Museos, redes sociales y tecnología 2.0

Índice: - Sobre museos, redes sociales y tecnología 2.0 (Alex Ibáñez Etxeberria). - Sitios web y museos: nuevas aplicaciones para el aprendizaje informal (Mikel Asensio, Elena Asenjo y Alex Ibáñez Etxeberria). - From headphones to microphones: mobile social media in the museum as distributed network (Nancy Proctor). - Mobile learning y patrimionio: aprendiendo historia con mi teléfono, mi GPS y mi PDA (Alex Ibáñez Etxeberria, Mikel Asensio y José Miguel Correa). - Digital asset management strategies for multi-platform content delivery (Titus Bicknell). - Redes sociales y museos participativos: la irrupción de las tecnologías 2.0 en la sociedad y su aplicación en los museos a través del caso de Arazi (Juan José Aranburu).

Disney: ideologia eta pedagogia

[eus] Ikerketa honek Walt Disney konpainiak ekoiztutako hainbat filmetan agertzen den edukia eta pertsonaiak analizatzen ditu. Pelikulak balorez eta aspektu ideologikoez beteta daude eta gizarte-ikaskuntzaren teoriaren arabera, izugarrizko eragina daukate haurren jarduteko moduan. Ideia horiek oso lotuta daude emakumezkoak gizartean hartzen duen irudiarekin, gizartean dagoen familiaren esanahiarekin eta gure gizarteko sistema politiko eta ekonomikoarekin. Beraz, animaziozko filmen aurrean umeen kritikotasuna garatzeko Lehen Hezkuntzako gelarako baliabide metodologikoa proposatzen da, umeek pantaila handian ikusten dutenaz hausnar dezaten.

Altruism in the (Social) Network

This paper explores the role of social integration on altruistic behavior. To this aim, we develop a two-stage experimental protocol based on the classic Dictator Game. In the first stage, we ask a group of 77 undergraduate students in Economics to elicit their social network; in the second stage, each of them has to unilaterally decide over the division of a fixed amount of money to be shared with another anonymous member in the group. Our experimental design allows to control for other variables known to be relevant for altruistic behavior: framing and friendship/acquaintance relations. Consistently with previous research, we find that subjects favor their friends and that framing enhances altruistic behavior. Once we control for these effects, social integration (measured by betweenness, a standard centrality measure in network theory) has a positive effect on giving: the larger social isolation within the group, the more likely it is the emergence of selfish behavior. These results suggest that information on the network structure in which subjects are embedded is crucial to account for their behavior.

Learning in Network Games

We report the findings of an experiment designed to study how people learn and make decisions in network games. Network games offer new opportunities to identify learning rules, since on networks (compared to e.g. random matching) more rules differ in terms of their information requirements. Our experimental design enables us to observe both which actions participants choose and which information they consult before making their choices. We use this information to estimate learning types using maximum likelihood methods. There is substantial heterogeneity in learning types. However, the vast majority of our participants' decisions are best characterized by reinforcement learning or (myopic) best-response learning. The distribution of learning types seems fairly stable across contexts. Neither network topology nor the position of a player in the network seem to substantially affect the estimated distribution of learning types.

An Open and Social Spaced Repetition System for Language Learning

In the last decades big improvements have been done in the field of computer aided learning, based on improvements done in computer science and computer systems. Although the field has been always a bit lagged, without using the latest solutions, it has constantly gone forward taking profit of the innovations as they show up. As long as the train of the computer science does not stop (and it won’t at least in the near future) the systems that take profit of those improvements will not either, because we humans will always need to study; Sometimes for pleasure and some other many times out of need. Not all the attempts in the field of computer aided learning have been in the same direction. Most of them address one or some few of the problems that show while studying and don’t take into account solutions proposed for some other problems. The reasons for this can be varied. Sometimes the solutions simply are not compatible. Some other times, because the project is an investigation it’s interesting to isolate the problem. And, in commercial products, licenses and patents often prevent the new projects to use previous work. The world moved forward and this is an attempt to use some of the options offered by technology, mixing some old ideas with new ones.

Contributions to learning Bayesian network models from weakly supervised data: Application to Assisted Reproductive Technologies and Software Defect Classification

162 p.