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Effect of Agripreneurship on Employment and Income Generation in Cattle Fattening Business in Nigeria Texte intégral
2019
Obayelu, Abiodun Elijah | Olaniyi, Ajibola | Ogbe, Agatha
Effect of Agripreneurship on Employment and Income Generation in Cattle Fattening Business in Nigeria Texte intégral
2019
Obayelu, Abiodun Elijah | Olaniyi, Ajibola | Ogbe, Agatha
Unemployment is a major issue in Nigeria because the youth finds it difficult or impossible to secure jobs that meet their expectations. There appears to be a mismatch between graduate skills and those sought by employers. The study investigated the effect of International Institute of Tropical Agriculture (IITA) youth Agripreneurs (IYA) programme on employment and income generation on cattle fattening enterprise under the N2Africa Borno youth project. A two-stage sampling procedure was used to select IYA participants and non-participants. Results revealed that the majority of respondents were males in both categories. It also indicated that youths who are in their productive age are more into cattle fattening enterprise in both categories. The study also found that, unemployment and skill acquisition are the main driving reasons for participating in IYA. It also indicated that both categories of respondents’ required external capital support for start-up of their enterprise, and that IYA programme participants on the average earn more income per month than non-participants. IYA programme participants generated more employment opportunities which implied that the programme had not only empowered participants but also made the participants’ become employers. The study recommended that there is a need to support youths with funds, access to trainings on capacity development and skill acquisition to make them self-employed and job creators.
Afficher plus [+] Moins [-]Effect of agripreneurship on employment and income generation in cattle fattening business in Nigeria Texte intégral
2019
Obayelu, A.E., Federal Univ. of Agriculture, Abeokuta (Nigeria) | Olaniyi, A., Nigeria Youth Agripreneurs Unit, Ibadan (Nigeria) | Ogbe, A., Federal Univ. of Agriculture, Abeokuta (Nigeria)
Unemployment is a major issue in Nigeria because the youth finds it difficult or impossible to secure jobs that meet their expectations. There appears to be a mismatch between graduate skills and those sought by employers. The study investigated the effect of International Institute of Tropical Agriculture (IITA) youth Agripreneurs (IYA) programme on employment and income generation on cattle fattening enterprise under the N2Africa Borno youth project. A two-stage sampling procedure was used to select IYA participants and non-participants. Results revealed that the majority of respondents were males in both categories. It also indicated that youths who are in their productive age are more into cattle fattening enterprise in both categories. The study also found that, unemployment and skill acquisition are the main driving reasons for participating in IYA. It also indicated that both categories of respondents’ required external capital support for start-up of their enterprise, and that IYA programme participants on the average earn more income per month than nonparticipants. IYA programme participants generated more employment opportunities which implied that the programme had not only empowered participants but also made the participants’ become employers. The study recommended that there is a need to support youths with funds, access to trainings on capacity development and skill acquisition to make them self-employed and job creators.
Afficher plus [+] Moins [-]A Constructivist Approach to the Teaching of Mathematics to Boost Competences Needed for Sustainable Development Texte intégral
2018
Vintere, Anna
A Constructivist Approach to the Teaching of Mathematics to Boost Competences Needed for Sustainable Development Texte intégral
2018
Vintere, Anna
The constructivist approach is based on the idea that knowledge can never be passed from one person to another. The only way to acquire knowledge is to create or construct them. The constructivist approach changes also the role of the teacher in the educational process, the task of them is to organize the environment so that the student himself can construct the cognitive forms that teacher wants to give him. In the paper, the nature of the constructivist approach is identified, different aspects regarding mathematics education are analysed as well as the potential impact on the development of mathematical competences in the context of sustainable development is discussed. The study process and learning methods appropriate to constructivist approach also were studied. In order to illustrate the need for a constructivist approach in mathematics education, the survey of students from Latvia University of Life Science and Technologies (LLU) and Riga Technical University (RTU) were carried out, the results of which proved that mathematics learning at universities has to be changed. The current study proved that the constructivist approach radically changes the process of teaching and learning mathematics, connecting it with daily life, rather than teaching only abstract formulas and using a creative approach to mathematical tasks solving. This study shows that using constructivist approach to the teaching of mathematics, the competences needed for sustainable development are boosted.
Afficher plus [+] Moins [-]A constructivist approach to the teaching of mathematics to boost competences needed for sustainable development Texte intégral
2018
Vintere, A., Latvia Univ. of Life Sciences and Technologies, Jelgava (Latvia)
The constructivist approach is based on the idea that knowledge can never be passed from one person to another. The only way to acquire knowledge is to create or construct them. The constructivist approach changes also the role of the teacher in the educational process, the task of them is to organize the environment so that the student himself can construct the cognitive forms that teacher wants to give him. In the paper, the nature of the constructivist approach is identified, different aspects regarding mathematics education are analysed as well as the potential impact on the development of mathematical competences in the context of sustainable development is discussed. The study process and learning methods appropriate to constructivist approach also were studied. In order to illustrate the need for a constructivist approach in mathematics education, the survey of students from Latvia University of Life Science and Technologies (LLU) and Riga Technical University (RTU) were carried out, the results of which proved that mathematics learning at universities has to be changed. The current study proved that the constructivist approach radically changes the process of teaching and learning mathematics, connecting it with daily life, rather than teaching only abstract formulas and using a creative approach to mathematical tasks solving. This study shows that using constructivist approach to the teaching of mathematics, the competences needed for sustainable development are boosted.
Afficher plus [+] Moins [-]Integrating reflective practice into the self-improvement cycle module for renewable energy forecasting accuracy Texte intégral
2024
Veigners, Girts | Galins, Ainars | Dukulis, Ilmars | Veignere, Elizabete
The increasing reliance on renewable energy sources such as solar and wind power necessitates the development of advanced forecasting techniques to address the inherent variability and unpredictability of these energy systems. Accurate forecasting is vital for optimising energy production, maintaining grid stability, and effectively integrating renewable energy into power systems. Traditional forecasting methods often struggle to adapt to rapidly changing environmental conditions and new data inputs, limiting their effectiveness in dynamic contexts. This study introduces the Self-Improvement Cycle (SIC) module, which is designed to enhance forecasting accuracy through continuous learning, adaptation, and feedback integration. The SIC module leverages advanced machine learning algorithms, reinforcement learning techniques, and reflective practice principles to create a self-improving framework that dynamically updates models based on real-time data and external feedback. The module’s design incorporates multiple feedback loops, enabling the system to iteratively refine its performance and remain robust in the face of changing conditions. Reflective practice, a concept drawn from psychology, plays a critical role in the SIC module by facilitating ongoing evaluation and adaptation. By learning from previous predictions and continuously adjusting algorithms, the SIC module demonstrates its potential to improve forecasting accuracy across various domains, with a particular emphasis on renewable energy forecasting. The theoretical and mathematical foundations of the SIC module are explored, showcasing its capability to enhance predictive accuracy and resilience in an evolving energy landscape.
Afficher plus [+] Moins [-]Comparative analysis on crop yield forecasting using machine learning techniques Texte intégral
2024
Sharma, Shubham | Walia, Gurleen Kaur | Singh, Kanwalpreet | Batra, Vanshika | Sekhon, Amandeep Kaur | Kumar, Aniket | Rawal, Kirti | Ghai, Deepika
Global overpopulation necessitates increased crop yields, yet available arable land is limited. The study compares and evaluates the performance of three machine learning algorithms—Random Forest (RF), Extra Trees (ET), and Artificial Neural Network (ANN)—in crop yield prediction. Using 28,242 samples with seven features from 101 countries, we evaluated these models based on Mean Absolute Error (MAE), R-squared (R^2), and Mean Squared Error (MSE). The ET regression model demonstrated superior performance, achieving an MAE of 5249.03, the lowest among the models tested. Despite having the highest R^2 value of 0.9873, the ANN exhibited higher MAE and MSE values, indicating less reliability. The RF model showed intermediate results. With a prediction accuracy of 97.5%, the ET model proved to be the most effective for crop yield prediction, achieving the highest accuracy reported to date. Future research should explore more advanced algorithms and larger datasets to validate these findings further.
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