Backpack – Person Centred Health, Care and Wellbeing

The proposal seeks to understand the personal behaviours, journeys and access points of Multiple Sclerosis (MS) citizens, in order to build out an eco-system for a Personal Data Store (PDS) and elicit issues around personal control over personal data. Research and recent reports highlight the urgent need for more integrated person-centred services as a means of delivering better patient outcomes, better clinical outcomes and better economic outcomes. Different implementation scenarios carry different configurations of cost, risks and benefits for different stakeholding gro ups, and the implementation of digital services has suffered in the past from lack of co-production or consultation with people and stakeholders on the ground before implementation. The proposed project will enable a group of citizen participants (plus organisations and their representatives) to interact in person-centred scenarios. These individuals may have long termconditions or professional interests with such condition – we have identified Multiple Sclerosis (MS) as a potential starting point – and we will identify needs, barriers, benefits and co-produce implementation scenarios

Applying the DeFT Framework to the Design of Multi-Representational Instructional Simulations

Learning environments use multiple external representations (MERs) in the hope that learners can benefit from the properties of each representation and ultimately achieve a deeper understanding of the subject being taught. Research on whether MERs do confer these additional advantages has shown that learning can be facilitated but only if learners can manage the complex tasks associated with their use. Our approach examines how the design of learning environments influences the cognitive task demands required of the learner with the longer term goal of using these findings to develop more adaptive and supportive multi-representational environments. In this paper, we begin by summarising the key features of the DeFT framework and then illustrate how such a framework can be used to classify existing systems. The main body of the paper describes the architecture of an instructional simulation that embodies DeFT. Finally, we conclude by illustrating the research questions we hope that experiments with this system can answer

Opening up the interpretation process in an open learner model

Opening a model of the learner is a potentially complex operation. There are many aspects of the learner that can be modelled, and many of these aspects may need to be opened in different ways. In addition, there may be complicated interactions between these aspects which raise questions both about the accuracy of the underlying model and the methods for representing a holistic view of the model. There can also be complex processes involved in inferring the learner's state, and opening up views onto these processes - which leads to the issues that are the main focus of this paper: namely, how can we open up the process of interpreting the learner's behaviour in such a manner that the learner can both understand the process and challenge the interpretation in a meaningful manner. The paper provides a description of the design and implementation of an open learner model (termed the xOLM) which features an approach to breaking free from the limitations of "black box" interpretation. This approach is based on a Toulmin-like argumentation structure together with a form of data fusion based on an adaptation of Dempster-Shafer. However, the approach is not without its problems. The paper ends with a discussion of the possible ways in which open learner models might open up the interpretation process even more effectively

Towards a learner modelling engine for the Semantic Web

We describe XLM, the learner modelling subsystem of LEACTIVEMATH, from the viewpoint of how it makes use of technologies associated with the Semantic Web. We discuss how a better usage of these technologies could make of XLM a more generic learner modelling engine to serve a variety of elearning systems. We try to foresee important issues to be addressed and difficult problems to be solved in the way to this goal

Connecting the 3D DGS Calques3D with the CAS Maple

Many (2D) Dynamic Geometry Systems (DGSs) are able to export numeric coordinates and equations with numeric coefficients to Computer Algebra Systems (CASs). Moreover, different approaches and systems that link (2D) DGSs with CASs, so that symbolic coordinates and equations with symbolic coefficients can be exported from the DGS to the CAS, already exist. Although the 3D DGS Calques3D can export numeric coordinates and equations with numeric coefficients to Maple and Mathematica, it cannot export symbolic coordinates and equations with symbolic coefficients. A connection between the 3D DGS Calques3D and the CAS Maple, that can handle symbolic coordinates and equations with symbolic coefficients, is presented here. Its main interest is to provide a convenient time-saving way to explore problems and directly obtain both algebraic and numeric data when dealing with a 3D extension of "ruler and compass geometry". This link has not only educational purposes but mathematical ones, like mechanical theorem proving in geometry, geometric discovery (hypotheses completion), geometric loci finding... As far as we know, there is no comparable "symbolic" link in the 3D case, except the prototype 3D-LD (restricted to determining algebraic surfaces as geometric loci)

Using student experience as a model for designing an automatic feedback system for short essays

The SAFeSEA project (Supportive Automated Feedback for Short Essay Answers) aims to develop an automated feedback system to support university students as they write summative essays. Empirical studies carried out in the initial phase of the system’s development illuminated students’ approaches to and understandings of the essay-writing process. Findings from these studies suggested that, regardless of their experience of higher education, students consider essay-writing as: 1) a sequential set of activities, 2) a process that is enhanced through particular sources of support and 3) a skill that requires the development of personal strategies. Further data collected from tutors offered insight into the feedback and reflection stages of essay-writing. These perspectives offered a fundamental model of essay-writing and feedback to inform the ongoing, iterative development of this automated feedback system and indeed, for any institution developing tools to support students’ writing

OpenEssayist: extractive summarisation and formative assessment of free-text essays

OpenEssayist is a system which is currently under development. It aims to provide an effective automated interactive feedback system that yields an acceptable level of support for university students writing summative essays. The principal natural language processing technique currently employed is extractive summarisation using graph-based ranking algorithms. OpenEssayist will be piloted in September 2013 with Open University UK students following a Master’s course of study

OpenEssayist: an automated feedback system that supports university students as they write summative essays

OpenEssayist is an automated, interactive feedback system designed to provide an acceptable level of support for students as they write essays for summative assessment. There are two main components to the system: (1) a linguistic analysis engine and (2) a web application that generates feedback for students The main pedagogical challenge in the e-assessment of free text is how to provide meaningful “advice for action” in order to support students writing their summative assessments. We have built a first working version of the system in which we use unsupervised graph-based ranking algorithms (following Mihalcea & Tarau, 2005) to automatically extract key words, phrases and sentences from student essays. We have developed several external representations of these summarisation techniques. For examples, key words and key phrases can be viewed in a word cloud or in a dispersion graph, and they can be explored and organised into groups. Holistic approaches have also been tested using ‘mash ups’ where key words and key sentences are highlighted in context in the essay itself, helping students to investigate the distribution of key words and its potential implications for the clarity of the narrative. This paper will report the findings from our pilot studies of the interactive models associated with the summarisation techniques

An exploration of the features of graded student essays using domain-independent natural language processing techniques

This paper presents observations that were made about a corpus of 135 graded student essays by analysing them with a computer program that we are designing to provide automated formative feedback on draft essays. In order to provide individualised feedback to help students to improve their essays, the program carries out automatic essay structure recognition and uses domain-independent graph-based ranking techniques to derive extractive summaries. These procedures generate data concerning an essay’s organisational structure and its discourse structure. We have selected 27 attributes from the data and used them in a comparative analysis of all the essays with a view to informing further development of the feedback program. The results of this analysis suggest that some characteristics of students’ essays that our domain-independent feedback program is measuring may be related to the grades that tutors assign to their essays

Designing and testing visual representations of draft essays for higher education students

This paper reports the findings of an empirical investigation, which set out to test a set of rainbow essay exercises. The rainbow diagrams are pictorial representations of formal graphs that are derived automatically from student essays. They were designed to allow students to discover how key concepts in a well written essay are connected together. The students would then be able to compare a rainbow diagram of their own essay with a good essay and make changes to it before submission to their tutor. However a trail was undertaken with academics, teaching and learning staff, doctoral students at the Open University of Catalonia and the Open University UK, before implementation into the web application known as Open Essayist. All the participants from each University completed the exercise correctly. This was a surprising finding as we expected participants to experience some difficulties, as previous visual representations we piloted. All the participants remarked that they had learnt a lot about the structure of good essays and more importantly how clear the role of the conclusion played in a well-constructed essay. This type of representation made this explicit and they would be able to see quickly if a second draft had improved. The users also mentioned that the rainbow diagram representations could be used as a generic essay feedback tool. It could be used across subject domains, a hypothesis worthy of further investigation