educational technology


Artificial Intelligence eLearning Africa News Portal

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The Internet contains various categories of materials, some of which can be used as educational resources. These educational resources can be retrieved for content creation for use in Adaptive eLearning Systems (AES). Adaptive eLearning is a branch of eLearning that provides educational materials and resources based on the learners' needs. The adaptive learning system is not limited to delivering materials in a personalised manner to the learner; it also adapts in terms of interaction with learners and maintains learners' preferences. Artificial Intelligence plays a key role in adaptive eLearning by providing a personalised learning experience.


4 ways artificial intelligence will shape the future of learning technology

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With the rapid pace of innovation continually disrupting business models, and in many cases entire industries, how will online learning keep up to provide the relevant courseware for today's and tomorrow's workforce? This will be essential for economic growth and to support a thriving, college-educated workforce that's equipped with the very latest knowledge, ideas and technology. In the future, I believe that institutions at the forefront of online education will be recognized via several capabilities which will have digitally transformed today's EdTech market. They will include a powerful combination of omni-channel learning pathways, cognitive courseware, virtual counselors and AI-enabled course development and grading. These innovations, underpinned by artificial intelligence (AI), will help to provide students the ultimate choice in their courseware – including up-to-the-minute courses on high-interest/high-growth subject matter – as well as highly-innovative digital services that support them every step of the way to help maximize their success and personal objectives.


The Sooner You Get Your First AI Job, the Better for Your Career

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Artificial intelligence is already reshaping society as we know it in both business and consumer realms. Early use cases with Alexa, autonomous vehicles and AI-driven supply chains provide just a glimpse of the disruption that AI is poised to deliver in the near future and for years to come. Yet despite all the AI hype and initial successes, it remains in its infancy. That makes now the ideal time for young people to build the knowledge, skill sets and connections they need to capitalize on the fast-growing market for AI jobs and build a strong AI career. One reason is simply practical.


Leveraging Artificial Intelligence to Tide Over Education Crisis - DZone AI

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Artificial intelligence technology in education is no more the future, it is the present. We are already witnessing the impact of technology in the education sector. Increased uses of digital devices, adaptive learning platforms, and engaging lessons have transformed the learning as well as teaching processes. With the help of artificial intelligence technology, the educators today are working on creating activities that can not only ignite the curiosities among the students, but can make their learning experience a memorable one. Although AI can never replace the human teachers, it has successfully given a whole new meaning to the roles and responsibilities of a teacher.


Websites That Teach Artificial Intelligence Fundamentals

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There are lots of education options available online, provided you're a self-starter with the discipline to do a lot of coursework on your own. For example, Microsoft's AI School offers a variety of lessons for developers in everything from text analytics and object recognition to custom neural-network models. The content is angled toward data scientists and developers, and heavily emphasizes the use of Microsoft products (of course) in addition to "universal" A.I. skills. It's also free, although those who want Verified Certificates will need to pay a fee. Microsoft, of course, is far from your only option when it comes to learning about A.I. online, particularly with regard to beginner-level material.


Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data

arXiv.org Machine Learning

Deep Learning has the hierarchical network architecture to represent the complicated features of input patterns. Such architecture is well known to represent higher learning capability compared with some conventional models if the best set of parameters in the optimal network structure is found. We have been developing the adaptive learning method that can discover the optimal network structure in Deep Belief Network (DBN). The learning method can construct the network structure with the optimal number of hidden neurons in each Restricted Boltzmann Machine and with the optimal number of layers in the DBN during learning phase. The network structure of the learning method can be self-organized according to given input patterns of big data set. In this paper, we embed the adaptive learning method into the recurrent temporal RBM and the self-generated layer into DBN. In order to verify the effectiveness of our proposed method, the experimental results are higher classification capability than the conventional methods in this paper.


10 Reasons you should learn Artificial Intelligence - TechEconomy.ng

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When talking about Artificial Intelligence, some people think about the destruction of the world and killer robots, but Artificial Intelligence is already playing a major role in our lives, non-destructively. We all are familiar with programs such as Siri and Google Now, which are improving our way of life. Similarly, you must have played chess against the computer, in which most people get beat atrociously. These programs are nothing but artificial intelligence, which is designed to assist us with a set of protocols. Similar programs are self-driving cars, or motion and reflex detecting video games, which evolve as time goes along.


The achievement gap and AI augmented online tutoring

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The achievement gap between students who come from different socio-economic backgrounds is a well-known and persistent problem in education. Disparities in achievements between high and low socio-economic groups are evident in children as young as age 3 years and seem to be a problem the world over. Despite pupils' overall attainment scores rising over the last decade or so, the gap between students from different socio-economic groups remains intractably present and widespread. Family finances play a big part amongst the various reasons for this disparity. Pupils from low socio-economic backgrounds (SEBs) are often only able to attend a few, if any of the extra-curricular activities enjoyed by their more affluent peers.


Examples of Artificial Intelligence in Education - Current Applications

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Though yet to become a standard in schools, artificial intelligence in education has been "a thing" since AI's uptick in the 1980s. In many ways, the two seem made for each other. We use education as a means to develop minds capable of expanding and leveraging the knowledge pool, while AI provides tools for developing a more accurate and detailed picture of how the human mind works. AI's digital, dynamic nature also offers opportunities for student engagement that cannot be found in often out-dated textbooks or in the fixed environment of the typical four-walled classroom. In synergistic fashion, they each have the potential to propel the other forward and accelerate the discovery of new learning frontiers and the creation of innovative technologies.


Artificial Intelligence is the bicycle for our Technology -- My Udacity AMA

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Firstly, Karen Baker and Martin McGovern from Udacity help organize and facilitate this AMA for the life long learners at Udacity. I am deeply thankful to Karen, Martin and Udacity for this opportunity to share the knowledge. QQ: What is the best piece of advice you've ever received in your career? VK: I have got some good advice from books as well as mentors. QQ: What suggestions do you have around building your portfolio?