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Nairobi 2010 Conference Reoprt  Climate Change and Natural Resource Use in Eastern Africa: Impacts, Adaptation and Mitigation Report of the 3rd Scientific Conference of the Ecological Society for Eastern Africa (ESEA) and co-hosted with the Pan African Climate Justice Alliance (PACJA) at Multimedia University College, Nairobi, 19 - 21 May 2010 By Nicholas Oguge, Caroline Lumosi, Teddy Odindo, Joseph Ngondi and Philista Malaki October 4, 2010 Summary While the Earth's climate has changed throughout history, the current warming trend has been of particular concern because most of it is human-induced and proceeding at a rate that is unprecedented.  One of the greatest concerns of this global warming is climate variability and change.  The risks associated with climate change add to development challenges such as food and water insecurity. Although climate change is only one of the many drivers negatively affecting biodiversity and ecosystem services, it certainly exacerbates the other factors such as land degradation and unsustainable natural resource use. There is general concern on the accelerating deterioration of the human environment and natural resources. This would widen poverty levels confronting eastern African countries and threaten gains made towards achieving the Millennium Development Goals. Thus, the Ecological Society for Eastern African organised its 3rd annual scientific conference with a theme addressing this global challenge.  The idea was to bring together researchers, policy makers and the general public together to discuss the climate change phenomena, its impacts, mitigation strategies and adaptation measures with regard to natural resource use in Eastern Africa. In order to address above issues and to reach out to a wider audience, we designed the conference strategically on three tiers:   1. Plenary talks: to provide policy information and direction, science on climate change, ecological and socio-economic effects, how to commun

"This paper describes the implementation of a quantitative cost effectiveness analyzer for Web-supported academic instruction that was developed in Tel Aviv University during a long term study. The paper presents the cost effectiveness analysis of Tel Aviv University campus. Cost and benefit of 3,453 courses were analyzed, exemplifying campus-wide analysis. These courses represent large-scale Web-supported academic instruction processes throughout the campus. The findings were described, referring to students, instructors and university from both the economical and educational perspectives. The cost effectiveness values resulting from the calculations were summarized in four "coins" (efficiency coins=$; quality coins; affective coins; and knowledge management coins) for each of the three actors (students, instructors and university). In order to examine the distribution of those values throughout the campus assessment scales were created on the basis of descriptive statistics. The described analyzer can be implemented in other institutions very easily and almost automatically. This enables us to quantify the costs and benefits of Web-supported instruction on both the single-course and the campus-wide levels. "

Home > Data Science > How to learn Data Science in 2021? Data Science (DS) is a great, promising, and most demanding career. But are you confused about being a beginner and wanna know the Right Way to Learn DS? Technology is more into digitisation and due to this extensive transformation, huge data is expected to be produced in the coming future. To make use of such big data we need data scientists who can layout, design and filter the data in an organized way. All things considered, with a huge number of options available choosing the correct curriculum program and admission to the right institute is important. Besides all this, the course and institute to be suitable for your requirement are extremely difficult. While online courses are an incredible path for some to upskill, good opportunities from top colleges and universities are the platform for data scientists to test their knowledge in their field. Here are the five essential guidelines to turn into an expert in Data Science: Get a Data Science certificate or similar degree To get an opportunity as an entry-level data researcher, one would require a four-year certification in DS, math, insights and software engineering. Degrees can likewise give temporary job openings. All things considered if you have just secured a 4 yr certification in a different background through online e-courses or basic boot camps and workshops. The focus should be given to mastering the skills required for DS. Take a look at this course from AntWak on Data Engineering delivered by top global experts. Take comprehensive courses and devote time to learning You can become a top-class data researcher by taking a full course at a time. It will be the skill and instruments needed to turn into a data researcher, many critical projects and coaching help. A variety of such courses are available online that offer top to bottom analysis of subjects, for example, data scratching, AI, big data analysis and many more. To begin your learning

Discussing how universities want to control knowledge rather than letting it flow freely.

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"When University College London was founded in the 1820s, the poet Samuel Taylor Coleridge ridiculed it as a "lecture-bazaar": an institution that imparted information but not wisdom. "

Adult learners value the flexibility and convenience offered to them as online learners, and many learners are required to absent themselves from their online classes during courses in order to accommodate demanding schedules. What factors and tensions contribute to learners' decision-making at these times? This qualitative study considered the planned absences of learners engaged in an online graduate course at a large university. Working within the framework provided by cognitive, instructional, and social presences, findings showed the following: (1) learners understood and accommodated the relationship and importance of the affective domain to their cognitive successes in learning, (2) successful learners demonstrated insightful self-knowledge in using metacognitive strategies, and (3) learners' external support systems were fundamental to their ability to continue to learn when absences occurred. The study's findings corroborate other recent research that similarly stresses the complexity and interrelated nature of the adult learning process.

The application of information processing that deals with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision making is now the norm.

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"George Siemens posts frequently and with clarity on his blog elearnspace, and often I find myself nodding my head as I read or questioning my assumptions or bouncing around to other web sites as I hunt down reinforcing or contradicting information. Today I challenged a couple claims made in his posting, Explaining leads to information, which examines the past, present, and future roles of universities."

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