E-LEARNING OR CLASSIC EDUCATION?

The digital environment extents obvious the sphere, being used to provide information and to express ideas in different manners: verbal, visual, auditory or a mix by all these. As result, for educators will be more and more difficult to favour the handle of verbal language to detriment of others expression modalities. Internet becomes, in every day, the referee of education and culture access, and the most adequate form from to come in the meet of knowledge needs and continuous formation is E-Learning.educational add value, higher education services, academics sites, e-learning, marketing research, consumer

AI for Classic Video Games using Reinforcement Learning

Deep reinforcement learning is a technique to teach machines tasks based on trial and error experiences in the way humans learn. In this paper, some preliminary research is done to understand how reinforcement learning and deep learning techniques can be combined to train an agent to play Archon, a classic video game. We compare two methods to estimate a Q function, the function used to compute the best action to take at each point in the game. In the first approach, we used a Q table to store the states and weights of the corresponding actions. In our experiments, this method converged very slowly. Our second approach was similar to that of [1]: We used a convolutional neural network (CNN) to determine a Q function. This deep neural network model successfully learnt to control the Archon player using keyboard event that it generated. We observed that the second approaches Q function converged faster than the first. For the latter method, the neural net was trained only using prediodic screenshots taken while it was playing. Experiments were conducted on a machine that did not have a GPU, so our training was slower as compared to [1]

Classic machine learning methods

In this chapter, we present the main classic machine learning methods. A large part of the chapter is devoted to supervised learning techniques for classification and regression, including nearest-neighbor methods, linear and logistic regressions, support vector machines and tree-based algorithms. We also describe the problem of overfitting as well as strategies to overcome it. We finally provide a brief overview of unsupervised learning methods, namely for clustering and dimensionality reduction

Tactical enacting : a grounded theory : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Education at Massey University, Manawatū, New Zealand

This research uses classic grounded theory methodology to produce a grounded theory of tactical enacting. Forty two participants were drawn from the population of learning advisors working in a variety of tertiary education organisations in New Zealand. Data consisted of field notes and transcripts from observations, interviews and a group workshop/discussion and were analysed using all procedures that comprise classic grounded theory methodology. The thesis of this thesis is that learning advisors express a concern for role performance and continually resolve that concern through tactical enacting. In tactical enacting, learning advisors are working tactically towards a variety of ends. These ends include a performance identity and a role critical to organisational agendas. A role critical to organisational agendas is one which makes a significant contribution to student success outcomes and organisational performance. Making a strong contribution to student success and organisational performance helps learning advisors construct the desired professional identity for themselves and establish their role as valuable in the eyes of others and the organisation. Tactical enacting means advisors perform their role tactically in order to meet their own professional standards as well as the needs and expectations of students and the organisation and to help secure their place within tertiary education. However, in tactical enacting, learning advisors constitute themselves as the performing subject, subject to and subjecting themselves to the performativity discourse of the contemporary tertiary education organisation. At the same time, in tactical enacting, learning advisors constitute themselves as the ethical subject in an effort not to be governed by performativity alone and to enable them to meet organisational, student and their own expectations of how they should behave. This research contributes to knowledge in three main areas. Firstly, to knowledge and practice in relation to professional roles and organisations; specifically, the learning advisor role in the contemporary tertiary education organisation in New Zealand. Secondly, to research; specifically, to the scholarship of learning advising, and, lastly, to research method; specifically, to classic grounded theory methodology, and to an approach that applies a Foucauldian analytical framework to a discussion of an emergent grounded theory

The Implications of Pricing on Social Learning

We study the implications of endogenous pricing for learning and welfare in the classic herding model . When prices are determined exogenously, it is known that learning occurs if and only if signals are unbounded. By contrast, we show that learning can occur when signals are bounded as long as non-conformism among consumers is scarce. More formally, learning happens if and only if signals exhibit the vanishing likelihood property introduced bellow. We discuss the implications of our results for potential market failure in the context of Schumpeterian growth with uncertainty over the value of innovations

A MODEL OF ANALYSIS OF THE E-LEARNING SYSTEM QUALITY

The wide proliferation of the e-learning formation system become a true fact. The infrastructure delivered by the internet network permitted the decreases of the exploitation costs in favor of the beneficiary of formations. Like in the case of the classic system of formation a question about how to measure the its quality is raised. It is very specialized environment with the same actors like in the classic system too but with different type of interactions. Can we say that in both system the results are similar and their quality is the same. This paper reveal a model that can be used when try to evaluate the quality of this kind of system using specialized indicators for every aspect that can be measured.e-learning system, quality, indicators, beneficiary of formation elearning activities, e-learning materials