Learning through Computer Model Improvisations

It has been convincingly argued that computer simulation modeling differs from traditional science. If we understand simulation modeling as a new way of doing science, the manner in which scientists learn about the world through models must also be considered differently. This article examines how researchers learn about environmental processes through computer simulation modeling. Suggesting a conceptual framework anchored in a performative philosophical approach, we examine two modeling projects undertaken by research teams in England, both aiming to inform flood risk management. One of the modeling teams operated in the research wing of a consultancy firm, the other were university scientists taking part in an interdisciplinary project experimenting with public engagement. We found that in the first context the use of standardized software was critical to the process of improvisation, the obstacles emerging in the process concerned data and were resolved through exploiting affordances for generating, organizing, and combining scientific information in new ways. In the second context, an environmental competency group, obstacles were related to the computer program and affordances emerged in the combination of experience-based knowledge with the scientists' skill enabling a reconfiguration of the mathematical structure of the model, allowing the group to learn about local flooding.

Interoperability of learning objects copyright in the LUISA semantic learning management system

Semantic Web technology is able to provide the required computational semantics for interoperability of learning resources across different Learning Management Systems (LMS) and Learning Object Repositories (LOR). The EU research project LUISA (Learning Content Management System Using Innovative Semantic Web Services Architecture) addresses the development of a reference semantic architecture for the major challenges in the search, interchange and delivery of learning objects in a service-oriented context. One of the key issues, highlighted in this paper, is Digital Rights Management (DRM) interoperability. A Semantic Web approach to copyright management has been followed, which places a Copyright Ontology as the key component for interoperability among existing DRM systems and other licensing schemes like Creative Commons. Moreover, Semantic Web tools like reasoners, rule engines and semantic queries facilitate the implementation of an interoperable copyright management component in the LUISA architecture.

Semantics-supported cooperative learning for enhanced awareness

Awareness is required for supporting all forms of cooperation. In Computer Supported Collaborative Learning (CSCL), awareness can be used for enhancing collaborative opportunities across physical distances and in computer-mediated environments. Shared Knowledge Awareness (SKA) intends to increase the perception about the shared knowledge, students have in a collaborative learning scenario and also concerns the understanding that this group has about it. However, it is very difficult to produce accurate awareness indicators based on informal message exchange among the participants. Therefore, we propose a semantic system for cooperation that makes use of formal methods for knowledge representation based on semantic web technologies. From these semantics-enhanced repository and messages, it could be easier to compute more accurate awareness.

Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T.

PURPOSE: To determine whether a mono-, bi- or tri-exponential model best fits the intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) signal of normal livers. MATERIALS AND METHODS: The pilot and validation studies were conducted in 38 and 36 patients with normal livers, respectively. The DWI sequence was performed using single-shot echoplanar imaging with 11 (pilot study) and 16 (validation study) b values. In each study, data from all patients were used to model the IVIM signal of normal liver. Diffusion coefficients (Di ± standard deviations) and their fractions (fi ± standard deviations) were determined from each model. The models were compared using the extra sum-of-squares test and information criteria. RESULTS: The tri-exponential model provided a better fit than both the bi- and mono-exponential models. The tri-exponential IVIM model determined three diffusion compartments: a slow (D1 = 1.35 ± 0.03 × 10(-3) mm(2)/s; f1 = 72.7 ± 0.9 %), a fast (D2 = 26.50 ± 2.49 × 10(-3) mm(2)/s; f2 = 13.7 ± 0.6 %) and a very fast (D3 = 404.00 ± 43.7 × 10(-3) mm(2)/s; f3 = 13.5 ± 0.8 %) diffusion compartment [results from the validation study]. The very fast compartment contributed to the IVIM signal only for b values ≤15 s/mm(2) CONCLUSION: The tri-exponential model provided the best fit for IVIM signal decay in the liver over the 0-800 s/mm(2) range. In IVIM analysis of normal liver, a third very fast (pseudo)diffusion component might be relevant. KEY POINTS: ? For normal liver, tri-exponential IVIM model might be superior to bi-exponential ? A very fast compartment (D = 404.00 ± 43.7 × 10 (-3)  mm (2) /s; f = 13.5 ± 0.8 %) is determined from the tri-exponential model ? The compartment contributes to the IVIM signal only for b ≤ 15 s/mm (2.)

Wiki-supported collaborative learning in primary education. How a dialogic space is created for thinking together

This paper explores how wikis may be used to support primary education students’ collaborative interaction and how such an interaction process can be characterised. The overall aim of this study is to analyse the collaborative processes of students working together in a wiki environment, in order to see how primary students can actively create a shared context for learning in the wiki. Educational literature has already reported that wikis may support collaborative knowledge-construction processes, but in our study we claim that a dialogic perspective is needed to accomplish this. Students must develop an intersubjective orientation towards each others’ perspectives, to co-construct knowledge about a topic. For this purpose, our project utilised a ‘Thinking Together’ approach to help students develop an intersubjective orientation towards one another and to support the creation of a ‘dialogic space’ to co-construct new understanding in a wiki science project. The students’ asynchronous interaction process in a primary classroom -- which led to the creation of a science text in the wiki -- was analysed and characterised, using a dialogic approach to the study of CSCL practices. Our results illustrate how the Thinking Together approach became embedded within the wiki environment and in the students’ collaborative processes. We argue that a dialogic approach for examining interaction can be used to help design more effective pedagogic approaches related to the use of wikis in education and to equip learners with the competences they need to participate in the global knowledge-construction era.

Análisis de logs con soluciones Big Data e integración con BI corporativo

En este trabajo se hace una evaluación de la solución Big Data Hadoop como alternativa de almacenamiento y procesado de elevados volúmenes de datos en comparación con modelos relacionales tradicionales en un Enterprise Data Warehouse (EDW) corporativo, y de cómo ésta es capaz de integrarse con las herramientas de visualización típicas de las suites Business Intelligence.

Time patterns and perceptions of online learning success factors

Online learning provides the opportunity to work on academic tasks at any time at the same time as doing other activities, such as using in web 2.0 tools. This study identifies factors that contribute to success in online learning from the students¿ perspective and their relationship with time patterns. A survey of learning outputs was used to find relationships between students¿ satisfaction, knowledge acquisition and knowledge transfer with time for working on academic tasks. In this study, 199 students from a university in Mexico completed the survey. Findings suggest that knowledge transfer has a significant association with the number of hours online per day, hours spent on social networks and the use made of e-learning during working hours. Learner satisfaction has a strong relationship with the time in years a learner has been using the Internet and the number of hours devoted to the course per week. The findings of this research will be helpful for faculty and instructional designers for implementing learning strategies.

Task complexity, the Cognition Hypothesis and second language learning and performance

In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance.

A Technology Intelligence Process for a High Technology Company

Tämä diplomityö määrittelee teknologiaseurantaprosessin, jolla korkean teknologian yritys voi ohjata toimintaansa. Korkean teknologian yrityksille on olennaista seurata teknologian kehitystä. Tällaiset yritykset tarvitsevat hyvin määritellyn järjestelmän, jolla ne voivat seurata ja ennustaa teknologista kehitystä.Työssä esitetään, että teknologiaseuranta ja kilpailuseuranta (competitive intelligence) ovat business intelligencen osa-alueita, jotka täydentävät ja tukevat toisiaan. Tärkeä havainto on, että business intelligence -prosessi on ennen kaikkea organisaation oppimisprosessi. Tästä seuraa, että minkä tahansa BI-prosessin tulisi perustua niihin prosesseihin, joiden avulla organisaatiot oppivat. Työssä esitetään myös, miten business intelligence, tietojohtaminen (knowledge management) ja organisaatioiden oppiminen liittyvät toisiinsa.Teknologiaseuranta on elintärkeä toiminto korkean teknologian yritykselle; sitä tarvitaan monella strategisen johtamisen osa-alueella, ainakin teknologia-, markkinointi- ja henkilöstöjohtamisessa. Teknologiaseurannan havaitaan myös olevan korkean teknologian yritykselle erittäin tärkeä ydinosaamisalue, jota ei voi kokonaan ulkoistaa.Työssä esitellään teknologiaseurantaprosessi, joka perustuu yleiselle business intelligence -prosessille ja siitä johdetulle kilpailuseurantaprosessille. Työssä myös esitetään ehdotus siitä, kuinka teknologiaseuranta voitaisiin järjestää korkean teknologian yrityksessä. Esitetty ratkaisu perustuu Community of practice -käsitteeseen. Community of practice on vapaaehtoisuuteen perustuva tiimi, jonka jäseniä yhdistää kiinnostus johonkin asiaan ja oppimishalu. Esimerkkiyrityksessä on tunnistettu selkeä tarve yhtenäiseen ja koordinoituun teknologiaseurantaan. Työssä esitetään alustava teknologiaseurantaprosessi esimerkkiyritykselle ja tunnistetaan teknologiaseurantaprosessin asiakkaat ja tekijät.

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.

A model for the evolution of reinforcement learning in fluctuating games

Many species are able to learn to associate behaviours with rewards as this gives fitness advantages in changing environments. Social interactions between population members may, however, require more cognitive abilities than simple trial-and-error learning, in particular the capacity to make accurate hypotheses about the material payoff consequences of alternative action combinations. It is unclear in this context whether natural selection necessarily favours individuals to use information about payoffs associated with nontried actions (hypothetical payoffs), as opposed to simple reinforcement of realized payoff. Here, we develop an evolutionary model in which individuals are genetically determined to use either trial-and-error learning or learning based on hypothetical reinforcements, and ask what is the evolutionarily stable learning rule under pairwise symmetric two-action stochastic repeated games played over the individual's lifetime. We analyse through stochastic approximation theory and simulations the learning dynamics on the behavioural timescale, and derive conditions where trial-and-error learning outcompetes hypothetical reinforcement learning on the evolutionary timescale. This occurs in particular under repeated cooperative interactions with the same partner. By contrast, we find that hypothetical reinforcement learners tend to be favoured under random interactions, but stable polymorphisms can also obtain where trial-and-error learners are maintained at a low frequency. We conclude that specific game structures can select for trial-and-error learning even in the absence of costs of cognition, which illustrates that cost-free increased cognition can be counterselected under social interactions.

Learning-induced gene expression in the heads of two Nasonia species that differ in long-term memory formation.

BACKGROUND: Cellular processes underlying memory formation are evolutionary conserved, but natural variation in memory dynamics between animal species or populations is common. The genetic basis of this fascinating phenomenon is poorly understood. Closely related species of Nasonia parasitic wasps differ in long-term memory (LTM) formation: N. vitripennis will form transcription-dependent LTM after a single conditioning trial, whereas the closely-related species N. giraulti will not. Genes that were differentially expressed (DE) after conditioning in N. vitripennis, but not in N. giraulti, were identified as candidate genes that may regulate LTM formation. RESULTS: RNA was collected from heads of both species before and immediately, 4 or 24 hours after conditioning, with 3 replicates per time point. It was sequenced strand-specifically, which allows distinguishing sense from antisense transcripts and improves the quality of expression analyses. We determined conditioning-induced DE compared to naïve controls for both species. These expression patterns were then analysed with GO enrichment analyses for each species and time point, which demonstrated an enrichment of signalling-related genes immediately after conditioning in N. vitripennis only. Analyses of known LTM genes and genes with an opposing expression pattern between the two species revealed additional candidate genes for the difference in LTM formation. These include genes from various signalling cascades, including several members of the Ras and PI3 kinase signalling pathways, and glutamate receptors. Interestingly, several other known LTM genes were exclusively differentially expressed in N. giraulti, which may indicate an LTM-inhibitory mechanism. Among the DE transcripts were also antisense transcripts. Furthermore, antisense transcripts aligning to a number of known memory genes were detected, which may have a role in regulating these genes. CONCLUSION: This study is the first to describe and compare expression patterns of both protein-coding and antisense transcripts, at different time points after conditioning, of two closely related animal species that differ in LTM formation. Several candidate genes that may regulate differences in LTM have been identified. This transcriptome analysis is a valuable resource for future in-depth studies to elucidate the role of candidate genes and antisense transcription in natural variation in LTM formation.