An introduction to video podcasts

This PowerPoint slideshow covers the educational uses of video podcasts, describes how RSS feeds work and shows how they can be created using Blackboard.

Learning Resource Coursework - Team Sigma

We have created a slideshow on Open Source, and have created a reference list and poster for it.

Copyright Questions: Making chapters from a book available to your students

This narrated slideshow (8 minutes) shows how UK copyright law applies to an example book and explores how a tutor can make copies of selected chapters to distribute to students

Using Panopto in a Common Learning Space

This narrated slideshow provides a step-by-step guide to recording a lecture in a CLS room using Panopto.

Copyright and DRM

A slideshow and an accompanying audio podcast about DRM and piracy, and a poster advertising them

Blackboard for teaching and learning

A slideshow and supporting handout used in a workshop that discusses how Blackboard can be used to effectively support student learning.

A guide to making your e-thesis available

This 10-minute presentation introduces e-theses, outlines their benefits and the issues they raise and describes the process requird to create and submit them. It is available as an Adobe Presenter slideshow, as an MP4 video and as a YouTube video with optional captions for accessibility.

INFO2009 Resource Examples

Slideshow demonstrating different types of possible resource. The presentation explains at the same time, some of the working methods which might be used when deciding upon format and researching exemplar resources

Inscripción del terrorismo en la agenda gubernamental estadounidense después de los ataques del 11 de septiembre de 2001

Este trabajo se enmarcará en la primera presidencia de George W. Bush y más específicamente entre el 11 de septiembre de 2001 cuando se dio el ataque a las torres gemelas y la invasión a Afganistán el 7 de octubre de este mismo año. En consecuencia lo que se busca con este estudio es demostrar que el gobierno estadounidense se ayuda de herramientas y elementos como la comunicación política, la fijación de agenda y el discurso para la inscripción del concepto terrorismo en la agenda gubernamental. Es así como genera un gran poder de influencia a nivel local logrando que los ciudadanos se tornen hacia el Estado y al mismo tiempo logra apoyo internacional generando el clima perfecto para legitimar la guerra anti-terrorista como una respuesta a los hechos ocurridos.

Análisis de la industria automotriz colombiana frente al Tratado de Libre Comercio con la República de Corea

Mediante este proyecto, se hace un análisis de la industria automotriz en Colombia, cómo se puede ver afectada y cuáles serán los pros y contras ante la puesta en ejecución del Tratado de Libre Comercio con la República de Corea, tomando como base diferentes agentes que incursionan directamente en la industria mencionada, como lo son sus consumidores, los comerciantes, productores (ensambladoras) y el gobierno nacional. Igualmente, la globalización como aspecto fundamental para las economías mundiales, genera la apertura de estas y afianza a su vez la firma de diferentes tratados que permitan mejorar el comercio y bajar los precios de bienes y servicios entre países; pero en este caso dicha apertura, puede no ser beneficiosa para la industria automotriz colombiana debido a las grandes diferencias en capacidad de producción y tecnología entre ambos países. Por lo anterior, se realizan comparaciones entre las dos economías y sus industrias (la automotriz), para encontrar los puntos en los cuales Colombia es más débil y buscar estrategias que permitan contrarrestar los efectos negativos que puede traer consigo el Tratado de Libre Comercio, así mismo, buscar oportunidades para mejorar el desarrollo tecnológico y de esta manera incentivar la inversión para consolidar dicha industria en el mercado.

Collaborative eLearning Assistant Network: caring agents are conscious agents

Would a research assistant - who can search for ideas related to those you are working on, network with others (but only share the things you have chosen to share), doesn’t need coffee and who might even, one day, appear to be conscious - help you get your work done? Would it help your students learn? There is a body of work showing that digital learning assistants can be a benefit to learners. It has been suggested that adaptive, caring, agents are more beneficial. Would a conscious agent be more caring, more adaptive, and better able to deal with changes in its learning partner’s life? Allow the system to try to dynamically model the user, so that it can make predictions about what is needed next, and how effective a particular intervention will be. Now, given that the system is essentially doing the same things as the user, why don’t we design the system so that it can try to model itself in the same way? This should mimic a primitive self-awareness. People develop their personalities, their identities, through interacting with others. It takes years for a human to develop a full sense of self. Nobody should expect a prototypical conscious computer system to be able to develop any faster than that. How can we provide a computer system with enough social contact to enable it to learn about itself and others? We can make it part of a network. Not just chatting with other computers about computer ‘stuff’, but involved in real human activity. Exposed to ‘raw meaning’ – the developing folksonomies coming out of the learning activities of humans, whether they are traditional students or lifelong learners (a term which should encompass everyone). Humans have complex psyches, comprised of multiple strands of identity which reflect as different roles in the communities of which they are part – so why not design our system the same way? With multiple internal modes of operation, each capable of being reflected onto the outside world in the form of roles – as a mentor, a research assistant, maybe even as a friend. But in order to be able to work with a human for long enough to be able to have a chance of developing the sort of rich behaviours we associate with people, the system needs to be able to function in a practical and helpful role. Unfortunately, it is unlikely to get a free ride from many people (other than its developer!) – so it needs to be able to perform a useful role, and do so securely, respecting the privacy of its partner. Can we create a system which learns to be more human whilst helping people learn?

Facebook & Blackboard: comparison of learner perspectives

Different systems, different purposes – but how do they compare as learning environments? We undertook a survey of students at the University, asking whether they learned from their use of the systems, whether they made contact with other students through them, and how often they used them. Although it was a small scale survey, the results are quite enlightening and quite surprising. Blackboard is populated with learning material, has all the students on a module signed up to it, a safe environment (in terms of Acceptable Use and some degree of staff monitoring) and provides privacy within the learning group (plus lecturer and relevant support staff). Facebook, on the other hand, has no learning material, only some of the students using the system, and on the face of it, it has the opportunity for slips in privacy and potential bullying because the Acceptable Use policy is more lax than an institutional one, and breaches must be dealt with on an exception basis, when reported. So why do more students find people on their courses through Facebook than Blackboard? And why are up to 50% of students reporting that they have learned from using Facebook? Interviews indicate that students in subjects which use seminars are using Facebook to facilitate working groups – they can set up private groups which give them privacy to discuss ideas in an environment which perceived as safer than Blackboard can provide. No staff interference, unless they choose to invite them in, and the opportunity to select who in the class can engage. The other striking finding is the difference in use between the genders. Males are using blackboard more frequently than females, whilst the reverse is true for Facebook. Interviews suggest that this may have something to do with needing to access lecture notes… Overall, though, it appears that there is little relationship between the time spent engaging with Blackboard and reports that students have learned from it. Because Blackboard is our central repository for notes, any contact is likely to result in some learning. Facebook, however, shows a clear relationship between frequency of use and perception of learning – and our students post frequently to Facebook. Whilst much of this is probably trivia and social chit chat, the educational elements of it are, de facto, contructivist in nature. Further questions need to be answered - Is the reason the students learn from Facebook because they are creating content which others will see and comment on? Is it because they can engage in a dialogue, without the risk of interruption by others?

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.