University Managers' Insights into Collaborative Networks and the Adoption of Digital Technologies for Human-Centric Teaching and Learning Models

University Managers' Insights into Collaborative Networks and the Adoption of Digital Technologies for Human-Centric Teaching and Learning Models | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article University Managers' Insights into Collaborative Networks and the Adoption of Digital Technologies for Human-Centric Teaching and Learning Models Liile L. Lekena -Mangosuthu, Anass Bayaga This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7100705/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates the strategic narratives of university managers in South Africa, aimed at the acceptance of digital technologies to advance human-centric teaching and learning models. It examines fundamental gaps in grasping how collaborative networks, digital skill, and interdisciplinary systems influence institutional strategies. The questions aimed at examining the mechanisms of strategic planning, encouraging effect of interdisciplinary teamwork in initiating. The research integrates qualitative thematic and quantitative network analysis with results demonstrating three critical insights: localized relationship strengthens intra-group reliability but limits broader incorporation across departments; digital readiness advances equitable adoption, permitting interdisciplinary pathways, knowledge diffusion, driving developments in human-centric education strategies. These results articulate through pathways such as localized collaboration → strong intra-group cohesion → limited cross-departmental incorporation; as well as digital readiness → equitable adoption → sustainable innovation; and interdisciplinary pathways → knowledge diffusion → enhanced human-centric education strategies. strategic planning digital transformation higher education human-centric models Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Strategic planning in higher education is experiencing restructuring, bound by global advances, local priorities, and technological improvements. Whereas internation education strives to incorporate inclusive strategic agendas, the South African higher education reveals how historical, socio-political, and economic issues require tailored methods (Moloi & Salawu, 2022 ). The nuanced improvement in South Africa features the requirement to align global best processes with access, and local societal effect. Current scholarships shed light on these dynamics. Moloi and Salawu ( 2022 ) highlight the transformative potential of digital technologies in advancing teaching, learning, and institutional formation, while Dacholfany et al. ( 2024 ) highlight the effect of adaptive educational management (digital change). Such insights resonate with the challenges faced by South African universities where strategic planning must concurrently address historical biases and adopt progress. Similarly, Damba et al. ( 2023 ) draw attention to the underutilization of research in South African universities, a theme echoed by Ngo Ndjama and Van Der Westhuizen ( 2023 ) in their reflection of participative decision-making. The global urge for integrating technology in education, as examined by Janahi et al. ( 2023 ), aligns with South Africa’s ambitions to develop institutional success through digital revolution (Moloi & Salawu, 2022 ). Nevertheless, the variant of these worldwide innovations requires a localized lens, as pointed out by Heleta and Jithoo ( 2023 ), who examine South Africa’s collective research configurations. This localized approach is needed for addressing critical concerns such as inclusivity and the societal significance of academic efforts (Basu et al., 2024 ; Panakaje et al., 2024 ). The current study examines the detailed practices through which strategic planning affects performance outcomes within the South African university outlook. It hinges on historical developments including the reactionary nature of early post-apartheid development (Idahosa & Vincent, 2018), the position of international effects, and current changes concerning adaptive methods (Soudien, 2019; Trianung et al., 2024 ). Through an assessment of these outlooks, the research identifies by university managers about the procedures linking strategic planning to performance conclusions. It also examines how digital technologies, combined networks, and interdisciplinary approaches contribute to the realization of human-centric teaching and learning models in South Africa. 2. Literature review Strategic planning in higher education serves as a foundation for institutional success, specifically in addressing advancing challenges in digital transformation, equity, and global affordability. While the international higher education landscape establishes developments in strategic frameworks and performance orientation, the unique socio-political and historical backgrounds of South African universities tell noteworthy gaps in application and consequences (Table 1). The strategic narratives of university managers in South Africa indicate development connections and detachments within the higher education sector, as outlined in Table 1. Strategic planning in the country is modeled by rare socio-political and historical considerations, yet international models, which prioritize metrics like research productivity and rankings, frequently fail to align with local significances. This establishes a gap where localized variations are necessary for aligning international beneficial pathways with the socio-economic realities of South African universities. The paths, Localized Adaptations → Inclusive Metrics → Improved Strategic Outcomes , establishes that addressing this misalignment can lead to strategic consequences that are both internationally feasible and locally applicable (Dacholfany et al., 2024; Yu & Ismail, 2024). In the realm of digital change, South African universities face significant barriers to readiness, relating resource constraints and inadequate adoption of technologies. While digital tools hold transformative possibility, their outcome remains unstable, highlighting need for robust methods to address these challenges. The outline, Digital Readiness → Equitable Adoption → Sustainable Transformation , underscores the position of guaranteeing that digital initiatives are not only all-inclusive but also practical, thereby advancing institutional performance (Moloi & Salawu, 2022; Jaca et al., 2023; Panakaje et al., 2024). Equity and inclusivity are necessary for the segment, yet gaps remain in applying equity-driven system. The lack of relationship between these factors and institutional goals hinders development toward reaching societal effect. The path, Equity Strategies → Participative Planning → Enhanced Institutional Goals , highlight the condition of embedding equity into institutional frameworks to produce strategies that are both inclusive and impactful (Idahosa & Vincent, 2018; Soudien, 2019; Ngo Ndjama & Van Der Westhuizen, 2023). Interdisciplinary connection emerges as a vital influence for innovation and performance enhancement, however weak network between technical and behavioral sciences limit knowledge diffusion. This disconnection limits the wider application of insights needed for strategic success. The pathway, Cross-Disciplinary Links → Knowledge Diffusion → Performance Improvement , emphasises the need for stronger collaboration across disciplines to strengthen institutional performance and advancement. By encouraging cross-disciplinary linkages, universities can realize more holistic and effectful strategic consequences (Heleta & Jithoo, 2023; Ouma-Mugabe et al., 2024; Jaca et al., 2023). These pathways jointly demonstrate the relationship between strategic planning, digital transformation, equity, and interdisciplinary partnership. While localized variations and digital readiness support a base for advancing institutional strategies, the gaps in equity-driven frameworks and interdisciplinary engagement reveal critical disconnections. Addressing these gaps through targeted initiatives will allow universities to align global aspirations with local requirements, developing novelty, inclusivity, and balanced transformation in higher education. This complete methodology guarantees that strategic narratives are both contextually appropriate and universally viable, paving the way for more operational and equitable institutional results. Table 1: Strategic narratives of university managers Dimension Findings Gaps Pathways Implications Sources Strategic Planning Context Strategic planning in is fashioned by rare socio-political and historical dynamics. Global models regularly prioritize system of measurement (research productivity and rankings), which may not align with local priorities. Limited research on localized modifications of global strategic planning models to South Africa's unique socio-political perspective. Localized Adaptations → Inclusive Metrics → Improved Strategic Outcomes Localized variations are essential to align international best routines with the specialized needs and priorities of South African universities. Dacholfany et al. (2024), Yu and Ismail (2024) Digital Transformation in Higher Education Digital tools have transformative possibility; however their incorporation remains irregular across South African universities, raising questions regarding institutional readiness and sustainability. Barriers to digital readiness, involving resource constraints and irregular acceptance of technologies. Digital Readiness → Equitable Adoption → Sustainable Transformation Institutions must address barriers to digital readiness to guarantee that digital transformation efforts are balanced and impartial. Moloi and Salawu (2022), Jaca et al. (2023), Panakaje et al. (2024) Equity and Inclusivity Equity and inclusivity are essentials in South African higher education, compelling approaches that address historical biases while advancing global effectiveness. Lack of equity-driven system of measurement and inadequate alignment of participative planning with institutional aims. Equity Strategies → Participative Planning → Enhanced Institutional Goals Strategic frameworks must combine equity-driven system of measurement and participative planning to realize institutional and societal targets. Idahosa and Vincent (2018), Soudien (2019), Ngo Ndjama and Van Der Westhuizen (2023) Interdisciplinary Collaboration Interdisciplinary partnership is necessary for innovation and performance advancement, nonetheless, gaps in knowledge diffusion and incorporation between technical and behavioral sciences endure. Weak connections between disciplines limit improvement and strategic diffusion of knowledge. Cross-Disciplinary Links → Knowledge Diffusion → Performance Improvement Improved partnership across disciplines can adjust innovation and strategic effect, encouraging more holistic methods to institutional performance. Heleta and Jithoo (2023), Ouma-Mugabe et al. (2024), Jaca et al. (2023) Anchored upon Table 2, several perspectives could be explained: For instance, strategic planning has become an important management instrument for higher education institutions internationally. Nonetheless, the adoption of these technologies is unpredictable, with Jaca et al. (2023) identifying substantial gaps in knowledge transformation and institutional readiness. This irregular adoption raises questions concerning the long-term sustainability of digital initiatives and their pathway with institutional performance system of measurement. South Africa’s universities face rare challenges rooted in their apartheid history, compelling strategic planning methods that address biases while engaging in international effectiveness. The historical reliance on conservative planning, as noted by Idahosa and Vincent (2018), has often hampered transformation. Recent scholars (Damba et al., 2023) put emphasis on the underutilization of doctoral research findings, showing gaps in connecting strategic goals to actionable decisions. Moreover, Ngo Ndjama and Van Der Westhuizen (2023) highlight participative decision-making as a fundamental nevertheless underexplored in achieving alignment between strategic aspirations and performance. These studies reveal a sizable gap in understanding how inclusive advancements can drive performance and equity. Interdisciplinary connection and knowledge diffusion are progressively noticeable as dynamic mechanisms of strategic planning in higher education. Correspondingly, Machado et al. (2022) and Quarchioni et al. (2022) contend that the effect of knowledge diffusion in strengthening strategic targets, highlighting the value of aligning research consequences with institutional ideas. Albeit these developments, gaps remain in unexplored. For instance, Jaca et al. (2023) identify drawbacks in knowledge translation in South Africa, implying a disconnect between research outputs and practical relevance. Addressing this disconnect is necessary for improving the strategic effect of universities in South Africa and elsewhere. Performance management taxonomy in South African universities frequently struggle to evaluate international objectives with local requirements. System of measurement (research productivity and global rankings), while significant, do not entirely capture the societal effects and inclusivity goals essential for the region (Carnegie, 2023; Gadd, 2023). Asiedu et al. (2022) and Sahibzada et al. (2022) lay emphasis on the consequence of knowledge management in aligning institutional approaches with performance outcomes. Nevertheless, the applicability of these structures in South Africa remains underexamined, specifically in settings with resource constraints and socio-economic discrepancies. While the prior research offers insights into the relationship between strategic planning, performance, and digital transformation, several significant gaps warrant further inquiry (Sahibzada et al., 2022). One key gap rest upon the contextual variations of international strategic planning developments to the socio-political and economic experiences of South African universities. Prevailing scholarship regularly focuses on international best methods but does not effectively investigate how these frames are localized to address the rare challenges and prospects within South Africa's higher education segment. Another area requiring evaluation is the uneven adoption of digital technologies across organizations, which highlights the need to examine the enablers and barriers to incorporation within strategic settings. Regardless of prominence of digital transformation, several South African universities face infrastructural and resource constraints that impede effective performance. Grasping these core forces is needed for proceeding with digital readiness in higher education. Performance management practices also tend to disregard locally applicable system of measurement (community engagement and equity-driven outcomes). This non-inclusion raises questions how these structures can better exhibit the societal inclusivity objectives necessary to South Africa’s higher education principle. Researching wide-ranging system of measurement that align with institutional goals and wider societal responsibilities remains an instrumental area for future scholarship. Additionally, there is a disconnect between research outputs and their practical consequence in South African universities, revealing gaps in knowledge transformation. While networks and interdisciplinary approaches hold value to advance strategic goals, more studies are required to filter their individual effects on higher education institutions’ efficiency. The relationship between strategic planning, performance, and digital transformation is multifaceted, chiefly in perspectives like South Africa, where historical injustices and resource constraints overlap with international targets. Addressing the detected gaps in appropriate adjustment, digital readiness, inclusive system of measurement, knowledge transformation, and interdisciplinary collaboration offer actionable insights for improving the strategic effect of universities, hence the following objectives. 3. Research Objectives Mapping collaborative networks and strategic narratives in digital education By what method do university managers leverage joint networks to influence the acceptance of digital technologies in teaching and learning? Who are the main institutional and individual contributors shaping human-centric digital education models? Exploring trends in strategic narratives for human-centric digital transformation What strategic ideas or themes lead university managers' narratives on digital transformation for teaching and learning? In what way have these narratives evolved to address equity, inclusivity, and international competitiveness? Analyzing interdisciplinary pathways in human-centric teaching and learning models How do interdisciplinary relationships foster the adoption of digital technologies in teaching and learning? What strategic methods improve knowledge diffusion across domains or disciplines to support human-centric education? 4. Methodology This research utilizes a mixed methods design that incorporates qualitative and quantitative approaches, with network structural analysis as the principal analytical framework. The aim is to investigate the collaborative networks and strategic narratives of university managers in the acceptance of digital technologies for human-centric teaching and learning models. This method links rich, qualitative data with quantitative system of measurement to grant a comprehensive interpretation of the research objectives, aligning with proven best systems in social network analysis (Bell et al., 2019; Braun & Clarke, 2019). The study hinges on university managers in South Africa, particularly targeting Heads of Departments, Deans, Directors, Senior Directors, and Deputy Vice-Chancellors. These respondents are strategically placed to exercise institutional judgments and performance consequences. Purposive sampling ensures the presence of respondents with appropriate knowledge, whereas network data are traced from institutional reports, academic publications, and collaborative project records. The sample size (n = 20) allows data saturation and diverse understanding, based on principles from Creswell and Creswell (2018). Data collection was conducted through semi-structured interviews as well as network data mining. The interviews were designed to explore narratives about strategic planning, concentrating on the acceptance of digital technologies and collaborative practices. Open-ended questions enabled detailed insight of managerial practices and decision-making, as encouraged by Merriam and Tisdell (2016). Shared with this, network data on co-authorship as well as institutional partnerships were gathered from publicly accessible repositories, citation indices, and institutional documents. The assessment applies to a convergent parallel design by combining qualitative thematic analysis with quantitative network metrics. Thematic analysis, supported by Braun and Clarke’s (2019) methodology, is utilized to identify relationships and themes in the interview data. By relating thematic assessment with network analysis, the examination not only offers actionable insights but also contributes to a deeper conception of the dynamics concerning performance outcomes in higher education. Both inductive and deductive coding methods ensure thorough searching of the descriptions, with codes linked to the research objectives. Concurrently, network analysis is conducted leveraging on tools such as Gephi and NetworkX, which facilitate the visualization and computation of system of measurement like degree centrality, betweenness centrality, clustering coefficients, and modularity. These systems of measurement are vital for identifying leading individuals, sub-communities, and relationships within the networks (Denzin & Lincoln, 2018). The combination of qualitative and quantitative data delivers a robust framework for triangulation. The narratives resulting from thematic assessment are cross-referenced with network metrics to confirm decisions and highlight the pathways between strategic narratives and collaborative procedures. Member-checking ensures the accuracy of explanations, while inter-coder reliability improves the thematic coding development (Creswell & Creswell, 2018). Clinical trial number is not applicable in current study. While, a clinical trial number was not applicable in the current study, official ethical clearance from the research ethics committee at University of Pretoria was fundamental to the research process, wherein ethical approval (IRPSD-1727) was secured before data collection, and informed consent acquired from all respondents. Participants were guaranteed not just confidentiality but with data securely saved and anonymized for reporting objectives. 5. Results 5.1 Mapping Collaborative Networks and Strategic Narratives in Digital Education 5.1.1 Collaborative networks among university managers The results started with drawing insights from collaborative networks among university managers as reflected in Figure 1, which displays the relationships among university managers. Nodes were used to characterize individuals in managerial roles, while edges revealed direct collaborations, such as shared projects or communication networks. The dominant outlook of interviewee 3 implies a high degree of centrality, suggesting they are a key hub aiding communication and relationship. The connections between Interviewees 3, 6, and 8 show a strong triadic closure, implying an influential sub-community driving strategic initiatives. The sparsity of connections between other interviewees highlights fragmentation, suggesting a need for enhanced cross-departmental collaboration. The network demonstrates the pivotal role of specific managers in bridging clusters, but it also reveals gaps in connectivity that may hinder cohesive strategic planning. Encouraging more inclusive participation in collaborative efforts could reduce reliance on key nodes and ensure a more integrated approach to decision-making. The second network (Fig 2) visualizes the relationships between dominant themes in strategic narratives. Nodes represent recurring themes from interviews, and edges show conceptual connections based on co-occurrence analysis. Central themes like equity, inclusivity, and digital readiness have multiple connections, indicating their foundational role in strategic planning discussions. Emerging themes such as AI in teaching and adaptive learning are less integrated, reflecting their nascent status in the narrative framework. The network highlights the prominence of equity and inclusivity in strategic narratives, aligning with broader institutional goals. Nonetheless, the peripheral positioning of advanced technological themes implies an opportunity to incorporate them more systematically into strategic frameworks, possibly improving innovation in human-centric teaching and learning models. 5.1.2 Interdisciplinary pathways in digital technology adoption The third network (Fig 3) represents interdisciplinary paths in digital technology acceptance, where directed edges signify knowledge flow and collaboration between faculties and administrative units. Engineering and management sciences act as primary drivers of innovation, feeding into natural sciences and administrative units. Nonetheless, the sparse relationships to natural sciences imply underutilized possibility for interdisciplinary integration. The reciprocal connection between administrative units and management sciences shows ongoing feedback and knowledge sharing. The network emphasises the importance of bridging detached fields to foster thorough acceptance of digital technologies. Strengthening connections with understated faculties like Natural Sciences could solve new ideas and improve the alignment of interdisciplinary attempts with planned objectives. These visualizations afford actionable understandings into the dynamics of networks, strategic narratives, and interdisciplinary relationship, depicting a roadmap for improving strategic planning and execution in higher education. The clustering coefficient is an influential system of measurement, revealing the extent to which nodes in a network form tightly related cluster. It establishes the likelihood that two nodes linked to a common node are also related to each other. A high clustering coefficient indicates localized association and coherence within sub-groups, whereas a low coefficient signifies a more distributed network where relationships are largely spread. Case in point, in a university perspective, a high clustering coefficient in a department shows close cooperation among members, which can foster trust, streamline communication, and increase the productivity of localized projects. Nevertheless, exceptionally high clustering can also lead to silos, where sub-groups prioritize their internal goals over wider institutional objectives, potentially stalling the diffusion of innovative attempts across the organisation. In the analysis of university managers' networks, clustering coefficients varied across different sub-groups. Example, administrative units showed a clustering coefficient of 0.68, demonstrating strong internal structure as they collaboratively resulted in operational strategies. Academic departments, on the other hand, presented a modest clustering coefficient of 0.58, suggesting moderate levels of collaboration but some degree of division. This demonstrates that though academic departments were somewhat connected, their collaboration did not extend broadly across different faculties, restricting the exchange of ideas and strategic organisation. The outlook of clustering coefficients on organisational plans is multifaceted. High clustering coefficients can enhance localized collaboration, supporting known factor sub-groups to concentrate and exceed in targeted initiatives, including piloting digital technologies for teaching. Case in point, a department with a high clustering coefficient may probably centre effectively on employing adaptive learning tools. Nonetheless, the lack of integration with other groups may impede the scaling of such innovations to the institution-wide intensity. Accordingly, harmonising clustering coefficients by encouraging cross-group collaborations through broker nodes - units involving different clusters facilitate both localized innovation and broader institutional consistency. Interdisciplinary configurations show an important function in improving inclusivity within strategic planning. By linking isolated faculties and units, these paths aid the exchange of diverse scenarios, ensuring that strategic plans are informed by a broad range of expertise as well as priorities. In the network analysis, directed pathways showed the flow of knowledge between faculties. For instance, the Management Sciences faculty (betweenness centrality score = 0.42), emerged as a bridge connecting technical faculties like Engineering with administrative units. This bridging role helped the combination of managerial understanding with technical innovations, contributing to additional broad and inclusive plans. However, some faculties, such as Natural Sciences, shown lower centrality scores, revealing limited engagement in interdisciplinary connections. This lack of incorporation focuses a missed potential for these faculties to contribute to and advance from broader strategic plans. Improving inclusivity involves fostering reciprocal pattern where every faculty can evenly participate in decision-making developments. For instance, Natural Sciences in projects led by Management Sciences not only guarantees that STEM disciplines contribute to equity-driven intentions but also helps the combination of varied viewpoints into human-centric teaching model. Clustering coefficients and interdisciplinary pathway together offer a nuanced awareness of strategic planning dynamics in higher education. That is while high clustering coefficients highlight the strength of localized relationship, they also accentuate the probability for silos that impede wider connectivity. Interdisciplinary pathways, in contrast address this limitation by creating bridges that foster inclusivity across the organisation. By improving clustering coefficients and upgrading interdisciplinary configurations, institutions can design methods that balance local expertise with institution-wide inclusivity, improving unified and operational educational context, consequently guaranteeing that methods are not only novel but also equitable, positioning with both global standards and local priorities. The visualization (Fig 4) describes the clustering and interdisciplinary configuration within the institution's collective network. The closely linked nodes within administrative units and faculties (e.g., administrative unit A, B, and C; Faculty A, B, and C) reveal high clustering coefficients. This clustering mirrors strong collaboration within these groups, which assists efficient localized initiatives such as policy development or faculty-specific projects. Nevertheless, these clusters are relatively detached from one another, indicating the manifestation of silos that may limit the diffusion of innovative practices and the overall strategic coherence across the institution. The directed edges involving faculties and administrative units characterise interdisciplinary pathways that enable knowledge interchange and collaboration across different fields. Faculties and administrative units act as bridges within the network. For instance, Faculty A and Administrative Unit A have reciprocal ties, demonstrating bidirectional knowledge flow. Nonetheless, the pathways are not consistently dispersed, with some links, such as those concerning Faculty C and Administrative Unit C, appearing weaker. This irregular distribution of paths may hinder inclusive involvement and limit the incorporation of understandings from these nodes into broader strategic initiatives. whereas the clustering within groups advances depth in specific areas, interdisciplinary pathways grant the breadth required to link different parts of the network. These paths are important for breaking down silos, confirming inclusivity, and incorporating technical improvements with institutional policies. The network underlines the two-fold position of preserving strong internal collaboration, as established by clustering, and helping interdisciplinary engagement, as demonstrated by the pathways, to realize interconnected and wide-ranging policies for digital technology acceptance. In the setting of the research questions and topic, the centrality metrics represented in the collaborative network in clustering and interdisciplinary configuration in digital technology adoption demonstrate their strategic implication. Nodes with high degree centrality, such as Faculty A and Administrative Unit A, act as hubs, involving multiple other nodes and driving partnership across diverse institutional areas. These hubs are fundamental in propagating approaches for digital technology acceptance and confirming that essential initiatives reach a broad audience within the organization. Nodes with high betweenness centrality, such as Administrative Unit B, serve as bridges between clusters, enabling the interchange of strategic narratives between academic faculties and administrative units. Example, the path from Administrative Unit A through Administrative Unit B to Faculty C demonstrates how these bridging nodes moderate communication gaps and facilitate the transfer of advanced follows. High closeness centrality, observed in Faculty B, highlights nodes that are strategically positioned to access other parts of the network efficiently, ensuring rapid dissemination of digital transformation strategies. Figure 4 also demonstrates how interdisciplinary pathways can mitigate organizational silos. Directed edges between faculties and administrative units, such as those connecting Faculty A to Administrative Unit A and further to Faculty B, highlight bidirectional knowledge flow. These pathways promote collaboration across traditionally isolated areas, enabling the integration of diverse perspectives into human-centric digital education strategies. For example, the link between Faculty C and Administrative Unit C, though weaker, represents an opportunity to enhance inclusivity by strengthening interdisciplinary engagement. The visualization underscores that fostering robust connections across disciplines is essential for breaking silos and ensuring cohesive strategic planning. 6. Discussion Mapping collaborative networks and research influence in digital education are multifaceted. The findings highlight the fragmented nature of collaborative networks among university managers, where certain individuals or units act as central hubs connecting disparate groups (Table 2 ). The discussion on adoption of digital technology in higher education, as mapped in Table 2 , underscores both progress and persistent challenges. Collaborative networks emerge as hierarchical structures, with central hubs such as Institution X and Institution Z driving research initiatives, while peripheral nodes like Institution Y remain underconnected. This disparity focuses on the disconnection between central and marginal actors, restricting equitable knowledge distribution. The configuration Central hubs → Peripheral nodes → Diverse Participation demonstrates how mentorship and structured association could take part in marginalized institutions into international research frameworks, promoting inclusivity and diversity in intellectual contributions. Patterns within these networks uncover the dominance of important institutions in influencing the scholarship, but innovative understandings suggest that partnerships and cross-institutional arrangements can lessen injustices by bridging these gaps (Heleta & Jithoo, 2023 ). Thematic developments mirror a shift towards AI-powered, human-centric methodologies in education, where inclusivity and ethical consequences have become global importance. Clusters of innovation, incorporating predictive analytics and adaptive learning tools, reveal an increasing alignment between technological developments and learner-centric bases. Nevertheless, the configuration AI tools → Human-centric Frameworks → Enhanced Inclusivity is comparatively disadvantaged by gaps in hybrid models that integrate established teaching with emerging technologies. The weakening consequence of unrelated pedagogies implies an opportunity to unite adaptive technologies with conventions, addressing equity worries while leveraging the strengths of both modalities. This tendency not only aligns with ethical AI importance but also points to an unknown connection where traditional and digital innovations coincide to serve diverse learner obligations (Panakaje et al., 2024 ; Yu & Ismail, 2024 ). Knowledge diffusion likewise shows the centrality of education technology as a bridge involving technical fields like computer science with applied disciplines such as psychology and policy studies. Though technical fields display robust intra-domain diffusion, the weaker pattern such as Technical Fields → Behavioral Sciences → Interdisciplinary Innovation suggests a central disconnection. This gap limits the incorporation of cognitive and emotional insights needed for improving AI tools that advance learner engagement, purpose, and well-being. Strengthening the pathways Behavioral Sciences ↔ Technical Fields → Holistic AI Systems is significant for recognizing more extensive and capable educational technologies. Existing patterns of diffusion indicate that technical advancement overlook, but new interpretations highlight the obligation of interdisciplinary collaboration to realise balanced and inclusive acceptance approaches (Ouma-Mugabe et al., 2024 ). These relationships, both connections and disconnections, outline a complex narrative of advancement and challenges in the adoption of digital technologies in higher education. While collaborative networks and thematic preferences highlight improvements in inclusivity and technology, the persistent gaps in interdisciplinary engagement and hybrid pedagogy signal areas for targeted involvement. Addressing such gaps will guarantee digital transformation policies aligning with both global priorities and local realities, fostering improvement, equity, and sustainable effect. Table 2 Strategic implications for digital technology adoption Dimension Findings Implications Pathways Contribution New Insights Sources Collaborative Networks The network is hierarchical, with Institution X and Institution Z acting as central hubs, and Author A and Author B serving as influential researchers. Peripheral nodes, such as Institution Y, show limited connections, leading to disparities in network integration. Sparse links between central and peripheral nodes hinder equitable dissemination of knowledge. Strengthening partnerships is essential to integrate underrepresented institutions and researchers into global networks. Encouraging central hubs to mentor peripheral nodes will help promote diverse participation. - Central hubs → Peripheral nodes (Mentorship programs to bridge gaps). - Cross-institutional partnerships → Enhanced global integration (Building international research connections). Confirmed (in part): Central institutions drive collaborative research, but persistent disparities in access and integration are significant barriers. Mentorship and structured collaboration models could transform peripheral nodes into active contributors, enhancing the diversity of global research. Muller et al. (2016); Webber and Calderon (2015); Damba et al. ( 2023 ); Heleta and Jithoo ( 2023 ). Thematic Trends Three dominant clusters emerged: AI and data-driven technologies (predictive analytics and machine learning), human-centric approaches (inclusivity, ethics, and equity), and implementation strategies (adaptive learning tools). Traditional teaching methods show declining prominence, reflecting the shift toward technology-enhanced practices. Human-centric approaches are increasingly emphasized, aligning with global priorities for ethical and inclusive education. - AI tools → Human-centric frameworks (Ethical AI systems align with learner needs). - Technology → Traditional teaching models (Combining adaptive technologies with conventional approaches). Extended: Ethical AI and inclusivity are confirmed as growing priorities, but the gap in hybrid models combining traditional and digital methods remains underexplored. The declining focus on standalone teaching methods highlights an opportunity to integrate traditional pedagogies with AI-driven learning models, ensuring equity for all learners. Biesta (2010); Morton (2015); Panakaje et al. ( 2024 ); Yu and Ismail ( 2024 ). Knowledge Diffusion Education Technology serves as a central hub, bridging technical disciplines like computer science with applied fields such as psychology and policy studies. Knowledge diffusion within technical domains is robust, but weaker links exist between technical fields and behavioral sciences, limiting interdisciplinary innovation. Diffusion across interdisciplinary pathways is slower, restricting the holistic integration of AI tools. Promoting interdisciplinary collaborations is essential to enhance knowledge transfer across disciplines. Strengthening links between technical and behavioral sciences could ensure that cognitive and emotional insights are incorporated into AI-driven tools for human-centric education. - Technical fields → Education Technology → Policy Studies (Knowledge transfer facilitates policy alignment). - Behavioral sciences ↔ Technical fields (Integrating cognitive and emotional insights into AI systems). Confirmed (in part): Knowledge diffusion is robust in technical fields, but cross-disciplinary integration remains a challenge, as behavioral insights are underutilized. Behavioral insights are critical for developing AI tools that address learner engagement, motivation, and well-being, but weak interdisciplinary links hinder their integration. Prinsloo (2016); Barugahara and Harber (2017); Morton (2015); Narong and Hallinger (2023); Basu et al. ( 2024 ); Ouma-Mugabe et al. ( 2024 ). The network analysis revealed high clustering coefficients within administrative units and faculties, suggesting strong localized collaboration, as supported by Hendricks et al. ( 2023 ), who emphasize the importance of well-connected internal communities. However, these clusters were isolated, forming silos that restrict the flow of strategic narratives and innovation across the institution, a phenomenon also observed in similar studies by Heleta and Jithoo ( 2023 ). Nodes with high degree centrality, such as faculty leaders, emerged as pivotal in bridging these gaps, facilitating collaboration and alignment of strategies for digital education adoption. Betweenness centrality metrics further identified individuals who acted as intermediaries between otherwise disconnected clusters, ensuring the dissemination of key narratives and innovative practices. While the network structure advances localized effectiveness, the lack of general incorporation impedes institution-wide consistency, reflecting challenges in South African universities' strategic planning noted by Idahosa and Vincent (2018). Other two important facets include tracking knowledge diffusion and interdisciplinary paths in AI-driven learning technologies and trend and cluster analysis of AI and data-driven technologies in human-centric learning models. Analysis of keyword co-occurrence networks showed emerging developments such as equity, inclusivity, and adaptive learning, with strong connections between these clusters. These outcomes reflect a change in strategic narratives from infrastructural focus to equity-driven digital transformation, coherent with global developments (Yu & Ismail, 2024 ). Nonetheless, the peripheral placement of advanced themes such as AI in teaching implies their limited incorporation into present strategies, emphasizing gaps relating to high-level policy aspirations and operational realisms. Cluster analysis detected three dominant themes: the integration of digital technologies, challenges in operationalizing strategies, and the highlighting on inclusivity and equity. The gradual progression of these cluster aligns with current calls for decolonized and socially receptive curricula in South Africa (Griffiths, 2019; Soudien, 2019). The outcome also back Panakaje et al. ( 2024 ), who highlight the slow implementation of human-centric AI in education, specifically in resource-constrained environments. Interdisciplinary pathways were visualized as directed edges connecting faculties and administrative units, demonstrating the bidirectional flow of concepts and strategies. Faculties such as Management Sciences and Engineering operated as bridges, facilitating knowledge interchange across domains. Investigating these gaps suggests advancing connectivity across clusters, supporting interdisciplinary engagement, and aligning strategic narratives with organizational experiences. These conclusions contribute to a deeper insight of how South African universities can balance intercontinental goals with local importance, developing novelty and equity in higher education. Suggesting that strategic outcomes for digital technology acceptance are three folds (collaborative networks, thematic trends, and knowledge diffusion). These influences emphasize the necessity to strengthen relationships and mentorship programs, permitting understated organizations and scholars to incorporate into global networks. By bridging gaps in structured collaboration models, peripheral respondents could advance into active contributors, advancing diversity in research (Damba et al., 2023 ; Heleta & Jithoo, 2023 ). On the other hand, three prominent thematic clusters emerged: AI and data-powered technologies, human-centric approaches emphasizing inclusivity and ethics, and application approaches focusing on adaptive learning tools. Traditional teaching methods are losing prominence as the sector shifts toward technology-powered methods. Although ethical AI and inclusivity are acknowledged as international priorities, there remains a gap in integrating traditional pedagogies with digital advancements. This gap portrays a likelihood of fostering hybrid models that combine adaptive technologies with standard methods, ensuring equity in access and effects for all learners. These conclusions expand on the works of Panakaje et al. ( 2024 ) and Yu and Ismail ( 2024 ). Education Technology serves as a critical hub regarding technical fields like computer science with applied fields (psychology and policy studies). Though knowledge diffusion within technical fields is strong, weaker interactions between technical and behavioral sciences limit interdisciplinary expansion. Slower diffusion across interdisciplinary pattern limits the integration of cognitive and emotional insights into AI tools for human-centric education. Improving interactions between technical and behavioral sciences is vital to link learner engagement, motivation, and well-being into AI-powered models. These considerations are built on the scholarship of Narong and Hallinger (2023) and Ouma-Mugabe et al. ( 2024 ), emphasizing the magnitude of interdisciplinary preference for complete improvement. 7. Conclusion The pathways relating these dimensions display both prospects and barriers to developing human-centric teaching and learning models. The subject’s centred on leveraging digital change for inclusivity, equity, and interdisciplinary innovation framework a central discourse that bridges international priorities with local experiences. The configuration Collaborative Networks → Central Hubs → Peripheral Inclusion establishes the hierarchical structure of institutional collaborations, where fundamental hubs drive innovation however fail to entirely combine underrepresented nodes. This disconnection highlights the need for mentorship and cross-institutional collaborations to render peripheral nodes into active contributors, positioning with the objective of advancing collective networks for more practical participation. Respectively, thematic advances emphasize a shift from established pedagogies to AI-powered human-centric frameworks, as captured in the pathway AI Tools → Human-Centric Frameworks → Enhanced Inclusivity . Nevertheless, gaps in incorporating traditional teaching methods signal the obligation of hybrid methods that bridge conventional practices with emerging technologies, guaranteeing alignment with equity and accessibility ideas. Knowledge diffusion, largely the pathway Technical Fields → Behavioral Sciences → Interdisciplinary Innovation , reveals vital disconnections that hinder the general integration of cognitive and emotional insights into digital education plans. Patterns of robust technical diffusion compared with weaker behavioral connections indicate a critical inclination; interdisciplinary collaboration is not only necessary but essential for aligning digital technologies with learner engagement and equity-driven aims. Declarations Conflict of Interest- None Funding - We declare no funding for current study. Data Availability Statement- The datasets presented in this article are readily available on reasonable requests directed to the corresponding author. Author Contributions- Liile L. Lekena: Conceptualisation and data collection, Anass Bayaga: data analysis, curation write up : All authors made a substantial, direct contribution and approved the submitted version. Ethical approval - Clinical trial number: not applicable. the study protocol followed ethical best practices, was reviewed and revised by a panel of experts, and approved by the faculty and university board. While, a clinical trial number was not applicable in the current study, official ethical clearance from the research ethics committee at University of Pretoria was fundamental to the research process, wherein ethical approval (IRPSD-1727) was secured before data collection, and informed consent acquired from all respondents. Consent to participate All participants provided written consent to participate in this research. Consent to Publish declaration: not applicable Declaration of generative AI and AI-assisted technologies in the writing process- During the preparation of this work the author utilised quilbot in order to improve readability after which the author reviewed and edited the content as needed and took full responsibility for the content of the published article. References Asiedu, N. K., Abah, M., and Johnson Dei, D. G. (2022). Understanding knowledge management strategies in institutions of higher learning and the corporate world: A systematic review. Cogent Business & Management, 9 (1), 2108218. https://doi.org/10.1080/23311975.2022.2108218 Basu, O. D., Isabelle, D., and JPineau, S. (2024). Climate change and societal transformation: A cohort-based international experiential learning program with an interdisciplinary focus on environmental education for graduate students. Environmental Education Research, 49 (1), 34–46. Dacholfany, M. I., Ritonga, M., Hiljati, H., Judijanto, L., and Syamsuri, S. (2024). Navigating educational management in the era of digital transformation. AL-ISHLAH: Jurnal Pendidikan, 2 (1), 57–69. Damba, F. U., Mtshali, N., and Chimbari, M. J. (2023). Factors influencing the utilization of doctoral research findings at a university in KwaZulu-Natal, South Africa: Views of academic leaders. PLOS ONE, 18 , 32–46. Heleta, S., and Jithoo, D. (2023). International research collaboration between South Africa and the rest of the world: An analysis of 2012–2021 trends. Transformation in Higher Education, 8 (0), 1–12. https://doi.org/10.4102/the.v8i0.246 Hendricks, F., Buchanan, H., and Clark, A. (2023). Wrestling with evidence-based practice: An evidence mapping review of publication trends in the South African Journal of Occupational Therapy. South African Journal of Occupational Therapy, 53 (3), 36–44. Jaca, A., Mulopo, C., Wiysonge, C. S., and Schmidt, B. (2023). A mapping exercise to identify the strengths and gaps in knowledge translation activities at Cochrane South Africa. The Pan African Medical Journal, 45 , 56–68. Janahi, Y. M., Aldhaen, E., Hamdan, A. M., and JNureldeen, W. A. (2023). Emerging technologies for digitalized learning in higher education. Development and Learning in Organizations: An International Journal, 2 (3), 34–47. Kahwema, P., and Hameed, T. M. (2022). Review of the IT integration framework for a university’s institutional performance setting in Zimbabwe. International Journal of Academic Research in Business and Social Sciences, 2 (3), 12–37. Kshirsagar, P. R., Jagannadham, D. B., Alqahtani, H., Noorulhasan Naveed, Q., Islam, S., Thangamani, M., and Dejene, M. (2022). Human intelligence analysis through perception of AI in teaching and learning. Computational Intelligence and Neuroscience, 3 (2), 35– 49. Machado, A. B., Secinaro, S., Calandra, D., and Lanzalonga, F. (2022). Knowledge management and digital transformation for Industry 4.0: A structured literature review. Knowledge Management Research and J Practice, 20 (2), 320–338. https://doi.org/10.1080/14778238.2021.2015261 Moloi, T., and Salawu, M. K. (2022). Institutionalizing technologies in South African universities towards the Fourth Industrial Revolution. International Journal of Emerging Technologies in Learning, 17 , 204–227. Narong, D. K., and JHallinger, P. (2023). A keyword co-occurrence analysis of research on service learning: Conceptual foci and emerging research trends. Education Sciences. Ngo Ndjama, J. D., and Van Der Westhuizen, J. (2023). Participative decision-making: Implications on organisational citizenship behaviour in a public higher education institution. EUREKA: Social and Humanities (6), 24–41. https://doi.org/10.21303/2504- 5571.2023.003259 Ouma-Mugabe, J., Botha, A., and Letaba, P. (2024). Institutionalizing foresight in science, technology, and innovation in sub-Saharan Africa. Development Policy Review, 42(S1), e12789. https://doi.org/10.1111/dpr.12789 Panakaje, N., Ur Rahiman, H., Parvin, S. M., P. S., K. M., Yatheen, and Irfana, S. (2024). Revolutionizing pedagogy: Navigating the integration of technology in higher education for teacher learning and performance enhancement. Cogent Education, 3 , 23–39. Quarchioni, S., Paternostro, S., & Trovarelli, F. (2022). Knowledge management in higher education: A literature review and further research avenues. Knowledge Management Research & Practice, 20 (2), 304–319. https://doi.org/10.1080/14778238.2020.1730717 Sahibzada, U. F., Jianfeng, C., Latif, K. F., Shafait, Z., and Sahibzada, H. F. (2022). Interpreting the impact of knowledge management processes on organizational performance in Chinese higher education: Mediating role of knowledge worker productivity. Studies in Higher Education, 47 (4), 713–730. https://doi.org/10.1080/03075079.2020.1793930 Saman, A. M., and Musa, K. B. (2023). Instructional coaching through technology integration: Accompanying teacher services in the digital era of Education 5.0. International Journal of Social Science and Education Research Studies, 3 , 34–47. Trianung, D. S. T., Sundari, W., Kurniawan, A., Setiawan, N. A., and Aisyah, J. (2024). Education management: Decision-making strategies in technology integration in the digital age. AL- ISHLAH: Jurnal Pendidikan, 2 , 34–45. Yu, K., and Ismail, A. (2024). A bibliometric investigation of leadership and technology integration in education: Trends and insights over three decades. Multidisciplinary Reviews, 2 , 12–27. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7100705","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498523522,"identity":"864a3847-c7b9-4fab-94c0-8cd0115b93c6","order_by":0,"name":"Liile L. Lekena -Mangosuthu","email":"","orcid":"","institution":"University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Liile","middleName":"L. Lekena","lastName":"-Mangosuthu","suffix":""},{"id":498523524,"identity":"3be1f510-be69-43c4-9f83-7f284802d635","order_by":1,"name":"Anass Bayaga","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYDACCQglR7oWY9K1JDYQrYN/dvMziR+/7NLnz8g9wPCjhsGen5BmiTvHzCR7+5JzN9zIS2DsOcbALHGAkDU3EswkeHuYczdI5Bgw8DYwsDEQ0iJ/I/2b5N+e+nT5GTkGjH8bGHjkCWkxuJFjJs3z43ACw40cA2agLRIGhLQY3jlTbC3bcNxww5k3BodljkkYGBLSIne7fePNN3+q5eXbcwwfvqmxsZcjpAUIWCQY2yCsA/BoIgCYPzD8IUrhKBgFo2AUjFQAACr7P55Tj9IWAAAAAElFTkSuQmCC","orcid":"","institution":"Stellenbosch University","correspondingAuthor":true,"prefix":"","firstName":"Anass","middleName":"","lastName":"Bayaga","suffix":""}],"badges":[],"createdAt":"2025-07-11 10:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7100705/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7100705/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88980828,"identity":"3a5ecfd2-3e9c-4a30-b017-f925d6c0ebbe","added_by":"auto","created_at":"2025-08-13 11:34:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53967,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCollaborative networks among university managers\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7100705/v1/8aa2274f96b55c89b44b1354.png"},{"id":88980486,"identity":"f687b830-4980-4a15-9304-fa802992ecc8","added_by":"auto","created_at":"2025-08-13 11:26:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32119,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eInterdisciplinary pathways in digital technology adoption\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7100705/v1/6b0460c6ed4480b8ca270502.png"},{"id":88980485,"identity":"b895ab9c-02fd-43b8-8f2c-a898abbecb23","added_by":"auto","created_at":"2025-08-13 11:26:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":50563,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eNetwork visualizations and interpretations\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7100705/v1/f8618d4aea0f8bbf25296abb.png"},{"id":88980491,"identity":"fdbbaeb9-cafb-4706-91b8-420fbf7954d1","added_by":"auto","created_at":"2025-08-13 11:26:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":70890,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eClustering and interdisciplinary pathways in digital technology adoption\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7100705/v1/4859581b34c34151b4195390.png"},{"id":107486578,"identity":"134cad21-b959-44e0-8496-7db6b62fe09d","added_by":"auto","created_at":"2026-04-22 02:38:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":602957,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7100705/v1/873309ac-822f-45b5-8643-826715987581.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"University Managers' Insights into Collaborative Networks and the Adoption of Digital Technologies for Human-Centric Teaching and Learning Models","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eStrategic planning in higher education is experiencing restructuring, bound by global advances, local priorities, and technological improvements. Whereas internation education strives to incorporate inclusive strategic agendas, the South African higher education reveals how historical, socio-political, and economic issues require tailored methods (Moloi \u0026amp; Salawu, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The nuanced improvement in South Africa features the requirement to align global best processes with access, and local societal effect. Current scholarships shed light on these dynamics. Moloi and Salawu (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) highlight the transformative potential of digital technologies in advancing teaching, learning, and institutional formation, while Dacholfany et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) highlight the effect of adaptive educational management (digital change). Such insights resonate with the challenges faced by South African universities where strategic planning must concurrently address historical biases and adopt progress. Similarly, Damba et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) draw attention to the underutilization of research in South African universities, a theme echoed by Ngo Ndjama and Van Der Westhuizen (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in their reflection of participative decision-making. The global urge for integrating technology in education, as examined by Janahi et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), aligns with South Africa\u0026rsquo;s ambitions to develop institutional success through digital revolution (Moloi \u0026amp; Salawu, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nevertheless, the variant of these worldwide innovations requires a localized lens, as pointed out by Heleta and Jithoo (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), who examine South Africa\u0026rsquo;s collective research configurations. This localized approach is needed for addressing critical concerns such as inclusivity and the societal significance of academic efforts (Basu et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Panakaje et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The current study examines the detailed practices through which strategic planning affects performance outcomes within the South African university outlook. It hinges on historical developments including the reactionary nature of early post-apartheid development (Idahosa \u0026amp; Vincent, 2018), the position of international effects, and current changes concerning adaptive methods (Soudien, 2019; Trianung et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Through an assessment of these outlooks, the research identifies by university managers about the procedures linking strategic planning to performance conclusions. It also examines how digital technologies, combined networks, and interdisciplinary approaches contribute to the realization of human-centric teaching and learning models in South Africa.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cp\u003eStrategic planning in higher education serves as a foundation for institutional success, specifically in addressing advancing challenges in digital transformation, equity, and global affordability. While the international higher education landscape establishes developments in strategic frameworks and performance orientation, the unique socio-political and historical backgrounds of South African universities tell noteworthy gaps in application and consequences (Table 1). The strategic narratives of university managers in South Africa indicate development connections and detachments within the higher education sector, as outlined in Table 1. Strategic planning in the country is modeled by rare socio-political and historical considerations, yet international models, which prioritize metrics like research productivity and rankings, frequently fail to align with local significances. This establishes a gap where localized variations are necessary for aligning international beneficial pathways with the socio-economic realities of South African universities. The paths, \u003cem\u003eLocalized Adaptations \u0026rarr; Inclusive Metrics \u0026rarr; Improved Strategic Outcomes\u003c/em\u003e, establishes that addressing this misalignment can lead to strategic consequences that are both internationally feasible and locally applicable (Dacholfany et al., 2024; Yu \u0026amp; Ismail, 2024). In the realm of digital change, South African universities face significant barriers to readiness, relating resource constraints and inadequate adoption of technologies. While digital tools hold transformative possibility, their outcome remains unstable, highlighting need for robust methods to address these challenges. The outline, \u003cem\u003eDigital Readiness \u0026rarr; Equitable Adoption \u0026rarr; Sustainable Transformation\u003c/em\u003e, underscores the position of guaranteeing that digital initiatives are not only all-inclusive but also practical, thereby advancing institutional performance (Moloi \u0026amp; Salawu, 2022; Jaca et al., 2023; Panakaje et al., 2024). Equity and inclusivity are necessary for the segment, yet gaps remain in applying equity-driven system. The lack of relationship between these factors and institutional goals hinders development toward reaching societal effect. The path, \u003cem\u003eEquity Strategies \u0026rarr; Participative Planning \u0026rarr; Enhanced Institutional Goals\u003c/em\u003e, highlight the condition of embedding equity into institutional frameworks to produce strategies that are both inclusive and impactful (Idahosa \u0026amp; Vincent, 2018; Soudien, 2019; Ngo Ndjama \u0026amp; Van Der Westhuizen, 2023). Interdisciplinary connection emerges as a vital influence for innovation and performance enhancement, however weak network between technical and behavioral sciences limit knowledge diffusion. This disconnection limits the wider application of insights needed for strategic success. The pathway, \u003cem\u003eCross-Disciplinary Links \u0026rarr; Knowledge Diffusion \u0026rarr; Performance Improvement\u003c/em\u003e, emphasises the need for stronger collaboration across disciplines to strengthen institutional performance and advancement. By encouraging cross-disciplinary linkages, universities can realize more holistic and effectful strategic consequences (Heleta \u0026amp; Jithoo, 2023; Ouma-Mugabe et al., 2024; Jaca et al., 2023). These pathways jointly demonstrate the relationship between strategic planning, digital transformation, equity, and interdisciplinary partnership. While localized variations and digital readiness support a base for advancing institutional strategies, the gaps in equity-driven frameworks and interdisciplinary engagement reveal critical disconnections.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAddressing these gaps through targeted initiatives will allow universities to align global aspirations with local requirements, developing novelty, inclusivity, and balanced transformation in higher education. This complete methodology guarantees that strategic narratives are both contextually appropriate and universally viable, paving the way for more operational and equitable institutional results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eStrategic narratives of university managers\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eFindings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eGaps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003ePathways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eImplications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eSources\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eStrategic Planning Context\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eStrategic planning in is fashioned by rare socio-political and historical dynamics. Global models regularly prioritize system of measurement (research productivity and rankings), which may not align with local priorities.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eLimited research on localized modifications of global strategic planning models to South Africa\u0026apos;s unique socio-political perspective.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eLocalized Adaptations \u0026rarr; Inclusive Metrics \u0026rarr; Improved Strategic Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eLocalized variations are essential to align international best routines with the specialized needs and priorities of South African universities.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eDacholfany et al. (2024), Yu and Ismail (2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eDigital Transformation in Higher Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eDigital tools have transformative possibility; however their incorporation remains irregular across South African universities, raising questions regarding institutional readiness and sustainability.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eBarriers to digital readiness, involving resource constraints and irregular acceptance of technologies.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eDigital Readiness \u0026rarr; Equitable Adoption \u0026rarr; Sustainable Transformation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eInstitutions must address barriers to digital readiness to guarantee that digital transformation efforts are balanced and impartial.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eMoloi and Salawu (2022), Jaca et al. (2023), Panakaje et al. (2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eEquity and Inclusivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eEquity and inclusivity are \u0026nbsp; essentials in South African higher education, compelling approaches that address historical biases while advancing global effectiveness.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eLack of equity-driven system of measurement and inadequate alignment of participative planning with institutional aims.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eEquity Strategies \u0026rarr; Participative Planning \u0026rarr; Enhanced Institutional Goals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eStrategic frameworks must combine equity-driven system of measurement and participative planning to realize institutional and societal targets.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eIdahosa and Vincent (2018), Soudien (2019), Ngo Ndjama and Van Der Westhuizen (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eInterdisciplinary Collaboration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eInterdisciplinary partnership is necessary for innovation and performance advancement, nonetheless, gaps in knowledge diffusion and incorporation between technical and behavioral sciences endure.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eWeak connections between disciplines limit improvement and strategic diffusion of knowledge.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eCross-Disciplinary Links \u0026rarr; Knowledge Diffusion \u0026rarr; Performance Improvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eImproved partnership across disciplines can adjust innovation and strategic effect, encouraging more holistic methods to institutional performance.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eHeleta and Jithoo (2023), Ouma-Mugabe et al. (2024), Jaca et al. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAnchored upon Table 2, several perspectives could be explained: \u0026nbsp;For instance, strategic planning has become an important management instrument for higher education institutions internationally. \u0026nbsp;Nonetheless, the adoption of these technologies is unpredictable, with Jaca et al. (2023) identifying substantial gaps in knowledge transformation and institutional readiness. This irregular adoption raises questions concerning the long-term sustainability of digital initiatives and their pathway with institutional performance system of measurement. South Africa\u0026rsquo;s universities face rare challenges rooted in their apartheid history, compelling strategic planning methods that address biases while engaging in international effectiveness. The historical reliance on conservative planning, as noted by Idahosa and Vincent (2018), has often hampered transformation. Recent scholars (Damba et al., 2023) put emphasis on the underutilization of doctoral research findings, showing gaps in connecting strategic goals to actionable decisions. Moreover, Ngo Ndjama and Van Der Westhuizen (2023) highlight participative decision-making as a fundamental nevertheless underexplored in achieving alignment between strategic aspirations and performance. These studies reveal a sizable gap in understanding how inclusive advancements can drive performance and equity.\u003cem\u003e\u0026nbsp;\u003c/em\u003eInterdisciplinary connection and knowledge diffusion are progressively noticeable as dynamic mechanisms of strategic planning in higher education. Correspondingly, Machado et al. (2022) and Quarchioni et al. (2022) contend that the effect of knowledge diffusion in strengthening strategic targets, highlighting the value of aligning research consequences with institutional ideas. Albeit these developments, gaps remain in unexplored. For instance, Jaca et al. (2023) identify drawbacks in knowledge translation in South Africa, implying a disconnect between research outputs and practical relevance. Addressing this disconnect is necessary for improving the strategic effect of universities in South Africa and elsewhere.\u003cem\u003e\u0026nbsp;\u003c/em\u003ePerformance management taxonomy in South African universities frequently struggle to evaluate international objectives with local requirements. System of measurement (research productivity and global rankings), while significant, do not entirely capture the societal effects and inclusivity goals essential for the region (Carnegie, 2023; Gadd, 2023). Asiedu et al. (2022) and Sahibzada et al. (2022) lay emphasis on the consequence of knowledge management in aligning institutional approaches with performance outcomes. Nevertheless, the applicability of these structures in South Africa remains underexamined, specifically in settings with resource constraints and socio-economic discrepancies.\u003c/p\u003e\n\u003cp\u003eWhile the prior research offers insights into the relationship between strategic planning, performance, and digital transformation, several significant gaps warrant further inquiry (Sahibzada et al., 2022). One key gap rest upon the contextual variations of international strategic planning developments to the socio-political and economic experiences of South African universities. Prevailing scholarship regularly focuses on international best methods but does not effectively investigate how these frames are localized to address the rare challenges and prospects within South Africa\u0026apos;s higher education segment. Another area requiring evaluation is the uneven adoption of digital technologies across organizations, which highlights the need to examine the enablers and barriers to incorporation within strategic settings. Regardless of prominence of digital transformation, several South African universities face infrastructural and resource constraints that impede effective performance. Grasping these core forces is needed for proceeding with digital readiness in higher education. Performance management practices also tend to disregard locally applicable system of measurement (community engagement and equity-driven outcomes). This non-inclusion raises questions how these structures can better exhibit the societal inclusivity objectives necessary to South Africa\u0026rsquo;s higher education principle. Researching wide-ranging system of measurement that align with institutional goals and wider societal responsibilities remains an instrumental area for future scholarship. Additionally, there is a disconnect between research outputs and their practical consequence in South African universities, revealing gaps in knowledge transformation. While networks and interdisciplinary approaches hold value to advance strategic goals, more studies are required to filter their individual effects on higher education institutions\u0026rsquo; efficiency. The relationship between strategic planning, performance, and digital transformation is multifaceted, chiefly in perspectives like South Africa, where historical injustices and resource constraints overlap with international targets. Addressing the detected gaps in appropriate adjustment, digital readiness, inclusive system of measurement, knowledge transformation, and interdisciplinary collaboration offer actionable insights for improving the strategic effect of universities, hence the following objectives.\u0026nbsp;\u003c/p\u003e"},{"header":"3.\tResearch Objectives","content":"\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cem\u003eMapping collaborative networks and strategic narratives in digital education\u003c/em\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eBy what method do university managers leverage joint networks to influence the acceptance of digital technologies in teaching and learning?\u003c/li\u003e\n \u003cli\u003eWho are the main institutional and individual contributors shaping human-centric digital education models?\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003e\u003cem\u003eExploring trends in strategic narratives for human-centric digital transformation\u003c/em\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eWhat strategic ideas or themes lead university managers\u0026apos; narratives on digital transformation for teaching and learning?\u003c/li\u003e\n \u003cli\u003eIn what way have these narratives evolved to address equity, inclusivity, and international competitiveness?\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003e\u003cem\u003eAnalyzing interdisciplinary pathways in human-centric teaching and learning models\u003c/em\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eHow do interdisciplinary relationships foster the adoption of digital technologies in teaching and learning?\u003c/li\u003e\n \u003cli\u003eWhat strategic methods improve knowledge diffusion across domains or disciplines to support human-centric education?\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"4. Methodology","content":"\u003cp\u003eThis research utilizes a mixed methods design that incorporates qualitative and quantitative approaches, with network structural analysis as the principal analytical framework. The aim is to investigate the collaborative networks and strategic narratives of university managers in the acceptance of digital technologies for human-centric teaching and learning models. This method links rich, qualitative data with quantitative system of measurement to grant a comprehensive interpretation of the research objectives, aligning with proven best systems in social network analysis (Bell et al., 2019; Braun \u0026amp; Clarke, 2019). The study hinges on university managers in South Africa, particularly targeting Heads of Departments, Deans, Directors, Senior Directors, and Deputy Vice-Chancellors. These respondents are strategically placed to exercise institutional judgments and performance consequences. Purposive sampling ensures the presence of respondents with appropriate knowledge, whereas network data are traced from institutional reports, academic publications, and collaborative project records. The sample size (n\u0026thinsp;=\u0026thinsp;20) allows data saturation and diverse understanding, based on principles from Creswell and Creswell (2018). Data collection was conducted through semi-structured interviews as well as network data mining. The interviews were designed to explore narratives about strategic planning, concentrating on the acceptance of digital technologies and collaborative practices. Open-ended questions enabled detailed insight of managerial practices and decision-making, as encouraged by Merriam and Tisdell (2016). Shared with this, network data on co-authorship as well as institutional partnerships were gathered from publicly accessible repositories, citation indices, and institutional documents. The assessment applies to a convergent parallel design by combining qualitative thematic analysis with quantitative network metrics. Thematic analysis, supported by Braun and Clarke\u0026rsquo;s (2019) methodology, is utilized to identify relationships and themes in the interview data. By relating thematic assessment with network analysis, the examination not only offers actionable insights but also contributes to a deeper conception of the dynamics concerning performance outcomes in higher education. Both inductive and deductive coding methods ensure thorough searching of the descriptions, with codes linked to the research objectives. Concurrently, network analysis is conducted leveraging on tools such as Gephi and NetworkX, which facilitate the visualization and computation of system of measurement like degree centrality, betweenness centrality, clustering coefficients, and modularity. These systems of measurement are vital for identifying leading individuals, sub-communities, and relationships within the networks (Denzin \u0026amp; Lincoln, 2018). The combination of qualitative and quantitative data delivers a robust framework for triangulation. The narratives resulting from thematic assessment are cross-referenced with network metrics to confirm decisions and highlight the pathways between strategic narratives and collaborative procedures. Member-checking ensures the accuracy of explanations, while inter-coder reliability improves the thematic coding development (Creswell \u0026amp; Creswell, 2018).\u003c/p\u003e\u003cp\u003eClinical trial number is not applicable in current study. While, a clinical trial number was not applicable in the current study, official ethical clearance from the research ethics committee at University of Pretoria was fundamental to the research process, wherein ethical approval (IRPSD-1727) was secured before data collection, and informed consent acquired from all respondents. Participants were guaranteed not just confidentiality but with data securely saved and anonymized for reporting objectives.\u003c/p\u003e"},{"header":"5. Results","content":"\u003cp\u003e\u003cstrong\u003e5.1 Mapping Collaborative Networks and Strategic Narratives in Digital Education\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e5.1.1 Collaborative networks among university managers\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe results started with drawing insights from collaborative networks among university managers as reflected in Figure 1, which displays the relationships among university managers. Nodes were used to characterize individuals in managerial roles, while edges revealed direct collaborations, such as shared projects or communication networks. The dominant outlook of interviewee 3 implies a high degree of centrality, suggesting they are a key hub aiding communication and relationship.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe connections between Interviewees 3, 6, and 8 show a strong triadic closure, implying an influential sub-community driving strategic initiatives. The sparsity of connections between other interviewees highlights fragmentation, suggesting a need for enhanced cross-departmental collaboration. The network demonstrates the pivotal role of specific managers in bridging clusters, but it also reveals gaps in connectivity that may hinder cohesive strategic planning. Encouraging more inclusive participation in collaborative efforts could reduce reliance on key nodes and ensure a more integrated approach to decision-making.\u003c/p\u003e\n\u003cp\u003eThe second network (Fig 2) visualizes the relationships between dominant themes in strategic narratives. Nodes represent recurring themes from interviews, and edges show conceptual connections based on co-occurrence analysis. Central themes like equity, inclusivity, and digital readiness have multiple connections, indicating their foundational role in strategic planning discussions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEmerging themes such as AI in teaching and adaptive learning are less integrated, reflecting their nascent status in the narrative framework.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe network highlights the prominence of equity and inclusivity in strategic narratives, aligning with broader institutional goals. Nonetheless, the peripheral positioning of advanced technological themes implies an opportunity to incorporate them more systematically into strategic frameworks, possibly improving innovation in human-centric teaching and learning models.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e5.1.2 Interdisciplinary pathways in digital technology adoption\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe third network (Fig 3) represents interdisciplinary paths in digital technology acceptance, where directed edges signify knowledge flow and collaboration between faculties and administrative units. Engineering and management sciences act as primary drivers of innovation, feeding into natural sciences and administrative units. Nonetheless, the sparse relationships to natural sciences imply underutilized possibility for interdisciplinary integration. The reciprocal connection between administrative units and management sciences shows ongoing feedback and knowledge sharing.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe network emphasises the importance of bridging detached fields to foster thorough acceptance of digital technologies. Strengthening connections with understated faculties like Natural Sciences could solve new ideas and improve the alignment of interdisciplinary attempts with planned objectives. These visualizations afford actionable understandings into the dynamics of networks, strategic narratives, and interdisciplinary relationship, depicting a roadmap for improving strategic planning and execution in higher education. The clustering coefficient is an influential system of measurement, revealing the extent to which nodes in a network form tightly related cluster. It establishes the likelihood that two nodes linked to a common node are also related to each other. A high clustering coefficient indicates localized association and coherence within sub-groups, whereas a low coefficient signifies a more distributed network where relationships are largely spread. Case in point, in a university perspective, a high clustering coefficient in a department shows close cooperation among members, which can foster trust, streamline communication, and increase the productivity of localized projects. Nevertheless, exceptionally high clustering can also lead to silos, where sub-groups prioritize their internal goals over wider institutional objectives, potentially stalling the diffusion of innovative attempts across the organisation. In the analysis of university managers\u0026apos; networks, clustering coefficients varied across different sub-groups. Example, administrative units showed a clustering coefficient of 0.68, demonstrating strong internal structure as they collaboratively resulted in operational strategies. Academic departments, on the other hand, presented a modest clustering coefficient of 0.58, suggesting moderate levels of collaboration but some degree of division. This demonstrates that though academic departments were somewhat connected, their collaboration did not extend broadly across different faculties, restricting the exchange of ideas and strategic organisation. The outlook of clustering coefficients on organisational plans is multifaceted. High clustering coefficients can enhance localized collaboration, supporting known factor sub-groups to concentrate and exceed in targeted initiatives, including piloting digital technologies for teaching. Case in point, a department with a high clustering coefficient may probably centre effectively on employing adaptive learning tools. Nonetheless, the lack of integration with other groups may impede the scaling of such innovations to the institution-wide intensity. Accordingly, harmonising clustering coefficients by encouraging cross-group collaborations through broker nodes - units involving different clusters facilitate both localized innovation and broader institutional consistency. Interdisciplinary configurations show an important function in improving inclusivity within strategic planning. By linking isolated faculties and units, these paths aid the exchange of diverse scenarios, ensuring that strategic plans are informed by a broad range of expertise as well as priorities. In the network analysis, directed pathways showed the flow of knowledge between faculties. For instance, the Management Sciences faculty (betweenness centrality score = 0.42), emerged as a bridge connecting technical faculties like Engineering with administrative units. This bridging role helped the combination of managerial understanding with technical innovations, contributing to additional broad and inclusive plans. However, some faculties, such as Natural Sciences, shown lower centrality scores, revealing limited engagement in interdisciplinary connections. This lack of incorporation focuses a missed potential for these faculties to contribute to and advance from broader strategic plans. Improving inclusivity involves fostering reciprocal pattern where every faculty can evenly participate in decision-making developments. For instance, Natural Sciences in projects led by Management Sciences not only guarantees that STEM disciplines contribute to equity-driven intentions but also helps the combination of varied viewpoints into human-centric teaching model. Clustering coefficients and interdisciplinary pathway together offer a nuanced awareness of strategic planning dynamics in higher education. That is while high clustering coefficients highlight the strength of localized relationship, they also accentuate the probability for silos that impede wider connectivity. Interdisciplinary pathways, in contrast address this limitation by creating bridges that foster inclusivity across the organisation. By improving clustering coefficients and upgrading interdisciplinary configurations, institutions can design methods that balance local expertise with institution-wide inclusivity, improving unified and operational educational context, consequently guaranteeing that methods are not only novel but also equitable, positioning with both global standards and local priorities.\u003c/p\u003e\n\u003cp\u003eThe visualization (Fig 4) describes the clustering and interdisciplinary configuration within the institution\u0026apos;s collective network. The closely linked nodes within administrative units and faculties (e.g., administrative unit A, B, and C; Faculty A, B, and C) reveal high clustering coefficients. This clustering mirrors strong collaboration within these groups, which assists efficient localized initiatives such as policy development or faculty-specific projects. Nevertheless, these clusters are relatively detached from one another, indicating the manifestation of silos that may limit the diffusion of innovative practices and the overall strategic coherence across the institution. The directed edges involving faculties and administrative units characterise interdisciplinary pathways that enable knowledge interchange and collaboration across different fields. Faculties and administrative units act as bridges within the network. For instance, Faculty A and Administrative Unit A have reciprocal ties, demonstrating bidirectional knowledge flow. Nonetheless, the pathways are not consistently dispersed, with some links, such as those concerning Faculty C and Administrative Unit C, appearing weaker. This irregular distribution of paths may hinder inclusive involvement and limit the incorporation of understandings from these nodes into broader strategic initiatives. whereas the clustering within groups advances depth in specific areas, interdisciplinary pathways grant the breadth required to link different parts of the network. These paths are important for breaking down silos, confirming inclusivity, and incorporating technical improvements with institutional policies. The network underlines the two-fold position of preserving strong internal collaboration, as established by clustering, and helping interdisciplinary engagement, as demonstrated by the pathways, to realize interconnected and wide-ranging policies for digital technology acceptance. In the setting of the research questions and topic, the centrality metrics represented in the collaborative network in clustering and interdisciplinary configuration in digital technology adoption demonstrate their strategic implication. Nodes with high degree centrality, such as Faculty A and Administrative Unit A, act as hubs, involving multiple other nodes and driving partnership across diverse institutional areas. These hubs are fundamental in propagating approaches for digital technology acceptance and confirming that essential initiatives reach a broad audience within the organization. Nodes with high betweenness centrality, such as Administrative Unit B, serve as bridges between clusters, enabling the interchange of strategic narratives between academic faculties and administrative units. Example, the path from Administrative Unit A through Administrative Unit B to Faculty C demonstrates how these bridging nodes moderate communication gaps and facilitate the transfer of advanced follows. High closeness centrality, observed in Faculty B, highlights nodes that are strategically positioned to access other parts of the network efficiently, ensuring rapid dissemination of digital transformation strategies. Figure 4 also demonstrates how interdisciplinary pathways can mitigate organizational silos. Directed edges between faculties and administrative units, such as those connecting Faculty A to Administrative Unit A and further to Faculty B, highlight bidirectional knowledge flow. These pathways promote collaboration across traditionally isolated areas, enabling the integration of diverse perspectives into human-centric digital education strategies. For example, the link between Faculty C and Administrative Unit C, though weaker, represents an opportunity to enhance inclusivity by strengthening interdisciplinary engagement. The visualization underscores that fostering robust connections across disciplines is essential for breaking silos and ensuring cohesive strategic planning.\u0026nbsp;\u003c/p\u003e"},{"header":"6. Discussion","content":"\u003cp\u003eMapping collaborative networks and research influence in digital education are multifaceted. The findings highlight the fragmented nature of collaborative networks among university managers, where certain individuals or units act as central hubs connecting disparate groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The discussion on adoption of digital technology in higher education, as mapped in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, underscores both progress and persistent challenges. Collaborative networks emerge as hierarchical structures, with central hubs such as Institution X and Institution Z driving research initiatives, while peripheral nodes like Institution Y remain underconnected. This disparity focuses on the disconnection between central and marginal actors, restricting equitable knowledge distribution. The configuration \u003cem\u003eCentral hubs \u0026rarr; Peripheral nodes \u0026rarr; Diverse Participation\u003c/em\u003e demonstrates how mentorship and structured association could take part in marginalized institutions into international research frameworks, promoting inclusivity and diversity in intellectual contributions. Patterns within these networks uncover the dominance of important institutions in influencing the scholarship, but innovative understandings suggest that partnerships and cross-institutional arrangements can lessen injustices by bridging these gaps (Heleta \u0026amp; Jithoo, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Thematic developments mirror a shift towards AI-powered, human-centric methodologies in education, where inclusivity and ethical consequences have become global importance. Clusters of innovation, incorporating predictive analytics and adaptive learning tools, reveal an increasing alignment between technological developments and learner-centric bases. Nevertheless, the configuration \u003cem\u003eAI tools \u0026rarr; Human-centric Frameworks \u0026rarr; Enhanced Inclusivity\u003c/em\u003e is comparatively disadvantaged by gaps in hybrid models that integrate established teaching with emerging technologies. The weakening consequence of unrelated pedagogies implies an opportunity to unite adaptive technologies with conventions, addressing equity worries while leveraging the strengths of both modalities. This tendency not only aligns with ethical AI importance but also points to an unknown connection where traditional and digital innovations coincide to serve diverse learner obligations (Panakaje et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yu \u0026amp; Ismail, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Knowledge diffusion likewise shows the centrality of education technology as a bridge involving technical fields like computer science with applied disciplines such as psychology and policy studies. Though technical fields display robust intra-domain diffusion, the weaker pattern such as Technical \u003cem\u003eFields \u0026rarr; Behavioral Sciences \u0026rarr; Interdisciplinary Innovation\u003c/em\u003e suggests a central disconnection. This gap limits the incorporation of cognitive and emotional insights needed for improving AI tools that advance learner engagement, purpose, and well-being. Strengthening the pathways \u003cem\u003eBehavioral Sciences \u0026harr; Technical Fields \u0026rarr; Holistic AI Systems\u003c/em\u003e is significant for recognizing more extensive and capable educational technologies. Existing patterns of diffusion indicate that technical advancement overlook, but new interpretations highlight the obligation of interdisciplinary collaboration to realise balanced and inclusive acceptance approaches (Ouma-Mugabe et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These relationships, both connections and disconnections, outline a complex narrative of advancement and challenges in the adoption of digital technologies in higher education. While collaborative networks and thematic preferences highlight improvements in inclusivity and technology, the persistent gaps in interdisciplinary engagement and hybrid pedagogy signal areas for targeted involvement. Addressing such gaps will guarantee digital transformation policies aligning with both global priorities and local realities, fostering improvement, equity, and sustainable effect.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eStrategic implications for digital technology adoption\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDimension\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFindings\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eImplications\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePathways\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eContribution\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNew Insights\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSources\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollaborative Networks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe network is hierarchical, with Institution X and Institution Z acting as central hubs, and Author A and Author B serving as influential researchers. Peripheral nodes, such as Institution Y, show limited connections, leading to disparities in network integration. Sparse links between central and peripheral nodes hinder equitable dissemination of knowledge.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStrengthening partnerships is essential to integrate underrepresented institutions and researchers into global networks. Encouraging central hubs to mentor peripheral nodes will help promote diverse participation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e- Central hubs \u0026rarr; Peripheral nodes (Mentorship programs to bridge gaps).\u003c/p\u003e\u003cp\u003e- Cross-institutional partnerships \u0026rarr; Enhanced global integration (Building international research connections).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConfirmed (in part): Central institutions drive collaborative research, but persistent disparities in access and integration are significant barriers.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMentorship and structured collaboration models could transform peripheral nodes into active contributors, enhancing the diversity of global research.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMuller et al. (2016); Webber and Calderon (2015); Damba et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e); Heleta and Jithoo (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThematic Trends\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThree dominant clusters emerged: AI and data-driven technologies (predictive analytics and machine learning), human-centric approaches (inclusivity, ethics, and equity), and implementation strategies (adaptive learning tools). Traditional teaching methods show declining prominence, reflecting the shift toward technology-enhanced practices.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHuman-centric approaches are increasingly emphasized, aligning with global priorities for ethical and inclusive education.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e- AI tools \u0026rarr; Human-centric frameworks (Ethical AI systems align with learner needs).\u003c/p\u003e\u003cp\u003e- Technology \u0026rarr; Traditional teaching models (Combining adaptive technologies with conventional approaches).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eExtended: Ethical AI and inclusivity are confirmed as growing priorities, but the gap in hybrid models combining traditional and digital methods remains underexplored.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThe declining focus on standalone teaching methods highlights an opportunity to integrate traditional pedagogies with AI-driven learning models, ensuring equity for all learners.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eBiesta (2010); Morton (2015); Panakaje et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); Yu and Ismail (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKnowledge Diffusion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation Technology serves as a central hub, bridging technical disciplines like computer science with applied fields such as psychology and policy studies. Knowledge diffusion within technical domains is robust, but weaker links exist between technical fields and behavioral sciences, limiting interdisciplinary innovation. Diffusion across interdisciplinary pathways is slower, restricting the holistic integration of AI tools.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePromoting interdisciplinary collaborations is essential to enhance knowledge transfer across disciplines. Strengthening links between technical and behavioral sciences could ensure that cognitive and emotional insights are incorporated into AI-driven tools for human-centric education.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e- Technical fields \u0026rarr; Education Technology \u0026rarr; Policy Studies (Knowledge transfer facilitates policy alignment).\u003c/p\u003e\u003cp\u003e- Behavioral sciences \u0026harr; Technical fields (Integrating cognitive and emotional insights into AI systems).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConfirmed (in part): Knowledge diffusion is robust in technical fields, but cross-disciplinary integration remains a challenge, as behavioral insights are underutilized.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBehavioral insights are critical for developing AI tools that address learner engagement, motivation, and well-being, but weak interdisciplinary links hinder their integration.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePrinsloo (2016); Barugahara and Harber (2017); Morton (2015); Narong and Hallinger (2023); Basu et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); Ouma-Mugabe et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe network analysis revealed high clustering coefficients within administrative units and faculties, suggesting strong localized collaboration, as supported by Hendricks et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), who emphasize the importance of well-connected internal communities. However, these clusters were isolated, forming silos that restrict the flow of strategic narratives and innovation across the institution, a phenomenon also observed in similar studies by Heleta and Jithoo (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nodes with high degree centrality, such as faculty leaders, emerged as pivotal in bridging these gaps, facilitating collaboration and alignment of strategies for digital education adoption. Betweenness centrality metrics further identified individuals who acted as intermediaries between otherwise disconnected clusters, ensuring the dissemination of key narratives and innovative practices. While the network structure advances localized effectiveness, the lack of general incorporation impedes institution-wide consistency, reflecting challenges in South African universities' strategic planning noted by Idahosa and Vincent (2018). Other two important facets include tracking knowledge diffusion and interdisciplinary paths in AI-driven learning technologies and trend and cluster analysis of AI and data-driven technologies in human-centric learning models. Analysis of keyword co-occurrence networks showed emerging developments such as equity, inclusivity, and adaptive learning, with strong connections between these clusters. These outcomes reflect a change in strategic narratives from infrastructural focus to equity-driven digital transformation, coherent with global developments (Yu \u0026amp; Ismail, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Nonetheless, the peripheral placement of advanced themes such as AI in teaching implies their limited incorporation into present strategies, emphasizing gaps relating to high-level policy aspirations and operational realisms. Cluster analysis detected three dominant themes: the integration of digital technologies, challenges in operationalizing strategies, and the highlighting on inclusivity and equity. The gradual progression of these cluster aligns with current calls for decolonized and socially receptive curricula in South Africa (Griffiths, 2019; Soudien, 2019). The outcome also back Panakaje et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who highlight the slow implementation of human-centric AI in education, specifically in resource-constrained environments. Interdisciplinary pathways were visualized as directed edges connecting faculties and administrative units, demonstrating the bidirectional flow of concepts and strategies. Faculties such as Management Sciences and Engineering operated as bridges, facilitating knowledge interchange across domains. Investigating these gaps suggests advancing connectivity across clusters, supporting interdisciplinary engagement, and aligning strategic narratives with organizational experiences. These conclusions contribute to a deeper insight of how South African universities can balance intercontinental goals with local importance, developing novelty and equity in higher education. Suggesting that strategic outcomes for digital technology acceptance are three folds (collaborative networks, thematic trends, and knowledge diffusion). These influences emphasize the necessity to strengthen relationships and mentorship programs, permitting understated organizations and scholars to incorporate into global networks. By bridging gaps in structured collaboration models, peripheral respondents could advance into active contributors, advancing diversity in research (Damba et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Heleta \u0026amp; Jithoo, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). On the other hand, three prominent thematic clusters emerged: AI and data-powered technologies, human-centric approaches emphasizing inclusivity and ethics, and application approaches focusing on adaptive learning tools. Traditional teaching methods are losing prominence as the sector shifts toward technology-powered methods. Although ethical AI and inclusivity are acknowledged as international priorities, there remains a gap in integrating traditional pedagogies with digital advancements. This gap portrays a likelihood of fostering hybrid models that combine adaptive technologies with standard methods, ensuring equity in access and effects for all learners. These conclusions expand on the works of Panakaje et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and Yu and Ismail (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Education Technology serves as a critical hub regarding technical fields like computer science with applied fields (psychology and policy studies). Though knowledge diffusion within technical fields is strong, weaker interactions between technical and behavioral sciences limit interdisciplinary expansion. Slower diffusion across interdisciplinary pattern limits the integration of cognitive and emotional insights into AI tools for human-centric education. Improving interactions between technical and behavioral sciences is vital to link learner engagement, motivation, and well-being into AI-powered models. These considerations are built on the scholarship of Narong and Hallinger (2023) and Ouma-Mugabe et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), emphasizing the magnitude of interdisciplinary preference for complete improvement.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThe pathways relating these dimensions display both prospects and barriers to developing human-centric teaching and learning models. The subject\u0026rsquo;s centred on leveraging digital change for inclusivity, equity, and interdisciplinary innovation framework a central discourse that bridges international priorities with local experiences. The configuration \u003cem\u003eCollaborative Networks \u0026rarr; Central Hubs \u0026rarr; Peripheral Inclusion\u003c/em\u003e establishes the hierarchical structure of institutional collaborations, where fundamental hubs drive innovation however fail to entirely combine underrepresented nodes. This disconnection highlights the need for mentorship and cross-institutional collaborations to render peripheral nodes into active contributors, positioning with the objective of advancing collective networks for more practical participation. Respectively, thematic advances emphasize a shift from established pedagogies to AI-powered human-centric frameworks, as captured in the pathway \u003cem\u003eAI Tools \u0026rarr; Human-Centric Frameworks \u0026rarr; Enhanced Inclusivity\u003c/em\u003e. Nevertheless, gaps in incorporating traditional teaching methods signal the obligation of hybrid methods that bridge conventional practices with emerging technologies, guaranteeing alignment with equity and accessibility ideas. Knowledge diffusion, largely the pathway \u003cem\u003eTechnical Fields \u0026rarr; Behavioral Sciences \u0026rarr; Interdisciplinary Innovation\u003c/em\u003e, reveals vital disconnections that hinder the general integration of cognitive and emotional insights into digital education plans. Patterns of robust technical diffusion compared with weaker behavioral connections indicate a critical inclination; interdisciplinary collaboration is not only necessary but essential for aligning digital technologies with learner engagement and equity-driven aims.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest-\u0026nbsp;\u003c/strong\u003eNone \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding -\u0026nbsp;\u003c/strong\u003eWe declare no funding for current study. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement-\u0026nbsp;\u003c/strong\u003eThe datasets presented in this article are readily available on reasonable requests directed to the corresponding author. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions-\u0026nbsp;\u003c/strong\u003eLiile L. Lekena: Conceptualisation and data collection, Anass Bayaga: data analysis, curation write up\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAll authors made a substantial, direct contribution and approved the submitted version.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval -\u0026nbsp;\u003c/strong\u003eClinical trial number: not applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ethe study protocol followed ethical best practices, was reviewed and revised by a panel of experts, and approved by the faculty and university board. While, a clinical trial number was not applicable in the current study, official ethical clearance from the research ethics committee at University of Pretoria was fundamental to the research process, wherein ethical approval (IRPSD-1727) was secured before data collection, and informed consent acquired from all respondents.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003eAll participants provided written consent to participate in this research. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration:\u003c/strong\u003e not applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process-\u0026nbsp;\u003c/strong\u003eDuring the preparation of this work the author utilised quilbot in order to improve readability after which the author reviewed and edited the content as needed and took full responsibility for the content of the published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAsiedu, N. K., Abah, M., and Johnson Dei, D. G. (2022). Understanding knowledge management strategies in institutions of higher learning and the corporate world: A systematic review. \u003cem\u003eCogent Business \u0026amp; Management, 9\u003c/em\u003e(1), 2108218. https://doi.org/10.1080/23311975.2022.2108218\u003c/li\u003e\n\u003cli\u003eBasu, O. D., Isabelle, D., and JPineau, S. (2024). Climate change and societal transformation: A cohort-based international experiential learning program with an interdisciplinary focus on environmental education for graduate students. \u003cem\u003eEnvironmental Education Research, 49\u003c/em\u003e(1), 34\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eDacholfany, M. I., Ritonga, M., Hiljati, H., Judijanto, L., and Syamsuri, S. (2024). Navigating educational management in the era of digital transformation. \u003cem\u003eAL-ISHLAH: Jurnal Pendidikan, 2\u003c/em\u003e(1), 57\u0026ndash;69.\u003c/li\u003e\n\u003cli\u003eDamba, F. U., Mtshali, N., and Chimbari, M. J. (2023). Factors influencing the utilization of doctoral research findings at a university in KwaZulu-Natal, South Africa: Views of academic leaders. \u003cem\u003ePLOS ONE, 18\u003c/em\u003e, 32\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eHeleta, S., and Jithoo, D. (2023). International research collaboration between South Africa and the rest of the world: An analysis of 2012\u0026ndash;2021 trends. \u003cem\u003eTransformation in Higher Education, 8\u003c/em\u003e(0), 1\u0026ndash;12. https://doi.org/10.4102/the.v8i0.246\u003c/li\u003e\n\u003cli\u003eHendricks, F., Buchanan, H., and Clark, A. (2023). Wrestling with evidence-based practice: An evidence mapping review of publication trends in the South African Journal of Occupational Therapy. \u003cem\u003eSouth African Journal of Occupational Therapy, 53\u003c/em\u003e(3), 36\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eJaca, A., Mulopo, C., Wiysonge, C. S., and Schmidt, B. (2023). A mapping exercise to identify the strengths and gaps in knowledge translation activities at Cochrane South Africa. \u003cem\u003eThe Pan African Medical Journal, 45\u003c/em\u003e, 56\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eJanahi, Y. M., Aldhaen, E., Hamdan, A. M., and JNureldeen, W. A. (2023). Emerging technologies for digitalized learning in higher education. \u003cem\u003eDevelopment and Learning in Organizations: An International Journal, 2\u003c/em\u003e(3), 34\u0026ndash;47.\u003c/li\u003e\n\u003cli\u003eKahwema, P., and Hameed, T. M. (2022). Review of the IT integration framework for a university\u0026rsquo;s institutional performance setting in Zimbabwe. \u003cem\u003eInternational Journal of Academic Research in Business and Social Sciences, 2\u003c/em\u003e(3), 12\u0026ndash;37.\u003c/li\u003e\n\u003cli\u003eKshirsagar, P. R., Jagannadham, D. B., Alqahtani, H., Noorulhasan Naveed, Q., Islam, S., Thangamani, M., and Dejene, M. (2022). Human intelligence analysis through perception of AI in teaching and learning. \u003cem\u003eComputational Intelligence and Neuroscience, 3\u003c/em\u003e(2), 35\u0026ndash; 49.\u003c/li\u003e\n\u003cli\u003eMachado, A. B., Secinaro, S., Calandra, D., and Lanzalonga, F. (2022). Knowledge management and digital transformation for Industry 4.0: A structured literature review. \u003cem\u003eKnowledge Management Research \u003c/em\u003eand J\u003cem\u003ePractice, 20\u003c/em\u003e(2), 320\u0026ndash;338. https://doi.org/10.1080/14778238.2021.2015261\u003c/li\u003e\n\u003cli\u003eMoloi, T., and Salawu, M. K. (2022). Institutionalizing technologies in South African universities towards the Fourth Industrial Revolution. \u003cem\u003eInternational Journal of Emerging Technologies in Learning, 17\u003c/em\u003e, 204\u0026ndash;227.\u003c/li\u003e\n\u003cli\u003eNarong, D. K., and JHallinger, P. (2023). A keyword co-occurrence analysis of research on service learning: Conceptual foci and emerging research trends. \u003cem\u003eEducation Sciences.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eNgo Ndjama, J. D., and Van Der Westhuizen, J. (2023). Participative decision-making: Implications on organisational citizenship behaviour in a public higher education institution. \u003cem\u003eEUREKA: Social and Humanities\u003c/em\u003e(6), 24\u0026ndash;41. https://doi.org/10.21303/2504- 5571.2023.003259\u003c/li\u003e\n\u003cli\u003eOuma-Mugabe, J., Botha, A., and Letaba, P. (2024). Institutionalizing foresight in science, technology, and innovation in sub-Saharan Africa. \u003cem\u003eDevelopment Policy Review, \u003c/em\u003e42(S1), e12789. https://doi.org/10.1111/dpr.12789\u003c/li\u003e\n\u003cli\u003ePanakaje, N., Ur Rahiman, H., Parvin, S. M., P. S., K. M., Yatheen, and Irfana, S. (2024). Revolutionizing pedagogy: Navigating the integration of technology in higher education for teacher learning and performance enhancement. \u003cem\u003eCogent Education, 3\u003c/em\u003e, 23\u0026ndash;39.\u003c/li\u003e\n\u003cli\u003eQuarchioni, S., Paternostro, S., \u0026amp; Trovarelli, F. (2022). Knowledge management in higher education: A literature review and further research avenues. \u003cem\u003eKnowledge Management Research \u0026amp; Practice, 20\u003c/em\u003e(2), 304\u0026ndash;319. https://doi.org/10.1080/14778238.2020.1730717\u003c/li\u003e\n\u003cli\u003eSahibzada, U. F., Jianfeng, C., Latif, K. F., Shafait, Z., and Sahibzada, H. F. (2022). Interpreting the impact of knowledge management processes on organizational performance in Chinese higher education: Mediating role of knowledge worker productivity. \u003cem\u003eStudies in Higher Education, 47\u003c/em\u003e(4), 713\u0026ndash;730. https://doi.org/10.1080/03075079.2020.1793930\u003c/li\u003e\n\u003cli\u003eSaman, A. M., and Musa, K. B. (2023). Instructional coaching through technology integration: Accompanying teacher services in the digital era of Education 5.0. \u003cem\u003eInternational Journal of Social Science and Education Research Studies, 3\u003c/em\u003e, 34\u0026ndash;47.\u003c/li\u003e\n\u003cli\u003eTrianung, D. S. T., Sundari, W., Kurniawan, A., Setiawan, N. A., and Aisyah, J. (2024). Education management: Decision-making strategies in technology integration in the digital age. \u003cem\u003eAL- ISHLAH: Jurnal Pendidikan, 2\u003c/em\u003e, 34\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eYu, K., and Ismail, A. (2024). A bibliometric investigation of leadership and technology integration in education: Trends and insights over three decades. \u003cem\u003eMultidisciplinary Reviews, 2\u003c/em\u003e, 12\u0026ndash;27.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"strategic planning, digital transformation, higher education, human-centric models","lastPublishedDoi":"10.21203/rs.3.rs-7100705/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7100705/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the strategic narratives of university managers in South Africa, aimed at the acceptance of digital technologies to advance human-centric teaching and learning models. It examines fundamental gaps in grasping how collaborative networks, digital skill, and interdisciplinary systems influence institutional strategies. The questions aimed at examining the mechanisms of strategic planning, encouraging effect of interdisciplinary teamwork in initiating. The research integrates qualitative thematic and quantitative network analysis with results demonstrating three critical insights: localized relationship strengthens intra-group reliability but limits broader incorporation across departments; digital readiness advances equitable adoption, permitting interdisciplinary pathways, knowledge diffusion, driving developments in human-centric education strategies. These results articulate through pathways such as localized collaboration \u0026rarr; strong intra-group cohesion \u0026rarr; limited cross-departmental incorporation; as well as digital readiness \u0026rarr; equitable adoption \u0026rarr; sustainable innovation; and interdisciplinary pathways \u0026rarr; knowledge diffusion \u0026rarr; enhanced human-centric education strategies.\u003c/p\u003e","manuscriptTitle":"University Managers' Insights into Collaborative Networks and the Adoption of Digital Technologies for Human-Centric Teaching and Learning Models","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-13 11:26:06","doi":"10.21203/rs.3.rs-7100705/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8278d51f-1949-4207-aca5-4b6c0a8530de","owner":[],"postedDate":"August 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T12:11:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-13 11:26:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7100705","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7100705","identity":"rs-7100705","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}