ABSTRACT
The continued predicament of ill-fitting ready-to-wear (RTW) children clothing spoils consumer satisfaction and confidence in the market in Kenya. Parents of children between two and six years of age are used to incongruent sizing, mismatch of garments between labels of age and actual body size, and lack of locally tested size standards. The paper discusses the aspects of apparel sizing and fit among children aged two to six years in Kisumu, Nakuru, and Nairobi, Kenya. A mixed-methods research design was used based on a combined needs theory of clothing (Dunlap, 1928) and used 385 children, 100 parents, and 21 clothing industry professionals. Data collection was done through questionnaires, structured interviews, and focus group discussions and analysed via descriptive and inferential statistics. Findings showed that the most important factors in making RTW buying choices were clothing quality and durability (65%), correct sizing and fit (58%), and informed clothing choice (55%). The prevalent sizing strategy (69 percent) was physical fitting at the point of sale, which reflects the lack of a credible national standard. Sizing on the basis of age labeling was generally unsatisfactory. Problems such as variation in the size of the brands, low quality of garment work, and limited variety in the market were experienced by 80% of the respondents. The paper suggests the establishment and use of an anthropometric size chart of children clothing that is approved by Kenya Bureau of Standards (KEBS) to facilitate the Kenyan children wear industry that is increasingly on the rise. These results offer a critical basis on the design of standardised, evidence-based sizing schemes that are specific to Kenya apparel market, and have the potential to curb consumer dissatisfaction, garment returns, and enhance the competitiveness of children clothing produced in Kenya.

ABSTRACT
This study examined the use of the 5E instructional model in teaching redox reactions and its association with high school students’ problem-solving competence (PSC). A quasi-experimental design was employed involving an experimental group (n = 48) and a control group (n = 50) at a Vietnamese high school. Data were collected through achievement tests, a PSC rubric, classroom observations, and student self-assessment questionnaires. The results showed that the experimental group obtained higher post-test scores and demonstrated a more favorable score distribution compared to the control group. However, the experimental group also exhibited higher baseline performance in the pre-test, indicating that the groups were not fully equivalent at the outset. The calculated effect size (Cohen’s d = 0.89) suggests a substantial between-group difference in post-test performance, although this should be interpreted cautiously due to baseline differences. In addition, the experimental group showed higher scores across key dimensions of PSC, including analysis, planning, implementation, evaluation, and reflection, as well as a higher overall PSC composite score. A significant positive correlation was found between teacher evaluations and student self-assessments (r = 0.71, p < 0.001). Overall, the findings indicate that the 5E instructional model was associated with more favorable learning outcomes in this context, but no causal inference can be made.

ABSTRACT
This bibliometric study examines the overall research trends and productivity of Artificial Intelligence in self-directed learning, based on published articles (2005-2025). Initially, we identified 1,801 studies from the Scopus database using the search string ("Artificial Intelligence" OR "AI") AND ("Self-directed Learning" OR "Self-learning"). Finally, we selected 219 articles for analysis after filtering by articles, Conference papers, and reviews within social science, psychology, multidisciplinary, and arts and humanities subjects. Utilizing VOS viewer software, we observed that most studies (38.2%) were in the social science subject area, and China is the dominant contributor, followed by the USA and Germany. Colby College (n = 4 articles) is the leading institution by the number of documents, followed by the University of Oxford and Indiana University Bloomington. Feldmann J., Youngblood N., Wright C.D., Bhaskaran H., and Pernice W. are the most influential authors based on citations. The United Kingdom is the leading country, followed by Germany and South Korea, according to citation counts. The leading source is “Sustainability Switzerland” (n = 7 articles), but the most cited journal in the context of citations is “Nature”. The article “All-optical spiking neurosynaptic networks with self-learning capabilities” by Feldmann et al., (2019) was highly cited (1072). Ogata H., Flanagan B., Majumdar R., Li H., Hwang G.J., Yang Y., Chen X., Liu Y., Zhang J., and Wang Y. are the most frequently co-cited in artificial intelligence research on self-directed learning. In the co-author analysis, the USA is the most collaborative country, followed by the UK and China. “Artificial Intelligence”, “Machine Learning”, “Learning Systems”, “Self-directed Learning”, and “ChatGPT” were the most common co-occurrences among the authors' keywords. The primary theme, based on the author’s keywords, is "Artificial Intelligence and Neural Learning for Sustainable Optimisation". This

ABSTRACT
This paper examined the potential of Canva as an emerging instructional technology capable of fostering innovative learning practices in Nigerian universities. The growing demand for digitally mediated and student-centred learning environments has necessitated the exploration of accessible technological tools that can enhance creativity, engagement, and knowledge construction among university students. Against the backdrop of persistent reliance on traditional lecture-centred pedagogy in many higher education institutions, the paper argues that the integration of Canva offers a practical pathway for transforming instructional practices and supporting the development of twenty-first-century skills. Drawing on contemporary literature on educational technology and innovative pedagogy, the paper conceptualises innovative learning within higher education and examines the instructional features of Canva that make it suitable for academic environments. Particular attention is given to its capacity to promote visual literacy, collaborative learning, creative knowledge representation, and improved student engagement through multimodal instructional design. The discussion also identifies key contextual challenges that may hinder the effective adoption of such technologies in Nigerian universities, including inadequate digital infrastructure, limited digital pedagogical competence among lecturers, and issues related to technological accessibility and academic rigour. To address these concerns, the paper proposes strategic institutional approaches involving curriculum integration, professional development for lecturers, infrastructural investment, and supportive educational policies that encourage technology-enhanced learning environments. It concludes that while Canva alone cannot resolve systemic pedagogical challenges within higher education, its deliberate and structured incorporation into teaching practices can significantly contribute to the modernisation of university pe

ABSTRACT
The inclusion of digital technology in the teaching and learning process of Spanish as a Foreign Language is presented as the beginning of a deeper transformation process that should take into account the environment and social inequalities in order to continue reinventing itself and fulfilling its mission of preparing future generations for an uncertain and changing world. To succeed in digitization in rural areas, the main stakeholders in the teaching and learning of Spanish as a Foreign Language, in collaboration with the authorities, should develop transformation models and methodologies adapted to the rural environment and realities. A policy should be implemented that specifically addresses the appropriate and timely digitization of the teaching and learning of Spanish as a Foreign Language. The objective of this work is to investigate the digitization of the teaching and learning of Spanish as a Foreign Language as a sociocultural experience, emphasizing the inequalities and disconnections in the appropriation of new information and communication technologies by the actors within digital inclusion. The mixed-methods research methodology employed in this study offers a design that incorporates both quantitative and qualitative data. Data was collected from two hundred students and twenty teachers using a survey technique. The results were analyzed and interpreted using figures and diagrams, yielding a 100% response rate. Based on these findings, it is essential to establish a culture of innovation, commitment, and resilience that integrates sociocultural elements from rural areas to ensure the success of digital transformation.

ABSTRACT
TPACK, or ‘Technological Pedagogical Content Knowledge’, is a model that describes the knowledge teachers need to integrate technology into their teaching. This study is all about the technological pedagogical content knowledge of preservice teachers who studied at various private and government colleges in West Bengal. For this study, a total of 189 preservice teachers from various private and government institutions were used. The primary goal of this research is to determine the extent to which preservice teachers incorporate pedagogical technological content knowledge into their teaching. The research findings indicate that students from government institutions possess a higher level of technological pedagogical content knowledge compared to those from private institutions. Additionally, their choice of stream significantly influences TPACK, while other socio-demographic variables do not have a significant impact.

ABSTRACT
Education and awareness are essential to promoting ethics and transparency in artificial intelligence (AI). They enable users, developers, and decision-makers to understand key issues related to AI, such as algorithmic biases, data protection, and automated decision-making. The objective of this study is to highlight the importance of education and awareness for the responsible use of intelligent technologies related to AI. A reflective and critical approach is adopted as the methodological framework, given the extensive discourse on the sociocultural representations surrounding the substitution of human actions with AI. Data collected is subjected to triangulation and analyzed using Bardin’s content analysis method. The findings reveal that robust education equips individuals to question and manage the social impacts of these technologies. Transparency in decision-making processes fosters public trust and ensures greater accountability among stakeholders. Awareness of AI's societal responsibility promotes fair, equitable, and beneficial use for all.