Assessment of Web Content Accessibility Levels in Spanish Official Online Education Environments

Diversity-based designing, or the goal of ensuring that web-based information is accessible to as many diverse users as possible, has received growing international acceptance in recent years, with many countries introducing legislation to enforce it. This paper analyses web content accessibility levels in Spanish education portals according to the international guidelines established by the World Wide Web Consortium (W3C) and the Web Accessibility Initiative (WAI). Additionally, it suggests the calculation of an inaccessibility rate as a tool for measuring the degree of non-compliance with WAI Guidelines 2.0 as well as illustrating the significant gap that separates people with disabilities from digital education environments (with a 7.77% average). A total of twenty-one educational web portals with two different web depth levels (42 sampling units) were assessed for this purpose using the automated analysis tool Web Accessibility Test 2.0 (TAW, for its initials in Spanish). The present study reveals a general trend towards non-compliance with the technical accessibility recommendations issued by the W3C-WAI group (97.62% of the websites examined present mistakes in Level A conformance). Furthermore, despite the increasingly high number of legal and regulatory measures about accessibility, their practical application still remains unsatisfactory. A greater level of involvement must be assumed in order to raise awareness and enhance training efforts towards accessibility in the context of collective Information and Communication Technologies (ICTs), since this represents not only a necessity but also an ethical, social, political and legal commitment to be assumed by society.

An Architecture by means of Anthropology. Beyond learning the tools of social science

Los arquitectos y urbanistas tienen una larga tradición en el aprendizaje de las herramientas de las ciencias sociales, especialmente las que les permiten analizar y describir mejor los entornos y las personas para las que trabajan. Esto ha llevado a los arquitectos a desarrollar mejores herramientas de observación y descripción del ámbito social y no sólo el material. Sin embargo, la mayoría de las veces este acercamiento interdisciplinar ha identificado las ciencias sociales, especialmente la antropología, con la etnografía. Este artículo parte de la crítica a esta identificación hecha por el antropólogo Tim Ingold y se centra en lo que él propone como el método central de la antropología, la observación participante. Para después revisar varias propuestas actuales de científicos sociales que tratan de desarrollar una disciplina no representacional y orientada al futuro, un objetivo más cercano al de la arquitectura. El artículo intenta imaginar cómo esta práctica transdisciplinar podría desarrollarse.

How to Use Cooperative Learning for Assessing Students’ Emotional Competences: A Practical Example at the Tertiary Level

Cooperative learning allows students acquisition of competences that are essential for the labour market such as leadership, critical thinking, communication, and so on. For this reason, different cooperative activities were designed in a language subject in English Studies so that students could work in groups and acquire those competences. This article describes some such activities and the emotional competences that students acquire with them. Moreover, a survey was conducted in order to establish students’ opinions about the main competences they acquired with the activities designed and their opinion about a cooperative methodology. Students’ answers were positive and they were aware of what they had learned.

Applied language learning.

No longer distributed to depository libraries in tangible format, .

Teaching College Writing in a High School Setting: The Impact of Concurrent Enrollment on Teacher Learning and Practice

Thesis (Ph.D.)--University of Washington, 2016-06

Simulating Nursing: Rhetoric, Materiality, and Disciplinary Learning

Thesis (Ph.D.)--University of Washington, 2016-06

Problem-based learning: a case study in providing e-health education using the Internet

The current trend among many universities is to increase the number of courses available online. However, there are fundamental problems in transferring traditional education courses to virtual formats. Delivering current curricula in an online format does not assist in overcoming the negative effects on student motivation which are inherent in providing information passively. Using problem-based learning (PBL) online is a method by which computers can become a tool to encourage active learning among students. The delivery of curricula via goal-based scenarios allows students to learn at different rates and can successfully shift online learning from memorization to discovery. This paper reports on a Web-based e-health course that has been delivered via PBL for the past 12 months. Thirty distance-learning students undertook postgraduate courses in e-health delivered via the Internet (asynchronous communication). Data collected via online student surveys indicated that the PBL format was both flexible and interesting. PBL has the potential to increase the quality of the educational experience of students in online environments.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup)

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robot’s action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robot’s navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Filtering duplicate items over distributed data streams

In recent years many real time applications need to handle data streams. We consider the distributed environments in which remote data sources keep on collecting data from real world or from other data sources, and continuously push the data to a central stream processor. In these kinds of environments, significant communication is induced by the transmitting of rapid, high-volume and time-varying data streams. At the same time, the computing overhead at the central processor is also incurred. In this paper, we develop a novel filter approach, called DTFilter approach, for evaluating the windowed distinct queries in such a distributed system. DTFilter approach is based on the searching algorithm using a data structure of two height-balanced trees, and it avoids transmitting duplicate items in data streams, thus lots of network resources are saved. In addition, theoretical analysis of the time spent in performing the search, and of the amount of memory needed is provided. Extensive experiments also show that DTFilter approach owns high performance.

Context-enhanced authentication for infrastructureless network environments

Infrastructureless networks are becoming more popular with the increased prevalence of wireless networking technology. A significant challenge faced by these infrastructureless networks is that of providing security. In this paper we examine the issue of authentication, a fundamental component of most security approaches, and show how it can be performed despite an absence of trusted infrastructure and limited or no existing trust relationship between network nodes. Our approach enables nodes to authenticate using a combination of contextual information, harvested from the environment, and traditional authentication factors (such as public key cryptography). Underlying our solution is a generic threshold signature scheme that enables distributed generation of digital certificates.

Virtual training environments to improve train driver's crisis decision making

This paper reports on a current research project in which virtual reality simulators are being investigated as a means of simulating hazardous Rail work conditions in order to allow train drivers to practice decision-making under stress. When working under high stress conditions train drivers need to move beyond procedural responses into a response activated through their own problem-solving and decision-making skills. This study focuses on the use of stress inoculation training which aims to build driver’s confidence in the use of new decision-making skills by being repeatedly required to respond to hazardous driving conditions. In particular, the study makes use of a train cab driving simulator to reproduce potentially stress inducing real-world scenarios. Initial pilot research has been undertaken in which drivers have experienced the training simulation and subsequently completed surveys on the level of immersion experienced. Concurrently drivers have also participated in a velocity perception experiment designed to objectively measure the fidelity of the virtual training environment. Baseline data, against which decision-making skills post training will be measured, is being gathered via cognitive task analysis designed to identify primary decision requirements for specific rail events. While considerable efforts have been invested in improving Virtual Reality technology, little is known about how to best use this technology for training personnel to respond to workplace conditions in the Rail Industry. To enable the best use of simulators for training in the Rail context the project aims to identify those factors within virtual reality that support required learning outcomes and use this information to design training simulations that reliably and safely train staff in required workplace accident response skills.

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

Building learning communities to support beginning teachers use of technology

This paper reports on the early stages of a three year study that is investigating the impact of a technology-enriched teacher education program on beginning teachers' integration of computers, graphics calculators, and the internet into secondary school mathematics classrooms. Whereas much of the existing research on the role of technology in mathematics learning has been concerned with effects on curriculum content or student learning, less attention has been given to the relationship between technology use and issues of pedagogy, in particular the impact on teachers' professional learning in the context of specific classroom and school environments. Our research applies sociocultural theories of learning to consider how beginning teachers are initiated into a collaborative professional community featuring both web-based and face to face interaction, and how participation in such a community shapes their pedagogical beliefs and practices. The aim of this paper is to analyse processes through which the emerging community was established and sustained during the first year of the study. We examine features of this community in terms of identity formation, shifts in values and beliefs, and interaction patterns revealed in bulletin board discussion between students and lecturers.

Development of a co-operative distributed process mining system for quality assurance

In this paper, a co-operative distributed process mining system (CDPMS) is developed to streamline the workflow along the supply chain in order to offer shorter delivery times, more flexibility and higher customer satisfaction with learning ability. The proposed system is equipped with the ‘distributed process mining’ feature which is used to discover the hidden relationships among each working decision in distributed manner. This method incorporates the concept of data mining and knowledge refinement into decision making process for ensuring ‘doing the right things’ within the workflow. An example of implementation is given, based on the case of slider manufacturer.