Teaching with wikis: addressing the digital divide

This paper addresses some aspects of the digital divide affecting teachers and learners in higher education. These relate to divisions arising from variable rates of technology adoption by teachers, which may be especially problematic when students’ uptake of technology is much more rapid than those who teach them, and also to divisions within the student body which teachers need to accommodate when they plan the design of learning. To address these divisions, we designed a pilot online workshop to prepare a small group of teaching staff at two Australian universities for using wikis in teaching and assessment. Participants were immersed in the experience of collaborating on a project in a wiki as learners, and then asked to reflect on this experience as teachers. We used a participatory action research approach with a view to developing a community of enquiry to investigate this experience for improving future offerings, and informing the participants’ teaching practice. This paper reports on the professional development effort, reflecting on the successes and limitations of the work, and lessons learned in relation to bridging the above aspects of the digital divide. We then comment on the potential for further development in the context of the evolution of learning technology as a research discipline

Teaching with wikis : addressing the digital divide

This paper addresses some aspects of the digital divide affecting teachers and learners in higher education. These relate to divisions arising from variable rates of technology adoption by teachers, which may be especially problematic when students&rsquo; uptake of technology is much more rapid than those who teach them, and also to divisions within the student body which teachers need to accommodate when they plan the design of learning. To address these divisions, we designed a pilot online workshop to prepare a small group of teaching staff at two Australian universities for using wikis in teaching and assessment. Participants were immersed in the experience of collaborating on a project in a wiki as learners, and then asked to reflect on this experience as teachers. We used a participatory action research approach with a view to developing a community of enquiry to investigate this experience for improving future offerings, and informing the participants&rsquo; teaching practice. This paper reports on the professional development effort, reflecting on the successes and limitations of the work, and lessons learned in relation to bridging the above aspects of the digital divide. We then comment on the potential for further development in the context of the evolution of learning technology as a research discipline.<br /

Testing the Variability Selection Hypothesis: The Adoption of Social Learning in Increasingly Variable Environments

The variability selection hypothesis predicts the adoption of versatile behaviors and survival strategies, in response to increasingly variable environments. In hominin evolution the most apparent adaptation for versatility is the adoption of social learning. The hypothesis that social learning will be adopted over other learning strategies, such as individual learning, when individuals are faced with increasingly variable environments is tested here using a genetic algorithm with steady state selection and constant population size. Individuals, constituted of binary string genotypes and phenotypes, are evaluated on their ability to match a target binary string, nominally known as the environment, with success being measured by the Hamming distance between the phenotype and environment. The state of any given locus in the environment is determined by a sine wave, the frequency of which increases as the simulation progresses thus providing increasing environmental variability. Populations exhibiting combinations of genetic evolution, individual learning and social learning are tested, with the learning rates of both individual and social learning allowed to evolve. We show that increasingly variable environments are sufficient but not necessary to provide an evolutionary advantage to those populations exhibiting the extra-genetic learning strategies, with social learning being favored over individual learning when populations are allowed to explore both strategies simultaneously. We also introduce a more biologically realistic model that allows for population collapse, and show that here the prior adoption of individual learning is a prerequisite for the successful adoption of social learning in increasingly variable environments

Online Resource Inference in Network Utility Maximization Problems

The amount of transmitted data in computer networks is expected to grow considerably in the future, putting more and more pressure on the network infrastructures. In order to guarantee a good service, it then becomes fundamental to use the network resources efficiently. Network Utility Maximization (NUM) provides a framework to optimize the rate allocation when network resources are limited. Unfortunately, in the scenario where the amount of available resources is not known a priori, classical NUM solving methods do not offer a viable solution. To overcome this limitation we design an overlay rate allocation scheme that attempts to infer the actual amount of available network resources while coordinating the users rate allocation. Due to the general and complex model assumed for the congestion measurements, a passive learning of the available resources would not lead to satisfying performance. The coordination scheme must then perform active learning in order to speed up the resources estimation and quickly increase the system performance. By adopting an optimal learning formulation we are able to balance the tradeoff between an accurate estimation, and an effective resources exploitation in order to maximize the long term quality of the service delivered to the users

Survival benefits in mimicry: a quantitative framework

Mimicry is a resemblance between species that benefits at least one of the species. It is a ubiquitous evolutionary phenomenon particularly common among prey species, in which case the advantage involves better protection from predation. We formulate a mathematical description of mimicry among prey species, to investigate benefits and disadvantages of mimicry. The basic setup involves differential equations for quantities representing predator behavior, namely, the probabilities for attacking prey at the next encounter. Using this framework, we present new quantitative results, and also provide a unified description of a significant fraction of the quantitative mimicry literature. The new results include `temporary' mutualism between prey species, and an optimal density at which the survival benefit is greatest for the mimic. The formalism leads naturally to extensions in several directions, such as the evolution of mimicry, the interplay of mimicry with population dynamics, etc. We demonstrate this extensibility by presenting some explorations on spatiotemporal pattern dynamics.Comment: 9 pages, 7 figure