Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Genisa: A web-based interactive learning environment for teaching simulation modelling

Intelligent Tutoring Systems (ITS) provide students with adaptive instruction and can facilitate the acquisition of problem solving skills in an interactive environment. This paper discusses the role of pedagogical strategies that have been implemented to facilitate the development of simulation modelling knowledge. The learning environment integrates case-based reasoning with interactive tools to guide tutorial remediation. The evaluation of the system shows that the model for pedagogical activities is a useful method for providing efficient simulation modelling instruction

Mobile Robot Lab Project to Introduce Engineering Students to Fault Diagnosis in Mechatronic Systems

This document is a self-archiving copy of the accepted version of the paper. Please find the final published version in IEEEXplore: http://dx.doi.org/10.1109/TE.2014.2358551This paper proposes lab work for learning fault detection and diagnosis (FDD) in mechatronic systems. These skills are important for engineering education because FDD is a key capability of competitive processes and products. The intended outcome of the lab work is that students become aware of the importance of faulty conditions and learn to design FDD strategies for a real system. To this end, the paper proposes a lab project where students are requested to develop a discrete event dynamic system (DEDS) diagnosis to cope with two faulty conditions in an autonomous mobile robot task. A sample solution is discussed for LEGO Mindstorms NXT robots with LabVIEW. This innovative practice is relevant to higher education engineering courses related to mechatronics, robotics, or DEDS. Results are also given of the application of this strategy as part of a postgraduate course on fault-tolerant mechatronic systems.This work was supported in part by the Spanish CICYT under Project DPI2011-22443

Optimising ITS behaviour with Bayesian networks and decision theory

We propose and demonstrate a methodology for building tractable normative intelligent tutoring systems (ITSs). A normative ITS uses a Bayesian network for long-term student modelling and decision theory to select the next tutorial action. Because normative theories are a general framework for rational behaviour, they can be used to both define and apply learning theories in a rational, and therefore optimal, way. This contrasts to the more traditional approach of using an ad-hoc scheme to implement the learning theory. A key step of the methodology is the induction and the continual adaptation of the Bayesian network student model from student performance data, a step that is distinct from other recent Bayesian net approaches in which the network structure and probabilities are either chosen beforehand by an expert, or by efficiency considerations. The methodology is demonstrated by a description and evaluation of CAPIT, a normative constraint-based tutor for English capitalisation and punctuation. Our evaluation results show that a class using the full normative version of CAPIT learned the domain rules at a faster rate than the class that used a non-normative version of the same system

Enhancing simulation education with intelligent tutoring systems

The demand for education in the area of simulation is in the increase. This paper describes how education in the field of simulation can take advantage of the virtues of intelligent tutoring with respect to enhancing the educational process. For this purpose, this paper gives an overview of what constitutes the objectives and the content of a comprehensive course in discrete event simulation. The architecture of an intelligent tutoring system is presented and it is discussed how these sophisticated learning aids offer individualised student guidance and support within a learning environment. The paper then introduces a prototype intelligent tutoring system, the simulation tutor, and suggests how the system might be developed to enhance education in simulation

Tutoring systems based on user-interface dialogue specification

This thesis shows how the appropriate specification of a user interface to an application software package can be used as the basis for constructing a tutorial for teaching the use of that interface. An economy can hence be made by sharing the specification between the application development and tutorial development stages. The major part of the user-interface specification which is utilised, the task classification structure, must be transformed from an operational to a pedagogic ordering. Heuristics are proposed to achieve this, although human expertise is required to apply them. The report approach is best suited to domains with hierarchically-ordered command sets. A portable rule-based shell has been developed in Common Lisp which supports the delivery of tutorials for a range of software application package interfaces. The use of both the shell and tutorials for two such interfaces is reported. A computer-based authoring environment provides support for tutorial development. The shell allows the learner of a software interface to interact directly with the application software being learnt while remaining under tutorial control. The learner can always interrupt in order to request a tutorial on any topic, although advice may be offered against this in the light of the tutor's current knowledge of the learner. This advice can always be over-ridden. The key-stroke sequences of the tutorial designer and the learner interacting with the package are parsed against an application model based on the task classification structure. Diagnosis is effected by a differential modelling technique applied to the structures generated by the parsing processes. The approach reported here is suitable for an unsupported software interface learner and is named LIY (`Learn It Yourself'). It provides a promising method for augmenting a software engineering tool-kit with a new technique for producing tutorials for application software

An open learner model for trainee pilots

This paper investigates the potential for simple open learner models for highly motivated, independent learners, using the example of trainee pilots. In particular we consider whether such users access their learner model to help them identify their current knowledge level, areas of difficulty and specific misconceptions, to help them plan their immediate learning activities; and whether they find a longer‐term planning aid useful. The Flight Club open learner model was deployed in a UK flight school over four weeks. Results suggest that motivated users such as trainee pilots will use a system with a simple open learner model, and are interested in consulting their learner model information both to facilitate planning over time, and to understand their current knowledge state. We discuss the extent to which our findings may be relevant to learners in other contexts

Proceedings of the 4th Student-STAFF Research Conference 2020 School of Computer Science and Engineering SSRC2020

This volume contains the proceedings of the 4th Student-STAFF Research Conference of the School of Computer Science and Engineering (SSRC2020). This is a traditional, annual forum which brings together, for an one-day intensive programme, established and young researchers from different areas of research, doctoral researchers, postgraduate and undergraduate alumni, and covers both traditional and emerging topics, disseminates achieved results or work in progress. During informal discussions at conference sessions, the attendees share their research findings with an open audience of academics, doctoral, postgraduate and undergraduate students. The SSRCS2020 was held on-line. The specifics of this year's conference was the participation of alumni from the Informatics Institute of Technology (IIT Sri Lanka) and Westminster International University in Tashkent (WIUT, Uzbekistan). The event met great interest - it had more than 200 on-line participants, with one session accommodating the audience of 156! The presenters whether they are established researchers or just at the start of their career, not only share their work but also gain invaluable feedback during the conference sessions. Twenty one abstracts of the Proceedings contributed by the speakers at the SSRC2020 are assembled in order of their presentation at the conference. The abstracts cover a wide spectre of topics including the development of on-line knowledge and learning repositories, data analysis, applications of machine learning in fraud detection, bankruptcy prediction, patients mortality, image synthesis, graph DB, image analysis for medical diagnostics, mobile app developments, user experience design, wide area networking, adaptive agent algorithms, plagiarism detection, process mining techniques for behavioural patterns, data mining for reablement, Cloud Computing, Networking and linguistic profiling

A generic architecture for interactive intelligent tutoring systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 07/06/2001.This research is focused on developing a generic intelligent architecture for an interactive tutoring system. A review of the literature in the areas of instructional theories, cognitive and social views of learning, intelligent tutoring systems development methodologies, and knowledge representation methods was conducted. As a result, a generic ITS development architecture (GeNisa) has been proposed, which combines the features of knowledge base systems (KBS) with object-oriented methodology. The GeNisa architecture consists of the following components: a tutorial events communication module, which encapsulates the interactive processes and other independent computations between different components; a software design toolkit; and an autonomous knowledge acquisition from a probabilistic knowledge base. A graphical application development environment includes tools to support application development, and learning environments and which use a case scenario as a basis for instruction. The generic architecture is designed to support client-side execution in a Web browser environment, and further testing will show that it can disseminate applications over the World Wide Web. Such an architecture can be adapted to different teaching styles and domains, and reusing instructional materials automatically can reduce the effort of the courseware developer (hence cost and time) in authoring new materials. GeNisa was implemented using Java scripts, and subsequently evaluated at various commercial and academic organisations. Parameters chosen for the evaluation include quality of courseware, relevancy of case scenarios, portability to other platforms, ease of use, content, user-friendliness, screen display, clarity, topic interest, and overall satisfaction with GeNisa. In general, the evaluation focused on the novel characteristics and performances of the GeNisa architecture in comparison with other ITS and the results obtained are discussed and analysed. On the basis of the experience gained during the literature research and GeNisa development and evaluation. a generic methodology for ITS development is proposed as well as the requirements for the further development of ITS tools. Finally, conclusions are drawn and areas for further research are identified