The COVID-19 pandemic increase the use of distance learning while studies have shown that there is insufficient digital knowledge among students in distance leaning as they do not adequately use technology as a digital citizenship indicator, while the awareness and knowledge of digital citizenship among teachers and students remains a key criterion for improving distance learning that mainly depends on information technology. Therefore, this study comes up to examine the awareness and knowledge of students and faculty of digital citizenship in distance environment by focusing on two different higher academic institutions, namely the Al-Quds Open University (QOU) in the Palestinian territories and the University of Kyrenia (KU) in the Turkish Republic of Northern Cyprus in 2020, using interview, descriptive analysis, and Z-test Technique. The results revealed that students and faculty in both institutions were aware of the digital citizenship concepts, but lacked the in-depth knowledge and understanding of concepts such as digital rights, digital security, and digital ethics. Furthermore, the awareness and knowledge of digital citizenship among KU students are higher than QOU students. Faculty in both institutions agreed with the importance of integrating digital citizenship practices such as digital rights, digital security, and digital ethics into elearning curriculum.

Global warning and thus climate change is a global issue and its consequences are being felt at varying degrees in different parts of the world. The developing countries are more vulnerable to its effects because of their poor economic status and political instability. In recent times, experiences of more flooding, erosion, drought, storms, rise in sea level and other extreme weather conditions resulting in poverty, degraded environment and low agricultural productivity. It’s devastating impact on various dimension of human endeavours and socio-economic income of nations and individual cannot be over emphasized. Climatologically, has an extremely variable rainfall distribution, which will be exacerbated by climate change. This will inevitably impact on agriculture and the availability of water to sustain human activities. These future climate change impacts are likely to aggravate the harmful effects of poor land use; practices, especially deforestation, soil degradation and water pollution. Communities that have been made vulnerable by economic hardship and disease will find it even harder to cope. Climate change is perhaps the most serious environmental threat to the fight against hunger, malnutrition, diseases and poverty in sub-Saharan Africa mainly through its impact on agricultural productivity

Nowadays, emerging technologies have changed the places of work through computers and ICT tools, which have revolutionized teaching and learning environments in different ways. In spite of the fact that computers as ICT tools have become part and progressively instrument for teachers and instructors used in teaching and learning, but most educators can't incorporate them into their teaching and learning process, which results in students being ill-equipped or lacking some necessary skills in the world of work, which leads to low performance and poor handling of tools whose lead to low production. To tackle this issue, it is essential to develop the technical and vocational education and training (TVET) system by determining the quality of technical and vocational education (TVE) teachers. In this paper, the literature concerning the competence required by TVET teachers towards computer-related instructional tech-nology for classroom teaching and learning was examined through the technological pedagogical content knowledge (TPACK) model. Sixty (60) questionnaires were ad-ministered to TVE teachers within six technical colleges of education in north-eastern Nigeria. The data was quantitatively analyzed using traditional linear models, namely multilinear regression (MLR) and artificial intelligence (AI) models, namely artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS), which were developed using MATLAB 9.3 (R2019a), while the classical linear MLR model was developed using SPSS software. The results from our classical study indicated that TVE teachers are competent in computer and some instructional technology usage and show a high correlation between competence and teaching experience and a lower correlation between competence and gender. The goodness of fit shows a good fit of the model. Future studies should examine the application of other linear and non-linear AI techniques.

Nowadays, emerging technologies have changed the places of work through computers and ICT tools, which have revolutionized teaching and learning environments in different ways. In spite of the fact that computers as ICT tools have become part and progressively instrument for instructors used in teaching and learning, most educators can't incorporate them into their teaching and learning process, which results in students being ill-equipped or lacking some necessary skills in the world of work, which leads to low performance and poor production. To tackle this issue, it is essential to develop the tech-nical and vocational education and training (TVET) system by determining the quality of TVE. In this paper, the literature concerning the competence required by TVET teachers towards computer-related instructional technology for classroom teaching and learning was examined through the technological pedagogical content knowledge (TPACK) model. Sixty (60) questionnaires were administered to TVE teachers within six technical colleges of education in north-eastern Nigeria. The data was quantitatively analyzed using tradi-tional linear models, namely multilinear regression (MLR) and artificial intelligence (AI) models, namely artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS), which were developed using MATLAB 9.3 (R2019a), while the classical linear MLR model was developed using SPSS software. The results from our classical study indicated that TVE teachers are competent in computer and some instructional technology usage and show a high correlation between competence and teaching experi-ence and a lower correlation between competence and gender. The goodness of fit shows a good fit of the model. Future studies should examine the application of other linear and non-linear AI techniques.

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