Evolutionary ecology of learning: insights from fruit flies

Ecologically and evolutionarily oriented research on learning has traditionally been carried out on vertebrates and bees. While less sophisticated than those animals, fruit flies (Drosophila) are capable of several forms of learning, and have an advantage of a short generation time, which makes them an ideal system for experimental evolution studies. This review summarizes the insights into evolutionary questions about learning gained in the last decade from evolutionary experiments on Drosophila. These experiments demonstrate that Drosophila have the genetic potential to evolve substantially improved learning performance in ecologically relevant learning tasks. In at least one set of selected populations the improved learning generalized to another task than that used to impose selection, involving a different behavior, different stimuli, and a different sensory channel for the aversive reinforcement. This improvement in learning ability was associated with reduction in other fitness-related traits, such as larval competitive ability and lifespan, pointing out to evolutionary trade-offs of improved learning. These trade-offs were confirmed by other evolutionary experiments where reduction in learning performance was observed as a correlated response to selection for tolerance to larval nutritional stress or for delayed aging. Such trade-offs could be one reason why fruit flies have not fully used up their evolutionary potential for learning ability. Finally, another evolutionary experiment with Drosophila provided the first direct evidence for the long-standing ideas that learning can under some circumstances accelerate and in other slow down genetically-based evolutionary change. These results demonstrate the usefulness of fruit flies as a model system to address evolutionary questions about learning.

OER in Portugal as agent of curriculum innovation and technological change. Inducing practices of "new" teaching standards

This research project aimed the following goal: promote the creation, use and disclosure of OER in a Group of Schools, involving schools and teachers from different learning levels, expecting to test and validate the use of OER, in a learning-teaching model towards curricular innovation. Defining as a starting point different subjects and teachers from distinct academic areas, we have implemented a set of activities leading to the creation of OER supported, when possible, in FLOSS tools. We adopted an action research methodology with a dual purpose: to act within a community of teachers and students, while increasing at the same time their knowledge, as well as the researcher's. The activity was developed cooperatively in order to process a certain reality of the teaching-learning process, through practical/reflective action towards it and inducing its implementation by others in the Portuguese School System, based on the production and sharing OER.

Open Learning Network : the evidence of OER impact

Much of the initial work on Open Educational Resources (OER) has inevitably concentrated on how to produce the resources themselves and to establish the idea in the community. It is now eight years since the term OER was first used and more than ten years since the concept of open content was described and a greater focus is now emerging on the way in which OER can influence policy and change the way in which educational systems help people learn. The Open University UK and Carnegie Mellon University are working in partnership on the OLnet (Open Learning Network), funded by The William and Flora Hewlett Foundation with the aims to search out the evidence for use and reuse of OER and to establish a network for information sharing about research in the field. This means both gathering evidence and developing approaches for how to research and understand ways to learn in a more open world, particularly linked to OER, but also looking at other influences.

Aversive Stimuli and Functional Networks of Fear Learning in PTSD : 734

Background: One characteristic of post traumatic stress disorder is an inability to adapt to a safe environment i.e. to change behavior when predictions of adverse outcomes are not met. Recent studies have also indicated that PTSD patients have altered pain processing, with hyperactivation of the putamen and insula to aversive stimuli (Geuze et al, 2007). The present study examined neuronal responses to aversive and predicted aversive events. Methods: Twenty-four trauma exposed non-PTSD controls and nineteen subjects with PTSD underwent fMRI imaging during a partial reinforcement fear conditioning paradigm, with a mild electric shock as the unconditioned stimuli (UCS). Three conditions were analyzed: actual presentations of the UCS, events when a UCS was expected, but omitted (CS+), and events when the UCS was neither expected nor delivered (CS-). Results: The UCS evoked significant alterations in the pain matrix consisting of the brainstem, the midbrain, the thalamus, the insula, the anterior and middle cingulate and the contralateral somatosensory cortex. PTSD subjects displayed bilaterally elevated putamen activity to the electric shock, as compared to controls. In trials when USC was expected, but omitted, significant activations were observed in the brainstem, the midbrain, the anterior insula and the anterior cingulate. PTSD subjects displayed similar activations, but also elevated activations in the amygdala and the posterior insula. Conclusions: These results indicate altered fear and safety learning in PTSD, and neuronal activations are further explored in terms of functional connectivity using psychophysiological interaction analyses.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Supporting the reuse of effective CSCL learning designs through social structure representations

Distance and blended collaborative learning settings are usually characterized by different social structures defined in terms of groups' number, dimension, and composition; these structures are variable and can change within the same activity. This variability poses additional complexity to instructional designers, when they are trying to develop successful experiences from existing designs. This complexity is greatly associated with the fact that learning designs do not render explicit how social structures influenced the decisions of the original designer, and thus whether the social structures of the new setting could preclude the effectiveness of the reused design. This article proposes the usage of new representations (social structure representations, SSRs) able to support unskilled designers in reusing existing learning designs, through the explicit characterization of the social structures and constraints embedded either by the original designers or the reusing teachers, according to well-known principles of good collaborative learning practice. The article also describes an evaluation process that involved university professors, as well as the main findings derived from it. This process supported the initial assumptions about the effectiveness of SSRs, with significant evidence from both qualitative and qualitative data.

The influence of learning on evolution: a mathematical framework.

The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.

How Millennials are changing the way of learning: the state of the art of ICT integration in education

Millennials generation is changing the way of learning, prompting educational institutions to attempt to better adapt to young needs by incorporating technologies into education. Based on this premise, we have reviewed the prominent reports of the integration of ICT into education with the aim of evidencing how education is changing, and will change, to meet the needs ofMillennials with ICT support. We conclude that most of the investments have simply resulted in an increase of computers and access to the Internet, with teachers reproducing traditional approaches to education and e-learning being seen as complementary to face-to-face education. While it would seem that the use of ICT is not revolutionizing learning, it is facilitating the personalization, collaboration and ubiquity of learning.

Demand-based structural change and balanced economic growth

[eng] We analyze the equilibrium of a multi-sector exogenous growth model where the introduction of minimum consumption requirements drives structural change. We show that equilibrium dynamics simultaneously exhibt structural change and balanced growth of aggregate variables as is observed in US when the initial intensity of minimum consumption requirements is sufficiently small. This intensity is measured by the ratio between the aggregate value of the minimum consumption requirements and GDP and, therefore, it is inversely related with the level of economic development. Initially rich economies benefit from an initially low intensity of the minimum consumption requirements and, as a consequence, these economies end up exhibiting balanced growth of aggregate variables, while there is structural change. In contrast, initially poor economies suffer from an initially large intensity of the minimum consumption requirements, which makes the growth of the aggregate variables unbalanced during a very large period. These economies may never exhibit simultaneously balanced growth of aggregate variables and structural change.

Faculty-librarians collaboration in an e-learning experience : resources management and training in Open University of Catalonia (UOC)

The traditional model of learning based on knowledge transfer doesn't promote the acquisition of information-related competencies and development of autonomous learning. More needs to be done to embrace learner-centred approaches, based on constructivism, collaboration and co-operation. This new learning paradigm is aligned with the European Higher Education Area (EHEA) requirements. In this sense, a learning experience based in faculty' librarian collaboration was seen as the best option for promoting student engagement and also a way to increase information-related competences in Open University of Catalonia (UOC) academic context. This case study outlines the benefits of teacher-librarian collaboration in terms of pedagogy innovation, resources management and introduction of open educational resources (OER) in virtual classrooms, Information literacy (IL) training and use of 2.0 tools in teaching. Our faculty-librarian's collaboration aims to provide an example of technology-enhanced learning and demonstrate how working together improves the quality and relevance of educational resources in UOC's virtual classrooms. Under this new approach, while teachers change their role from instructors to facilitators of the learning process and extend their reach to students, libraries acquire an important presence in the academic learning communities.

The Roles of Cultural, Functional and Value Diversity in Innovativeness and Learning

Tutkielman tavoite on tutkia kulttuurista, funktionaalista ja arvojen diversiteettiä, niiden suhdetta innovatiivisuuteen ja oppimiseen sekä tarjota keinoja diversiteetin johtamiseen. Tämän lisäksi selvitetään linjaesimiesten haastattelujen kautta miten diversiteetti case -organisaatiossa tällä hetkellä koetaan. Organisaation diversiteetin tämänhetkisen tilan tunnistamisen kautta voidaan esittää parannusehdotuksia diversiteetin hallintaan. Tutkimus- ja tiedonkeruumenetelmänä käytetään kvalitatiivista focus group haastattelumenetelmää. Tutkimuksessa saatiin selkeä kuva kulttuurisen, funktionaalisen ja arvojen diversiteetin merkityksistä organisaation innovatiivisuudelle ja oppimiselle sekä löydettiin keinoja näiden diversiteetin tyyppien johtamiseen. Tutkimuksen tärkeä löydös on se, että diversiteetti vaikuttaa positiivisesti organisaation innovatiivisuuteen kun sitä johdetaan tehokkaasti ja kun organisaatioympäristö tukee avointa keskustelua ja mielipiteiden jakamista. Case organisaation tämänhetkistä diversiteetin tilaa selvitettäessä havaittiin että ongelma organisaatiossa ei ole diversiteetin puute, vaan paremminkin se, ettei diversiteettia osata hyödyntää. Organisaatio ei tue erilaisten näkemysten ja mielipiteiden vapaata esittämistä jahyväksikäyttöä ja siksi diversiteetin hyödyntäminen on epätäydellistä. Haastatteluissa tärkeinä seikkoina diversiteetin hyödyntämisen parantamisessa nähtiin kulttuurin muuttaminen avoimempaan suuntaan ja johtajien esimiestaitojen parantaminen.

Once and for all - How people change strategy to ignore irrelevant information in visual tasks

Ignoring irrelevant visual information aids efficient interaction with task environments. We studied how people, after practice, start to ignore the irrelevant aspects of stimuli. For this we focused on how information reduction transfers to rarely practised and novel stimuli. In Experiment 1, we compared competing mathematical models on how people cease to fixate on irrelevant parts of stimuli. Information reduction occurred at the same rate for frequent, infrequent, and novel stimuli. Once acquired with some stimuli, it was applied to all. In Experiment 2, simplification of task processing also occurred in a once-for-all manner when spatial regularities were ruled out so that people could not rely on learning which screen position is irrelevant. Apparently, changes in eye movements were an effect of a once-for-all strategy change rather than a cause of it. Overall, the results suggest that participants incidentally acquired knowledge about regularities in the task material and then decided to voluntarily apply it for efficient task processing. Such decisions should be incorporated into accounts of information reduction and other theories of strategy change in skill acquisition.

Transferring control demands across incidental learning tasks - Stronger sequence usage in serial reaction task after shortcut option in letter string checking

After incidentally learning about a hidden regularity, participants can either continue to solve the task as instructed or, alternatively, apply a shortcut. Past research suggests that the amount of conflict implied by adopting a shortcut seems to bias the decision for vs. against continuing instruction-coherent task processing. We explored whether this decision might transfer from one incidental learning task to the next. Theories that conceptualize strategy change in incidental learning as a learning-plus-decision phenomenon suggest that high demands to adhere to instruction-coherent task processing in Task 1 will impede shortcut usage in Task 2, whereas low control demands will foster it. We sequentially applied two established incidental learning tasks differing in stimuli, responses and hidden regularity (the alphabet verification task followed by the serial reaction task, SRT). While some participants experienced a complete redundancy in the task material of the alphabet verification task (low demands to adhere to instructions), for others the redundancy was only partial. Thus, shortcut application would have led to errors (high demands to follow instructions). The low control demand condition showed the strongest usage of the fixed and repeating sequence of responses in the SRT. The transfer results are in line with the learning-plus-decision view of strategy change in incidental learning, rather than with resource theories of self-control.

Demand-based structural change and balanced economic growth

[eng] We analyze the equilibrium of a multi-sector exogenous growth model where the introduction of minimum consumption requirements drives structural change. We show that equilibrium dynamics simultaneously exhibt structural change and balanced growth of aggregate variables as is observed in US when the initial intensity of minimum consumption requirements is sufficiently small. This intensity is measured by the ratio between the aggregate value of the minimum consumption requirements and GDP and, therefore, it is inversely related with the level of economic development. Initially rich economies benefit from an initially low intensity of the minimum consumption requirements and, as a consequence, these economies end up exhibiting balanced growth of aggregate variables, while there is structural change. In contrast, initially poor economies suffer from an initially large intensity of the minimum consumption requirements, which makes the growth of the aggregate variables unbalanced during a very large period. These economies may never exhibit simultaneously balanced growth of aggregate variables and structural change.