An online e-Learning authoring tool to create interactive multi-device learning objects using e-Infrastructure resources

Education can take advantage of e-Infrastructures to provide teachers with new opportunities to increase students' motivation and engagement while they learn. Nevertheless, teachers need to find, integrate and customize the resources provided by e-Infrastructures in an easy way. This paper presents ViSH Editor, an innovative web-based e-Learning authoring tool that aims to allow teachers to create new learning objects using e-Infrastructure resources. These new learning objects are called Virtual Excursions and are created as reusable, granular and interoperable learning objects. This way they can be reused to build new ones and they can be integrated in websites or Learning Management Systems. Details about the design, development and the tool itself are explained in this paper as well as the concept, structure and metadata of the new learning objects. Lastly, some real examples of how to enrich learning using Virtual Excursions are exposed.

Generation of human computational models with machine learning

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

Autonomous Acquisition of Natural Situated Communication

An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

Una contribución a la programación cognitiva: arquitecturas de segunda generación para representación del conocimiento

La tesis propone el concepto y diseño de una arquitectura cognitiva para representación de conocimiento profesional especializado en clases de dominios relacionados con el mundo físico. Constituye una extensión de los trabajos de B.Chandrasekaran, potenciando el concepto de arquitectura basada en tareas genéricas propuesta por dicho autor. En base a la arquitectura propuesta, se ha desarrollado un entorno como herramienta de construcción de sistemas expertos de segunda generación, así como un lenguaje para programación cognitiva (DECON)- Dicho entorno, programado en lenguaje C sobre UNIX, ha sido utilizado para el desarrollo de un sistema para predicción de avenidas en la Cuenca Hidrográfica del Jucar, en el marco del proyecto SAIH. Primeramente, la tesis plantea el problema de la modelización del comportamiento de los sistemas físicos, reflejando las limitaciones de las formas clásicas de representación del conocimiento para abordar dicho problema, así como los principales enfoques más recientes basados en el concepto de arquitectura cognitiva y en las técnicas de simulación cualitativa. Se realiza después una síntesis de la arquitectura propuesta, a nivel del conocimiento, para detallar posteriormente su desarrollo a nivel simbólico y de implementación, así como el método general para la construcción de modelos sobre la arquitectura. Se muestra también un resumen de los principales aspectos del desarrollo de software. Finalmente, en forma de anejos, se presenta un caso de estudio, el sistema SIRAH (Sistema Inteligente de Razonamiento Hidrológico), junto con la gramática formal del lenguaje de soporte para la definición de modelos.---ABSTRACT---The thesis proposes the concept and design of a cognitive architecture for professional knowledge representation, specialized in domain classes related to the physical world. It is an extensión of the Chandrasekaran's work, improving the concept of Generic Task based architecture introduced by this author. Based on the proposed architecture, an environment has been developed, as a case of second generation building expert systems tool, as well as a language for cognitive programming (DECON). The environment, programmed in C lenguage on UNIX operating system, has been used to develop a system for flood prediction in the Jucar watershed, inside of the SAIH project. Firstly, the behavior modeling problem of physical systems is discussed, showing the limitations of the classical representations to tackle it, beside the most recent approaches based on cognitive architecture concepts and qualitative simulation technique. An overview of the architecture at the knowledge level is then made, being followed by its symbolic and implementation level description, as well as a general guideline for building models on top of the architecture. The main aspects of software development are also introduced. Finaly, as annexes, a case of study -the SIRAH system (Sistema Inteligente de RAzonamiento Hidrológico)- is introduced, along with the formal grammar of the support language for model definition.

Formation of temporal-feature maps by axonal propagation of synaptic learning

Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.

Teaching as a fractal: from experience to model

The aim of this work is to improve students’ learning by designing a teaching model that seeks to increase student motivation to acquire new knowledge. To design the model, the methodology is based on the study of the students’ opinion on several aspects we think importantly affect the quality of teaching (such as the overcrowded classrooms, time intended for the subject or type of classroom where classes are taught), and on our experience when performing several experimental activities in the classroom (for instance, peer reviews and oral presentations). Besides the feedback from the students, it is essential to rely on the experience and reflections of lecturers who have been teaching the subject several years. This way we could detect several key aspects that, in our opinion, must be considered when designing a teaching proposal: motivation, assessment, progressiveness and autonomy. As a result we have obtained a teaching model based on instructional design as well as on the principles of fractal geometry, in the sense that different levels of abstraction for the various training activities are presented and the activities are self-similar, that is, they are decomposed again and again. At each level, an activity decomposes into a lower level tasks and their corresponding evaluation. With this model the immediate feedback and the student motivation are encouraged. We are convinced that a greater motivation will suppose an increase in the student’s working time and in their performance. Although the study has been done on a subject, the results are fully generalizable to other subjects.

The orchestration of modes and EFL audio-visual comprehension: A multimodal discourse analysis of vodcasts

This thesis explores the role of multimodality in language learners’ comprehension, and more specifically, the effects on students’ audio-visual comprehension when different orchestrations of modes appear in the visualization of vodcasts. Firstly, I describe the state of the art of its three main areas of concern, namely the evolution of meaning-making, Information and Communication Technology (ICT), and audio-visual comprehension. One of the most important contributions in the theoretical overview is the suggested integrative model of audio-visual comprehension, which attempts to explain how students process information received from different inputs. Secondly, I present a study based on the following research questions: ‘Which modes are orchestrated throughout the vodcasts?’, ‘Are there any multimodal ensembles that are more beneficial for students’ audio-visual comprehension?’, and ‘What are the students’ attitudes towards audio-visual (e.g., vodcasts) compared to traditional audio (e.g., audio tracks) comprehension activities?’. Along with these research questions, I have formulated two hypotheses: Audio-visual comprehension improves when there is a greater number of orchestrated modes, and students have a more positive attitude towards vodcasts than traditional audios when carrying out comprehension activities. The study includes a multimodal discourse analysis, audio-visual comprehension tests, and students’ questionnaires. The multimodal discourse analysis of two British Council’s language learning vodcasts, entitled English is GREAT and Camden Fashion, using ELAN as the multimodal annotation tool, shows that there are a variety of multimodal ensembles of two, three and four modes. The audio-visual comprehension tests were given to 40 Spanish students, learning English as a foreign language, after the visualization of vodcasts. These comprehension tests contain questions related to specific orchestrations of modes appearing in the vodcasts. The statistical analysis of the test results, using repeated-measures ANOVA, reveal that students obtain better audio-visual comprehension results when the multimodal ensembles are constituted by a greater number of orchestrated modes. Finally, the data compiled from the questionnaires, conclude that students have a more positive attitude towards vodcasts in comparison to traditional audio listenings. Results from the audio-visual comprehension tests and questionnaires prove the two hypotheses of this study.

The importance of promoting multimodal teaching in the foreign language classroom for the acquisition of social competences: practical examples

This article analyses the way in which the subject English Language V of the degree English Studies (English Language and Literature) combines the development of the five skills (listening, speaking, reading, writing and interacting) with the use of multimodal activities and resources in the teaching-learning process so that students increase their motivation and acquire different social competences that will be useful for the labour market such as communication, cooperation, leadership or conflict management. This study highlights the use of multimodal materials (texts, videos, etc.) on social topics to introduce cultural aspects in a language subject and to deepen into the different social competences university students can acquire when they work with them. The study was guided by the following research questions: how can multimodal texts and resources contribute to the development of the five skills in a foreign language classroom? What are the main social competences that students acquire when the teaching-learning process is multimodal? The results of a survey prepared at the end of the academic year 2015-2016 point out the main competences that university students develop thanks to multimodal teaching. For its framework of analysis, the study draws on the main principles of visual grammar (Kress & van Leeuwen, 2006) where students learn how to analyse the main aspects in multimodal texts. The analysis of the different multimodal activities described in the article and the survey reveal that multimodality is useful for developing critical thinking, for bringing cultural aspects into the classroom and for working on social competences. This article will explain the successes and challenges of using multimodal texts with social content so that students can acquire social competences while learning content. Moreover, the implications of using multimodal resources in a language classroom to develop multiliteracies will be observed.

The independent effects of attention and lead stimulus properties on the acoustic blink reflex

The effects of attention to a lead stimulus and of its sensory properties on modulation of the acoustic blink reflex were investigated. Participants performed a reaction time task cued by an acoustic or a visual lead stimulus. In Experiment 1, half the participants were presented with sustained lead stimuli. For the remainder, the lead stimulus was discrete and consisted of two brief presentations that marked the onset and offset of a stimulus-free interval. In Experiment 2, sustained lead stimuli were presented at a low or high intensity. The attentional demands of the task enhanced blink latency and magnitude modulation during acoustic and visual lead stimuli, with blink modulation being largest at a late point during the lead stimulus. Independent of the attentional effects, blink latency and magnitude modulation were larger during sustained than during discrete acoustic lead stimuli, whereas there was no difference for visual lead stimuli. Increases in the intensity of the lead stimulus enhanced blink modulation regardless of lead stimulus modality. Attention to a lead stimulus and the properties of the lead stimulus appear to have independent effects on blink reflex modulation.

Attending to the distractor and old/new discriminations in negative priming

When participants ignore an irrelevant distractor they typically show impaired responding to that item if it becomes the relevant stimulus on a subsequent trial. In Experiment 1 (N = 64), a masked white colour name was presented briefly before a Stroop display. Negative priming in colour naming occurred when the colour of the lettering for the Stroop stimulus matched the colour name displayed in the first display, consistent with the proposal of temporal discrimination theory that negative priming arises because a recurrence of an unattended stimulus cannot readily be classified as old or new. Experiment 2 (N = 32) replicated negative priming in the interleaved-word display where participants had to name the red word from a pair of red and green words. In Experiment 3 (N = 32) and Experiment 4 (N = 28) the participants were required to attend to but not respond to the words in the prime display and name one of two interleaved words in the probe display. Negative priming was observed in this arrangement, consistent with the episodic retrieval theory of negative priming. The temporal discrimination model may need to be extended to situations in which the attended stimuli have different responses attached to them.

Scaffolding and bilingual shared reading experiences: Promoting primary school students' learning and development

This paper explores the connections between scaffolding, second language learning and bilingual shared reading experiences. A socio- cultural theory of cognition underpins the investigation, which involved implementing a language and culture awareness program (LCAP) in a year 4 classroom and in the school community. Selected passages from observations are used to analyse the learning of three students, particularly in relation to languages other than English (LOTE). As these three case study students interacted in the classroom, at home and in the community, they co-constructed, appropriated and applied knowledge form one language to another. Through scaffolding, social spaces were constructed, where students learning and development were extended through a variety of activities that involved active participation, such as experimenting with language, asking questions and making suggestions. Extending these opportunities for student learning and development is considered in relation to creating teaching and learning environments that celebrate socio-cultural and linguistic diversity.

Does the type of concurrent task affect preferred and cued gait in people with Parkinson's disease?

Difficulty performing more than one task at a time is common in people with Parkinson's disease, resulting in interference with one or both tasks. While studies have shown that greater interference in gait occurs with more complex concurrent tasks, the impact of the type of concurrent task is unclear in the Parkinson's population. Thus the first purpose of this study was to investigate the effect of the concurrent task (calculation, language, or motor) on gait in people with Parkinson's disease. As visual cues are commonly used to aid stride regulation in people with Parkinson's disease, the second purpose of this study was to determine whether this method of increasing stride length was still effective if other tasks were performed simultaneously. Sixteen patients with Parkinson's disease and 16 gender- and age-matched controls performed six cognitive and motor concurrent tasks when seated, walking 10 m, and walking over visual cues. Stride length decreased in people with Parkinson's disease when performing the concurrent calculation and language tasks, but not with the motor task. The language task was more complex than the calculation task, thus the effect was not due to task complexity alone. Visual cues were effective in improving stride length whist maintaining velocity in people with Parkinson's disease, even when performed under dual task conditions. These findings highlight the importance of the task when assessing and retraining dual tasking during gait, and suggest that retraining dual tasking can occur whilst simultaneously using visual aids to regulate stride length.

Intelligent agent supported personalization for virtual learning environments

Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Rapport-building through call in teaching Chinese as a foreign language: An exploratory study

Technological advances have brought about the ever-increasing utilisation of computer-assisted language learning ( CALL) media in the learning of a second language (L2). Computer-mediated communication, for example, provides a practical means for extending the learning of spoken language, a challenging process in tonal languages such as Chinese, beyond the realms of the classroom. In order to effectively improve spoken language competency, however, CALL applications must also reproduce the social interaction that lies at the heart of language learning and language use. This study draws on data obtained from the utilisation of CALL in the learning of L2 Chinese to explore whether this medium can be used to extend opportunities for rapport-building in language teaching beyond the face-to-face interaction of the classroom. Rapport's importance lies in its potential to enhance learning, motivate learners, and reduce learner anxiety. To date, CALL's potential in relation to this facet of social interaction remains a neglected area of research. The results of this exploratory study suggest that CALL may help foster learner-teacher rapport and that scaffolding, such as strategically composing rapport-fostering questions in sound-files, is conducive to this outcome. The study provides an instruction model for this application of CALL.