Journal of Technology Innovations and Energy

Digital Competence as Predictor for the Motivation to Use Artificial Intelligence Technologies among Librarians in Edo and Delta States, Nigeria

Nosakhare Okuonghae — 2024-01-13

Motivation to use artificial intelligence (AI) technologies are those factors that influenced users’ drive to actually use AI technologies. There are various AI technologies that librarians can adopt to improve their service functions. However, studies have shown that the use of AI among librarians is low. It is in the light of this that this study therefore investigated the motivation to use AI technologies among librarians in Edo and Delta States. Descriptive survey research design was adopted. The population consist of 125 librarians selected from 18 Universities in Edo and Delta States, Nigeria. Total enumeration technique was adopted because of the manageable size of the population. A validated questionnaire was used to collect data from the respondents. Data collected was analysed using both inferential and descriptive statistics. Finding revealed that digital competence (Adj. R² = 0.195, p = 0.000^b) has significant but weak influence on motivation to use AI technologies among librarians. The study concluded that digital competence influenced motivation to use AI technologies. The study recommended that there should be more awareness of AI among librarians. At the same time, librarians should improve their digital skill through regular training programs so that they can effectively use AI tools.

On Modification of Some Estimators using Parameters of Auxiliary Information for the Estimation of the Population Coefficient of Variation

Awwal Adejumobi — 2024-02-05

Several studies in the theory of sampling survey have established the fact that the use of auxiliary information at the planning and estimation stages helps in enhancing the efficiency of estimators for estimating population parameters like population mean, population variance, standard deviation etc. as compared to the estimators which use not auxiliary information. In the present study, four estimators for estimating the population coefficient of variation of the study variable using auxiliary information were proposed. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of approximation using Taylor series approach. Numerical analysis was conducted to justify the efficiencies of the proposed estimators and the results revealed that the proposed estimators are more efficient than the existing estimators considered in the study.

Teacher Education for National Development Using Google Meet: Issues and Prospects

Fadele Ayotunde Alaba — 2024-02-17

This research examines the role of teacher education in Nigeria’s national development using Google Meet, a virtual learning platform. The study assesses the effectiveness of Google Meet in enhancing educators’ professional development and impacting student learning outcomes. It also investigates the challenges and limitations of implementing virtual teacher training in Nigeria. The findings show that Google Meet can improve education quality and foster professional growth. However, internet connectivity and digital infrastructure challenges hinder widespread adoption, especially in rural areas. The research proposes recommendations for optimizing Google Meet in teacher education, such as providing equitable access to digital resources, investing in robust internet connectivity, and implementing ongoing training for educators. This study offers insights for education policymakers and institutions in Nigeria and other developing countries seeking to leverage technology for teacher education and national development. Aligning teacher training with digital innovations can enhance educational outcomes, foster sustainable development, and prepare citizens for a rapidly evolving global landscape

Performance Assessment of Affordable Solar Dehydrator for Sustainable Energy

Tanveeruz Zaman — 2024-03-18

Dehydration has long been the preferred method of food preservation over all other techniques. In contrast to other techniques, dehydration uses heat to evaporate extra water from food. This can be simply obtained through solar energy. This work aims to apply appropriate engineering methods to use solar energy for food dehydration efficiently. This work prioritizes both food quality and cost equally. In addition, it features a backup system that operates at night to continuously dehydrate food items with drying times longer than 12 hours, in contrast to previous approaches that are either costly or result in lower-quality products. So, the solar collector is designed at an optimum angle of 27ᵒ with an area of 0.5153 m² to collect useful heat from the sun that develops enough temperature difference to dehydrate some selected food. Experiment results show that the desired purpose is greatly achieved by comparing the dehydrated products with the conventional or commercially available products.