Journals and Research Papers

How Do National Education Policies and Quality Assurance Frameworks Influence the Adoption, Governance, and Pedagogical Innovation of Online Teaching, Particularly in Relation to Assessment Practices, Accreditation Processes, and Academic Integrity?

2026-06-23T15:41:53Z

How Do National Education Policies and Quality Assurance Frameworks Influence the Adoption, Governance, and Pedagogical Innovation of Online Teaching, Particularly in Relation to Assessment Practices, Accreditation Processes, and Academic Integrity? Otieno, Robert Liston Omari; Otieno, Tabitha; Ngwudike, Benjamin C. The rapid institutionalization of online teaching has intensified debates about the role of national education policies and quality assurance (QA) frameworks in shaping educational quality, legitimacy, and innovation. While online teaching offers expanded access and pedagogical flexibility, its effectiveness is profoundly influenced by regulatory environments governing adoption, assessment, accreditation, and academic integrity. This study examines how national education policies and quality assurance frameworks influence the adoption, governance, and pedagogical innovation of online teaching, with particular attention to assessment practices, accreditation processes, and academic integrity. Drawing on a critical review of policy and quality assurance literature, the study analyzed how regulatory frameworks both enable and constrain institutional practices in digitally mediated learning environments. The analysis reveals persistent tensions between standardization and innovation, especially where quality assurance systems remain anchored in face-to-face teaching assumptions. Findings indicate that policy clarity and alignment with institutional capacity are essential for sustainable online teaching, while enhancement-oriented QA frameworks are more effective than compliance-driven models in supporting pedagogical innovation. The study further showed that surveillance-heavy approaches to assessment and academic integrity raise ethical concerns and may undermine trust and learning quality. The paper argues for adaptive, context-sensitive governance models that balance accountability with pedagogical flexibility. By foregrounding the interaction between policy intentions, quality assurance mechanisms, and institutional enactment, the study contributes to ongoing debates on the governance of online teaching and offers policy-relevant insights for strengthening quality, credibility, and innovation in digital higher education.

Adversarial Debiasing for Bias Mitigation in Healthcare AI Systems: A Literature Review

2026-06-23T15:17:49Z

Adversarial Debiasing for Bias Mitigation in Healthcare AI Systems: A Literature Review Waithira, Joshua; Chweya, Ruth; Ratemo, Makiya Cyprian The application of artificial intelligence (AI) in healthcare has tremendous potential for improving diagnostic precision and optimizing treatment and patient care. However, increasing dependence on such tools brings up urgent questions regarding the amplification of existing biases, which may detract from their ability to improve fair clinical decision-making. Adversarial debiasing, a method that utilizes fairness measures by contrasting a core predictive model with an adversarial network to reduce the influence of sensitive features, has emerged as an effective way of mitigating bias in AI systems. This review combines findings from 25 studies on several areas, encompassing the technical elements of adversarial learning and its practical applications in healthcare. The review offers extensive data and thoroughly assesses technological, ethical, and practical issues. This study reveals that adversarial debiasing improves fairness indicators and presents significant trade-offs, including reduced sensitivity and interpretability. We conclude with recommendations for future research avenues, encompassing prospective multicenter trials, adaptive training methodologies, hybrid debiasing strategies, and formulating standardized regulatory frameworks.

Distribution of organochlorine pesticides in macroinvertebrate functional feeding guild (FFG) of predators, Rhagovelia spp. in a tropical estuarine ecosystem

2026-06-23T15:13:53Z

Distribution of organochlorine pesticides in macroinvertebrate functional feeding guild (FFG) of predators, Rhagovelia spp. in a tropical estuarine ecosystem Nyakeya, Kobingi; Onchieku, James; Masese, Frank Onderi; Gichana, Zipporah Moraa; Nyamora, Jane Moraa; Getabu, Albert; Gitonga, Lydiah The current world population stands at approximately 8.5 billion people and this number is likely to shoot up in the coming decades. This increased trend in world population demands for sufficient food, which calls for, improved agricultural production systems. In order to achieve this, a tremendous in- crease in pesticide application of about 30-40% has been documented and this trend is predicted to increase in the coming years. Due to their negative impacts to the environment, some pesticides main- ly those of organochlorines (OCPs) have since been banned, but their residues can still be detected in different media causing deleterious effects on organisms. The aim of this study, therefore, was to assess the distribution of organochlorine pesticides (OCPs) by aquatic macroinvertebrates FFG of Rhagovelia spp. in the tropical estuarine ecosystems of South Coast, Kenya. Twelve sampling stations were purpo- sively identified taking into considerations different hydrological and ecological factors. Rhagovelia spp. were sampled using established methods and analysis for OCPs detection were performed using a TSQ Vantage Triple-Stage Quadrupole Mass Spectrophotometer (Thermo Electron) equipped with a heat- ed electrospray ionization probe (HESI-II). Separation, detection, identification and quantification of tar- get analyses followed the same established methods. Sixteen OCPs were recorded in Rhagovelia spp. samples collected from all the 12 sampling stations. γ-HCH was the lowest (2.74 0.18 ng g-1 dw) recorded concentration value for OCPs from Rhagovelia species samples whereas OCPs Cis_chlordan, mirex, p,p’_DDT, p,p’_DDE, o,p’_DDE and HCH recorded 10.09 0.35 ng g-1 dw, being the highest registered value. Analysis of variance (ANOVA) on the mean concentration residues of OCPs in Rhagovelia spp. samples yielded a significant variation among the sampled stations (F = 77.79, df = 11, p < 2.2e-16). The statistical analysis revealed that each station played a crucial role in determining the levels of OCPs in Rhagove- lia spp. due to environmental factors, early life history strategies of the tested bioassay organism, and different sources of OCPs as influenced by anthropogenic activities. The study recommends for the application of macroinvertebrate FFG of Rhagovelia spp. in biomonitoring of estuarian eco- systems. The study also recommends the use of different FFGs of macroinvertebrates such as grazers, collector-gatherers, filterers and shredders in order to bring out the general behavior of these pesticides along the food web.

Analyzing Spatial-temporal Variation in Water Quality Parameters in South Coast Estuarine Ecosystem, Kenya

2026-06-23T14:34:11Z

Analyzing Spatial-temporal Variation in Water Quality Parameters in South Coast Estuarine Ecosystem, Kenya Nyakeya, Kobingi; Onchieku, James; Masese, Frank; Gichana, Zipporah; Getabu, Albert; Nyamora, Jane Estuarine ecosystems are classified as among the most productive systems on the planet earth supporting an array of biodiversity. However, due to the ever increasing human population, they experience environmental degradation originating from intensive anthropogenic activities hence the need for regular assessment and monitoring to inform its management. The purpose of this study, Original Research Article Nyakeya et al.; Int. J. Environ. Clim. Change, vol. 14, no. 10, pp. 46-57, 2024; Article no.IJECC.121848 47 therefore, was to analyze the spatio-temporal variation in water quality parameters in South Coast estuarine ecosystem, Kenya. Twelve sampling stations were identified based on different hydrological regimes, anthropogenic activities, and accessibility factors. Sampling was done for 12 months taking into account different seasons of the year. Such parameters as temperature, dissolved oxygen, pH, conductivity, salinity and TDS were collected in situ using YSI Multiparameter meter (Professional plus) whereas nutrients (nitrates, phosphates and ammonia) were analyzed in the laboratory using established methods. Two-way analysis of variance (ANOVA) was applied to discriminate any significant differences among stations and between seasons, and where there was a difference, Tukey post hoc test was applied to show which site differed from each other. Principal Component Analysis (PCA) was performed to correlate the environmental factors with sampling sites, and months. There was significant difference in water quality parameters among the sampling stations (P = .05) that was attributed mainly to anthropogenic activities, and both the point and non- point sources of pollution. Conversely, there was no significant difference in most of the water quality attributes in terms of seasons due to unpredictable weather patterns associated with climate change. There is need for long term monitoring strategies in order to generate sufficient data for sound management of South Coast estuary in Kenya. The study further recommends for community sensitization and implementation of relevant policies on the protection and management of riparian land.