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The Role Of Parental Support On Science Self-Efficacy Among Secondary School Students In Muranga, Kenya
No full textThe paper explored parental involvement factors that affect 498 secondary school students’ science self-efficacy in Murang’a County Kenya. The choice of determining future engagement in the science disciplines in the world of work rests on self-confidence in science. Inferential statistics were determined by pearson’s correlation coefficient, analysis of variance, and multiple linear regression analysis. The findings established instrumental assistance and verbal encouragement as positively influencing students’ science self-efficacy, career modeling had an insignificant effect while emotional support was found to have a negative relationship with students' science self-efficacy. The results reveal that the emotional status of students was a predictor of the development of confidence in science-related tasks
The Effect of Identified Social ICT Platforms on Prevalence of Conflicts in Kenya
No full textInformation Communication Technology contributes immensely to the world economy. In Developed countries, ICT innovations are utilized for safety, economic improvement and health while much is yet to be realized in developing countries. Africa has advanced in ICT though not clear on how it enhances the people’s wellbeing apart from positive and negative causes on moral value erosion and wars. This paper sought to establish the influence of identified ICT platforms on conflict prevalence in Kenya. Specifically, the study objectives were to establish the effect of Facebook communication and information flow on conflict prevalence, establish the information flow through WhatsApp on conflict prevalence, determine the influence of Twitter on conflict prevalence and establish the influence of Instagram on conflict prevalence in Kenya. Social exchange and innovation theories were adopted. The population of the study will entail the general public with a sample of 384 respondents sourced through media. Simple random sampling was employed to get the sample respondents. Questionnaires were formulated and sent online through the media and feedback analyzed with the aid of SPSS. Reliability of the instruments was ensured using Cronbach’s reliability technique while validity was checked using content validity methods. The findings revealed a reliability coefficient of 0.83 for the overall instruments implying that it was reliable. Pearson product moment correlation and multiple linear regression models were mingled with descriptive statistics to obtain meaningful associations and ratings. The findings were presented in tables. First, it emerged from the demographic characteristics that most of the respondents, 200(52.6%) were aged 51-60, 171(45.0%) were male and majority of professionals worked in NGOs. The findings revealed that ICT platforms (social media) accounted for an overall significant variance of 72.1% in conflict prevalence. Facebook (β=.333, p<.05), WhatsApp (β=.329, p<.05), Instagram (β=.278, p<.05) and Twitter (β=.225, p<.05) has a significant effect on Conflict prevalence in Kenya. It was concluded that the selected social media ICT platforms contributed significantly to conflict prevalence in Kenya. The findings may be helpful to stakeholders in the ICT, scholars and conflict sector in controlling disruptive innovations and managing conflicts
A Comparative Study of Deep Learning and Transfer Learning in Detection of Diabetic Retinopathy
No full textComputer vision has gained momentum in medical imaging tasks. Deep learning and Transfer learning are some of the approaches used in computer vision. The aim of this research was to do a comparative study of deep learning and transfer learning in the detection of diabetic retinopathy. To achieve this objective, experiments were conducted that involved training four state-ofthe-art neural network architectures namely; EfficientNetB0, DenseNet169, VGG16, and ResNet50. Deep learning involved training the architectures from scratch. Transfer learning involved using the architectures which are pre-trained using the ImageNet dataset and then fine-tuning them to solve the task at hand. The results show that transfer learning outperforms learning from scratch in all three models. VGG16 achieved the highest accuracy of 84.12% in transfer learning. Another notable finding is that transfer learning is able to not only achieve high accuracy with very few epochs but also starts higher than deep learning in the first epoch. This study has also demonstrated that in image processing tasks there are a lot of transferrable features since the ImageNet weights worked well in the Diabetic retinopathy detection task
The global spread of misinformation on spiders
No full textIn the internet era, the digital architecture that keeps us connected and informed may also amplify the spread of misinformation. This problem is gaining global attention, as evidence accumulates that misinformation may interfere with democratic processes and undermine collective responses to environmental and health crises1,2. In an increasingly polluted information ecosystem, understanding the factors underlying the generation and spread of misinformation is becoming a pressing scientific and societal challenge3. Here, we studied the global spread of (mis-)information on spiders using a high-resolution global database of online newspaper articles on spider–human interactions, covering stories of spider–human encounters and biting events published from 2010–20204. We found that 47% of articles contained errors and 43% were sensationalist. Moreover, we show that the flow of spider-related news occurs within a highly interconnected global network and provide evidence that sensationalism is a key factor underlying the spread of misinformation
Analysis of Demographic and Travel Characteristics of Domestic Tourists Visiting Coast Region, Kenya
No full textPurpose: With the increased tourism demand among domestic tourists in Kenya their travel needs for tourism products and services varies considerably due to their unique characteristics. The purpose of this study was to identify demographic and travel characteristics exhibited by domestic tourists in the Coast region of Kenya. Methodology: The study adopted explanatory research approach while cross-sectional survey design was used to collect quantitative data from domestic tourists’ visiting Coast region, Kenya. Simple random sampling technique was used to select respondents while data was collected using self-administered structured questionnaires and analyzed using descriptive and Chi-square techniques. Notably, 400 questionnaires were distributed of which 371 were successfully analyzed representing73.3% return rate.
Findings: It was found out that both demographic and travel characteristics significantly influence the final travel choice and purchase decisions among domestic tourist in Kenya. Subsequently, form the analysis demographic and travel characteristics are pivotal in forming basis for market segmentation, positioning and branding initiatives in a destination. The findings indicated that duration of current visit is dependent on annual income (ퟀ2=23.055, p=0.027), number of times visited is dependent on age (ퟀ2=30.579, p=0.015), while travel arrangement is dependent on age (ퟀ2=9.986, p=0.041). The mode of transport depended on age (ퟀ2=52.645, p=0.012) and mode of transport is dependent on education (ퟀ2=44.734, p=0.006).
Recommendations: Based on the findings, it is imperative for destination managers to focus on: identification and prioritization of preferred local appeal; avail market information based on travel needs of domestic tourists, and; constantly carry out periodical market surveys in order to address market dynamics for increased travel propensity for sustainability of the industry
Effect of on-the-Job Training Technique on Job Performance at Murang’a University of Technology in Kenya
No full textOn-the-job training of employees is a big challenge to employees and specifically those working in universities in Kenya. The main purpose of this study therefore, was to explore the effect of on-the job training on employee job satisfaction at Murang’a University of Technology. The results showed that on-the job training techniques have a great impact on employee job satisfaction. The study, recommends that: Universities should have an effective job rotation programme for all employees as it greatly affects their job satisfaction; University management should ensure that mentorship programmes have clearly set policies to effectively guide them for effectiveness; Induction should be institutionalized at the University as new employees view it as an opportunity to fit into the system easily, and understand their duties and responsibilities at work; and finally, Universities should have a well thought out coaching programme that will add value to its employee’s job satisfaction