Merging Web 2.0 technologies with e-learning gets e-learning 2.0 term, which focus on people’s ability to interact and collaborate with each other; this presents drivers and barriers to e-learning 2.0. Web 3.0 would be more connected, more open, and more intelligent, this will transform the Web from a network of separately applications and content repositories to a more seamless and interoperable whole. Web 3.0 technologies emphasize machine-facilitated understanding of information in order to provide a more productive and intuitive user experience. It can be successfully used for educational projects. This paper presents a general overview of e-learning evolution vs web evolution, why e-learning 2.0 is not enough, how web 3.0 technologies could affect e-learning, what are the opportunities that we can benefit, and what are the challenges that we could face.

The concept of e-Learning 2.0 has become well established and widely accepted. Just like how e-Learning 2.0 replaced its predecessor, we are again on the verge of a transformation. Both previous generations of e-Learning (1.0 and 2.0) closely parody the prevalent technologies available in their kin Web versions (1.0 and 2.0, respectively). In order to acquire a better perspective to assess what technologies will be available in the Web 3.0 and therefore e-Learning 3.0, we take a historical glance at the previous generations of e-Learning and theWeb. We then survey some existing predictions for e-Learning 3.0 and finally provide our own. Previous surveys tend to identify educational needs for e-Learning, and then discuss what technologies are required to satisfy these needs. Educational needs are an important factor, but the required technologies may not reach fruition. Gauging past trends we take the reverse approach by first identifying technologies that are likely to be brought forth by the Web 3.0, and only then looking at how these technologies could be utilized in the learning domain. In particular, we pin-point Artificial Intelligence (more specifically Machine Learning and Data Mining) as a major driving force behind the Web 3.0. We therefore examine the influence that AI might exert on the development of e-Learning 3.0.

© Abstract: http://link.springer.com/chapter/10.1007/978-3-662-43454-3_18

® Citation Preprint: N. Rubens, D. Kaplan, and T. Okamoto. E-Learning 3.0: anyone, anywhere, anytime, and AI. In International Workshop on Social and Personal  Computing for Web- Supported Learning Communities (SPeL 2011), Dec 2011.

The purpose of this essay is to examine the different ways in which two sci-fi films approach AI in the near future – Moon (2009) and 2001 (1968) – and what their approaches tell us about the perceived consequences of AI technology during those time periods.