Open educational resources promise cost relief for students in technical colleges, yet faculty report hidden time costs during search, adaptation, and quality verification. This policy-oriented analysis models how institutions can allocate release hours, library support, and instructional design assistance to reduce individual burden. It compares department-wide adoptions with instructor-led customization pathways and discusses sustainability when grant funding ends. Recommendations include shared repositories curated by discipline teams and clear attribution standards compatible with accreditation reviews in applied science and engineering programs.

Rural clinical placements offer authentic patient contact but may limit opportunities for structured interprofessional teamwork rehearsals. This article reviews low-fidelity and hybrid simulation models that prepare nursing, pharmacy, and medical students for collaborative handoffs, medication reconciliation, and shared decision conversations. Logistical guidance covers portable equipment kits, tele-simulation debriefing, and scheduling across programs with different rotation calendars. Outcome indicators include team communication scores and student confidence measures collected before and after intensive simulation weeks embedded in rural clerkships.

Students encounter historical claims through textbooks, documentaries, and social media feeds that blur primary and secondary source boundaries. This curriculum essay proposes instructional progressions for upper secondary history that integrate traditional archive work with contemporary credibility heuristics. Lessons move from corroboration and contextualization tasks toward structured evaluation of digital artifacts including manipulated images and anonymous posts. Assessment rubrics reward transparent reasoning about provenance and perspective rather than memorization of narrative summaries alone.

Graduate programs increasingly expect students to conduct research with community partners, but formal training in participatory methods remains uneven. This methodological essay describes a seminar sequence covering power mapping, co-design of research questions, benefit-sharing agreements, and reflexive field journaling. It argues that mentorship structures should include community liaisons alongside faculty advisors and that IRB protocols must accommodate iterative consent in long-term partnerships. The framework targets social science departments seeking to embed ethical engagement without treating communities as extractive data sources.

Standardized testing formats can inadvertently disadvantage students with sensory processing differences even when content knowledge is intact. This article synthesizes universal design for learning principles applied to assessment environments, including flexible timing, reduced sensory load, alternative response modes, and advance familiarization with task formats. Case vignettes illustrate how multidisciplinary teams coordinate occupational therapy insights with classroom accommodations. Ethical and legal considerations around equitable grading and documentation for certification pathways are addressed for school administrators and assessment coordinators.

Continuing professional development for practicing nurses must fit irregular schedules and varying baseline knowledge. This practice paper outlines gamified microlearning modules delivered through short mobile sessions with spaced repetition and scenario-based quizzes. Design principles emphasize clinical relevance, immediate feedback, and optional social leaderboards that do not penalize slower learners. The article discusses alignment with competency frameworks, accreditation documentation, and strategies for evaluating knowledge retention three months after module completion in hospital-affiliated programs.

Translanguaging policies invite teachers to leverage students' full linguistic repertoires, yet classroom practice often lags behind official guidance. This conceptual review traces how teacher beliefs about language purity, assessment fairness, and parental expectations evolve through structured professional learning communities. The analysis highlights micro-interactional moves such as strategic code-switching, parallel text displays, and peer translation routines that support comprehension without lowering academic rigor. Recommendations address school leadership support and portfolio-based documentation of emergent bilingual growth across subject areas.

Large lecture courses often provide limited feedback loops for students who struggle to monitor their own progress. This design-oriented article examines how adaptive learning analytics dashboards can surface timely indicators of engagement, quiz performance, and study pacing without overwhelming users. Drawing on self-regulated learning frameworks, it proposes dashboard layouts that emphasize actionable next steps rather than raw scores. Implementation considerations include data privacy, instructor training, and integration with existing learning management systems in introductory university settings.

When products become increasingly complex in form and functionality, the stylistic design process becomes highly time-consuming. This paper investigates the relationship between design complexity and the decision-making process that designers use in their design practices when selecting either GenAI or conventional CAD systems at the very early stages of product design development. A hybrid workflow strategy that merges GenAI and CAD systems in design processes has been proposed with the aim of unlocking designers\' full creative potential whilst maintaining accuracy of product data. This paper reports on how styling students utilize digital tools during their design activities. A case-study approach was utilized to experiment with 36 advanced undergraduate students. Two styling briefs of different complexity levels were developed to observe how students select digital tools to aid their design tasks, and to measure their resulting designs and outcomes. Students’ perceptions of using the tools were also evaluated to gain deeper insights. The results demonstrated that all students assigned to the high styling complexity motorcycle brief used GenAI for their styling task within a strict 90-minute timeframe, and in often diverse ways. For the lower styling complexity high-speed train brief, however, students divided their task and used CAD and GenAI separately. The results indicate that CAD was used when dimensional control and manipulable geometry were required during the idea generation process; and when design ideas needed to be converged for refinement and produced with accurate dimensions and a completed model ready for display within a tight timeframe. In contrast, GenAI was found to be more effective in rapidly generating ideas for highly complex aesthetic design problems. Through the examination of the current problems in design ideation, this research identifies opportunities for improvement in Hybrid GenAI–CAD based workflows for product design. The paper outlines a two-stage design workflow based around Divergent GenAI generated ideas for stylistic exploration and a Convergent CAD design approach that results in a dimensionally controlled, manufacturable solution. At the point of handover key decisions are made thus the paper presents pedagogical and industrial solutions to prevent transition loss; training GenAI in CAD, the selection of design tools based on project characteristics, handover protocols, and the use of interoperable (editable AI-to-CAD) sources to reduce time-to-market whilst ensuring quality designs.

This study aimed to adapt the Negative Core Beliefs Inventory (NCBI) into Turkish and to examine its psychometric properties within a university student sample in Cyprus. Negative core beliefs are fundamental cognitive schemas that shape individuals’ interpretations of themselves and others and play a critical role in psychological vulnerability according to cognitive theory. The study was conducted as a methodological scale adaptation research within a quantitative framework. A total of 400 participants were included in the exploratory analyses, while an independent sample of 250 participants was used for confirmatory factor analysis. The adaptation process followed international guidelines for cross-cultural scale adaptation using forward–backward translation, expert evaluation, and pilot testing. Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), reliability analyses, and Item Response Theory (IRT) models were applied. EFA revealed a four-factor structure: Worthlessness/Inadequacy, Distrust of Others, Helplessness/Vulnerability, and Self-Inadequacy. Confirmatory factor analysis supported the structure with acceptable model fit indices (χ²(371) = 1132.203, CFI = .868, TLI = .856, RMSEA = .072, SRMR = .054). Reliability analyses indicated high internal consistency for the overall scale (α=.94). Item Response Theory analyses using the Graded Response Model showed adequate discrimination parameters and strong measurement precision, particularly for the Worthlessness/Inadequacy and Helplessness/Vulnerability subscales. The findings indicate that the Turkish version of the Negative Core Beliefs Inventory is a reliable and valid instrument for assessing negative core beliefs in Turkish cultural contexts. The scale can contribute to both psychological research and clinical assessment by providing a culturally sensitive tool for measuring maladaptive cognitive schemas.

Effective organisational leadership remains a critical determinant of sustainable service delivery within South Africa’s local government sphere, particularly in Mpumalanga Province’s municipalities. Persistent governance failures, administrative instability, financial mismanagement, political interference, and declining public trust continue to undermine municipalities’ ability to deliver essential services efficiently and equitably. This literature review critically examines the relationship between organisational leadership and municipal service delivery, with particular emphasis on the leadership challenges facing local municipalities in Mpumalanga Province. The study draws on contemporary scholarly literature, government reports, policy documents, and institutional publications from sources such as the South African Local Government Association (SALGA), the Local Government Sector Education and Training Authority (LGSETA), National Treasury, and the Auditor-General South Africa. A qualitative desktop research methodology was employed to analyse literature published primarily within the last decade. The review identifies several leadership deficiencies affecting municipal performance, including inadequate strategic leadership capacity, weak accountability systems, political-administrative interference, ineffective communication, limited stakeholder engagement, poor financial management, and insufficient leadership development initiatives. The findings further reveal that ineffective leadership contributes significantly to service delivery protests, community dissatisfaction, governance instability, and institutional decline within municipalities. The study argues that strengthening leadership competencies, promoting ethical governance, enhancing accountability mechanisms, and fostering participatory governance are essential for improving municipal performance and developmental outcomes. The article contributes to ongoing debates on local governance reform by proposing leadership-centred interventions to improve service delivery effectiveness and restore public confidence in Mpumalanga municipalities.

Advances in artificial intelligence (AI), has created the need for AI based risk detection. This is a rapidly developing area of study in terms of ensuring the safety and security of areas including Cybersecurity, Surveillance Systems, and Critical Infrastructure Protection. The authors of this article describe their approach to designing and evaluating an intelligent threat detection framework designed to identify and detect threats in near real-time by analyzing behaviors, patterns, and anomaly trends found within vast amounts of complex data streams. The proposed model will be trained on a large amount of varied data sets, which include both malicious and benign activities. Therefore, it will allow for a strong distinction between \"normal\" behavior and actual threats, along with reduced false positives. The proposed model includes Advanced Data Preprocessing, Feature Representation, Deep Learning Architectures, Scalability, Adaptability to evolving attack strategies, and Automated Learning so that the system continues to learn and adjust its boundary for making decisions regarding future data and emerging threats. Experimental results show the proposed model had superior detection accuracy compared to other models tested under various types of attacks. Additionally, experimental results indicated that the proposed model was able to operate effectively when presented with noisy and imbalanced data. Further testing on the model demonstrated its ability to identify potential threats quickly enough to allow prevention or mitigation of loss in real-time based security applications. Studies were also performed comparing the performance of the model with both traditional rule-based systems and other forms of machine learning models. The comparisons indicated better performance metrics (i.e., precision, recall) than the traditional models and improved threat detection efficiency. As such, these results support the idea that AI enabled risk detection capabilities will help move current security architectures from passive protection mechanisms toward active defensive systems and decrease the reliance on user input while increasing the level of informed decisions. In total, the study presents an approachable, scalable, automatic method for managing intelligent threats through automation and further reinforces the importance of using AI as part of a security system’s foundation.

This article presents a comprehensive analysis of scholarly publications, international practices, and empirical data reflecting the potential, implementation models, and barriers associated with the use of MOOCs in the professional training of future teachers. The methodological framework is based on a systematic review of English- and Russian-language sources published between 2010 and 2025, including the selection of peer-reviewed literature, thematic coding, and conceptual interpretation of key areas such as digital literacy, constructivist and connectivist learning theories, the TPACK and SAMR models, blended learning, and the internationalization of educational trajectories.
The main findings demonstrate that MOOCs have considerable potential in fostering professional and digital competencies, supporting the development of self-directed learning strategies, and engaging pre-service teachers in global communities of practice. The article provides concrete examples of MOOC integration in universities across Russia, Kazakhstan, Europe, Latin America, and the Middle East. However, the analysis also reveals a number of limitations, including low course completion rates, lack of motivation, language barriers, digital inequality, and insufficient pedagogical support.

Teacher motivation is vital to maintaining educational quality, especially during times of change. This qualitative study examined how educational reform influences motivation among 12 teachers and 4 principals in South Africa. Guided by Self-Determination Theory, semi-structured interviews and thematic analysis were used to explore key aspects relating to teacher motivation. Findings revealed certain intrinsic and extrinsic factors have a significant influence on teacher motivation. It is crucial that school leaders take cognisance of these factors as demotivated teachers can have a profound and far-reaching influence on the overall effectiveness of education reform. The study offers practical recommendations for school leaders, with broader implications for global education systems undergoing reform.

The GCC countries are enhancing their succulency with innovative technologies, investing in new services for citizens, and focusing on strategic innovations. Among developing technologies, cryptocurrencies and blockchain are some of the most powerful capable of augmenting and enhancing socioeconomic systems supporting development. This research analyzes how trading major cryptocurrencies, Bitcoin, Ethereum, Ripple, and Litecoin influence the digital economies of these six GCC countries: KSA, UAE, Bahrain, Kuwait, Qatar and Oman. Using samples of 575 respondents across these countries, the research demonstrates strong positive correlation between cryptocurrency participation and the development of resilient economies. Key contributing factors are user trust, accessibility, knowledge, and public acceptance. This research emphasizes the need to encourage active investment in establishing a cryptocurrency framework that is flexible yet mitigates the risks peripheral to unregulated assets. Further suggested policy actions focus on boosted digital onboarding, clearer regulation policies, and more integrated digital infrastructures to ensure that cryptocurrency is adopted in an inclusive way that enhances economic development across the GCC. This is very helpful for those intending to use cryptocurrency outside of traditional markets for setting strategies toward strengthening national enduring and developmental resilience.

#FeesMustFall was a movement which became a critical rupture in South Africa\'s post, apartheid higher education landscape, revealing inequalities to do with access, funding, epistemic exclusion and institutional power that are still persistent. Bonginkosi Khanyile was one of the most prominent voices of the movement and his radical activism gave the most confrontational critique of neoliberal governance, coloniality and the commodification education. This study examined the point of view of Khanyile on #FeesMustFall by analysing the discourse of Khanyile regarding the starting point of the movement, its objectives and its political significance. Basing the argumentation on Decolonial Theory, Critical Political Economy and Social Movement Theory, the study made use of qualitative document and discourse analyses of Khanyile\'s public speeches, interviews, court statements, and media interactions during 2015 to 2018. The results showed three interconnected themes. Firstly, it is the idea of tuition fees as a type of structural violence that sustains racialised and class, based exclusion. Secondly, it is the university as a contested colonial space that refuses transformation conceptually. Thirdly, it is student activism as a revolutionary citizenship that challenges the limits of liberal democratic protest politically and in practice. This paper argues that Khanyile’s viewpoint stretches #FeesMustFall beyond just a struggle for reduced tuition fees to a more general decolonial and political project that questions the unfinished nature of post, apartheid transformation. This paper shows how activist knowledge gets produced in the scholarship debates concerning student movements, decolonisation and higher education reform in South Africa.