoning. The EU AI Act (Regulation 2024/1689), with its risk-based classification of AI systems and its extraterritorial provisions, introduces binding obligations for transparency, oversight, and ethical alignment in educational applications. These obligations challenge existing norms of voluntary governance in U.S. academia and signal a shift toward anticipatory and structured forms of technological oversight. Within this landscape, reflexivity is positioned not as a rhetorical gesture but as a necessary institutional capacity. It refers to the ongoing process of self-examination that engages with embedded assumptions, power dynamics, and the normative dimensions of algorithmic systems. This analysis argues that reflexivity must guide institutional responses to AI governance if universities are to align technological adoption with their academic values and global responsibilities.

ABSTRACT:
This paper reported on the development of an online data-gathering system for the programmatic assessment of General Education Programs (GEP) at a US public polytechnic university. The article began with a brief introduction to the study area and population. It then presents the findings of a literature review that underpinned the study, including research on faculty buy-in for programmatic evaluation. The primary findings highlighted a significant disconnect between those managing the data-reporting process for accreditation agencies and those charged with teaching and assessing students who are required to provide the data. Next, the study methods and procedures utilized for developing the online data-gathering system were described. A group of educators was engaged in a collaborative co-design process to develop the necessary data-gathering instrument and to test various tools during feedback sessions. For this pilot test, the GEP outcome being examined was 'Oral Communication,' which utilized a four-point Likert-style scale for indicators. The results of the pilot test are presented, along with user observations and comments. The article concludes with a series of findings and implications for how these methods can be applied to other GEPs and, more broadly, to any program evaluation needs.

ABSTRACT:
Education, research, and methodologies form an organic unit that is the essence of human identity. Education is the object (which also is a process); research is the domain of process in which knowledge is to be found; methodology is the manner in which a person is to bring information into the mind that is to be transformed into knowledge. Education etymologically stems from conducting or leading, that is knowing oneself. It is transdisciplinary, recursive, and second-order cybernetic, all aspects of organicity, or life, itself. It is not enough to realize these things; we need to apprehend the context in which these are set, i.e., our universe, itself, conscious and organic, as we are. Did not God make us in his image, as the Biblical saying goes? Along the way, we need to be cognizant of innate processes in the universe, such as the most fundamental law known since ancient times and expressed by GWF Hegel, the unity of opposites, as well as organicity, itself (as opposed to static entities). These factors implicitly describe transdisciplinary access to knowledge. Anatomically, the Universe is both deductive and inductive, the former as descending from the outer limits of our knowledge to the center (ourselves), the latter inductively, reaching outward to find what is there to be known. These “ends”, from the infinitesimal to the infinite, describe the domain of research. Our method of investigation is contradiction, employing the unity of opposites, the most extreme form of critical thinking. Permeating the Universe is Plato’s realm of the ideal, consciousness, the transcendental, represented by the words of Buddha, Christ, Mahoma, Aristotle, and Plato, among others. Truth characterizes the Creator, and so is the object of search in education, and so it is, we must realize authenticity, both in ourselves and the world around us. Training as deduction, validates it through virtue (internalizing behavior exhibiting our values, or meaning). Truth, itself is a function of order. A disordered identity compromises a person’s being, and conversely. Two methods of identity location are neurocorrelation and deep personal questioning (as with an authentic method of self-discovery). I will merely reference the former and describe in more detail the latter, a representative being Authentic Systems, showing specifically why it is educative.

ABSTRACT:
This article explores how service-learning in higher education fosters metacognitive awareness and reflexivity among students by positioning education, methodology, and research as a mutually reinforcing triad. It defines metacognitive awareness as students’ ability to regulate their own thinking, and reflexivity as critical self-examination shaped by social contexts, both seen as essential twenty-first century skills. Service-learning is presented as a high-impact educational practice that challenges students to apply academic knowledge in real-world settings, confront ill-structured problems, and reflect deeply on their experiences of community engagement. This discussion emphasizes the central role of reflection in cultivating metacognitive awareness and reflexivity by using various strategies. This article also highlights how artificial intelligence can support reflection by offering personalized feedback while underscoring irreplaceable aspects of learning. Finally, it examines how service-learning must be culturally contextualized through transdisciplinary communication, especially in Asian settings, to resonate with local values and facilitate collective sense-making. Together, these aspects illustrate how thoughtfully designed service-learning can nurture self-aware, reflective learners.