Studentship Vacancies
The Knowledge Media Institute (KMi) is home to internationally recognised researchers in semantic technologies, educational multimedia, collaboration technologies, artificial intelligence, cognitive science, and human-computer interaction. KMi offers students an intellectually challenging environment with exceptional research and computer facilities.
We are currently offering fully-funded studentships commencing October 2012. Applications are invited from UK, EU and international students for full-time, 3-year study on the following PhD projects:
- Empowering Self-Regulated Learning within Personal Learning Environments
- Exploratory knowledge media analysis
- Learning analytics for learning power
- Lifestyle logs
- Linking nature to databases with your smartphone
- Opinion Diffusion Analysis in the Social Web
- Shared web-based representations to support learning
- Visual Exploration of Research Spaces
- Web data mining
- What makes a good picture?
All applicants must have a first or upper second class degree from a UK university or the overseas equivalent and ideally a relevant Masters degree. Unless from a majority English-speaking country, non-EEA applicants will require an IELTS score of 6.5 with a minimum of 6 in each element of Listening, Reading, Speaking and Writing. IELTS Certificates are valid for a period of 2-years. All applications are assessed as to their quality, the fit with The Open University research priorities and the availability of supervisors in the relevant field.
Deadline: 7th June 2012
Empowering Self-Regulated Learning within Personal Learning Environments
Self-regulated learning (SRL) is a term that describes an individual's ability to learn how to learn. In other words, each of us can develop a wide-ranging skill set that enables us to learn in a number of different ways. In some university settings the term SRL is more commonly described as "independent learning" or "auto-didactic learning". This project is about supporting SRL through learning tools and services, such as recommenders of learning resources. These tools and services will enable learners to define their learning goals, build their online Personal Learning Environment (PLE) and use it actively in order to reach their learning goals and monitor their own progress...Read more.(Deadline 7th June 2012)
Exploratory Knowledge Media Analysis
An abundance of research papers and learning materials are shared today digitally on the web, often with open, machine-readable access available for free. At the same time, virtual presence solutions such as FlashMeeting create ample opportunity for online collaboration as part of the daily routine. Bringing online collaboration together with exploratory knowledge media analysis is the key in creating "new discovery and innovation processes for individuals, groups, and communities" (Shneiderman, 2007, p.29). Novel technology-enhanced learning and information retrieval technologies need to provide facilities for exploratory search, facilitate collaboration, help keep rich histories, and provide multilayered interfaces with functionality growing alongside the users (cf. Shneiderman et al., 2006; Resnick et al., 2005).(Deadline 7th June 2012)
Learning Analytics for Learning Power
Intrinsic motivation to engage in learning (whether formal/informal, or academic/workplace) is known to be a function of a learner's dispositions towards learning. When these are fragile, learners often disengage when challenged, and are passive, lacking vital personal qualities such as resilience, curiosity and creativity needed to thrive in today's complex world. Learning Analytics seek to improve learning by making the optimal use of the growing amounts of data that are becoming available to, and about, learners. Dispositional Learning Analytics seek specifically to build stronger learning dispositions (note that these are not 'learning styles', which have a dubious conceptual basis). One particularly promising approach models dispositions as a 7-dimensional construct called Learning Power, measured through self-report data. A web application generates real time personal and cohort analytics, which have been shown to impact learners, educators, and organizational leaders, and the underlying platform pools data from >50,000 profiles, which in combination with other datasets, enables deeper analytics. As a form of Social Learning Analytic, in combination with Discourse-Centric Analytics and Social Network Analytics for learning, our strategic goal is to provide a suite of analytics that can help learners grow in Learning Power, and ultimately, build their capacity as life-long, life-wide learners...Read more.(Deadline 7th June 2012)
Lifestyle Logs
The ambition of this project is to analyse lifestyle pictures that users take with their smartphones of meals they eat, drinks they have, sports they do, etc: The tasks are to classify these pictures automatically recognising the activity, measuring and logging automatically as much relevant data as is possible for these activities. The research for this project is firmly placed in the areas of image retrieval and machine learning...Read more.(Deadline 7th June 2012)
Linking nature to databases with your smartphone
You will research and develop analysis tools that are able to look up smartphone snaps of certain types of natural objects (eg, rocks or butterflies) in image databases. These tools are meant to support not only image search but also interactive image browsing activities by exploiting partial visual aspects such as colour and texture...Read more.(Deadline 7th June 2012)
Opinion Diffusion Analysis in the Social Web
In the online social media space, it is often observed that users connected with each other are likely to express similar opinions. Such connections can be established by either explicit connections, e.g., a user follows another in Twitter or one is another's friend in Facebook, or social interactions, e.g., a user retweets others' messages in Twitter or users express their support on someone's post by clicking on the "Like" button in Facebook. Such social interactions are often viewed as endorsements of one's support of another's opinion. While opinion diffusion patterns might be created by social influence, they might also be created because of dyadic similarities among neighbouring nodes in social networks without causal influence (homophily), or external influences such as marketing or mass advertising (confounding factors). This PhD project aims to investigate what factors influence opinion formation and how opinions diffuse over implicit social networks on the social web using techniques from statistical modelling, machine learning, natural language processing, and data mining...Read more.(Deadline 7th June 2012)
Shared web-based representations to support learning
Technology-enhanced learning over the web offers an opportunity for communication between students and tutors that exploits the immediacy of the web as a channel for communication rather than just a channel for information distribution. Recent developments in web standards for interactive interfaces (i.e. AJAX and HTML5) and distributed services (i.e. REST and SOAP) provide the technical means for interacting with models, simulations and visualisations. These dynamic representations are used most effectively within educational situations where they offer a pedagogical advantage over the real thing. For example, a virtual microscope enables every user to view the same sample at the same time, which is not physically possible when using a set of real microscopes and samples. Within the context of group work and collaboration, shared representations provide an opportunity for multiple users to interact with the same representation simultaneously. A shared virtual microscope, for example, provides an opportunity for a group of users to work together on the same equipment, rather than working on identical (but independent) replicas. In this way, shared models, simulations and visualisations can be used within learning activities to enable students to demonstrate and explain their understanding of dynamic systems and processes...Read more.(Deadline 7th June 2012)
Visual Exploration of Research Spaces
A PhD studentship is available at the Knowledge Media Institute of the Open University on the Visual Exploration of Research Spaces. This project is inherently interdisciplinary and the successful candidate will contribute to our established research in one or more areas, including human-computer interaction, semantic, statistical and natural language technologies. The main aim of this project is to investigate methods for improving the ability of users to explore the rich set of data which are now available about scholarly research, by developing i) new knowledge-based methods for aggregating data from both traditional (e.g., bibliographic servers) and other sources (e.g., blogs, tweets, conference web sites, etc), as well as ii) novel visual analytics solutions, able to support a seamless and flexible exploration of this rich set of aggregated types of data. In particular, we are interested in building on the work carried out on the KC-Viz system for ontology navigation and visualization - http://kmi.open.ac.uk/technologies/name/kc-viz, which relies on a novel abstraction mechanism based on the notion of key concepts, which denote the most important elements of an ontology and act as 'islands' to structure the exploration process and abstract from the large space of concepts in an ontology. Thus, we are interested in developing new methods that can employ this navigation metaphor in the context of research spaces, by identifying the appropriate notions and abstraction techniques, which apply in the research domain...Read more.(Deadline 7th June 2012)
Web Data Mining
The Web is currently being flooded with data, from information reported in documents for human consumption to, more and more, open data available in structured and reusable forms (APIs, linked data, etc.) While a lot of efforts have been dedicated to the integration of data, using conceptual models such as ontologies, we are now facing the unprecedented need for support in "interpreting" data gathered from a large number of distributed, heterogeneous and un-controlled sources on the Web. In this PhD studentship, which is inter-disciplinary in nature, the aim is to investigate the combination of ontology-based, top-down approaches to data interpretation, with techniques originating from data mining to make sense of data through the bottom-up emergence of meaningful information patterns. Contributions are therefore expected a the areas of the Semantic Web, linked data, ontology engineering, data mining, data analytics and machine learning...Read more.(Deadline 7th June 2012)
What makes a good picture?
This PhD project aims at uncovering the secrets of a good photograph. You are expected to develop computational algorithms that can set aside the very best photos of a set of similar photos - based on photographic design principles, trained with decisions taken by users, and for example based on learning from user comments on public photo sharing sites such as flickr and picassa. You will research and derive suitable high and low-level features from digital images that allow classification of photos as "good" and that allow categorisation of the emotive content of a digital image. You might use principles of simplicity (objects can easily be separated from the background), realism (eg, particular use of colour palette), basic techniques (right exposure, have areas with distinct focus, suitable colour, intensity and sharpness contrast) and composition principles. Armed with these features you will study, deploy, devise and modify machine learning algorithms that predict which photos make good representatives out of a bigger set of photographs...Read more.(Deadline 7th June 2012)
