Innovative use of e-portfolio for personal development

iLearn is a quasi-Web 2.0 tool developed in Blackboard to help users with Personal Development Planning (PDP). This paper describes a case study on how the innovative use of mobile digital technology in iLearn e-Portfolio for developing reflective portfolios for PDP benefits the users, who are training to be professionals in construction management and surveying, The e-Portfolio tool benefits users as it enables them to create and share portfolios, record achievements and reflections that support future job applications and promotion. Users find it beneficial because they can make use of iLearn e-Portfolio to keep academic records and achievements, activities and interests, work experience, reflective practice, employer information and some other useful resources, and also to tailor their CV and covering letters including evidence to support their CV, transferable skills and selling points. Useful information for preparing for an interview, reflecting after an event and any thoughts and evaluation can be kept in iLearn e-Portfolio. Keeping assessment and feedback records in iLearn e-Portfolio enables learners to know their progress, to identify any gaps they need to fill to develop their study practices and areas for development. The key points from the feedback on the assignments and assessments are beneficial for future improvement. The reflections on the tasks and how they make use of the advice are particularly useful to improve their overall performance. In terms of pedagogical benefits, the “Individual Learner Profile” records and reviews evidence in verbal communication, basic and higher academic skills, time management, numeracy skill and IT skills, learners become increasingly aware of their own strengths and any weaker areas that may require development. The e-Portfolio also provides opportunity for them to reflect on the experience and skills they have gained whilst participating in activities outside their studies. As the iLearn e-Portfolio is a reflective practice tool, it is consistent with the principle of Schon's reflective practitioner to reframe problems and to explore the consequences of actions. From the users’ feedback, for those who engage regularly in iLearn, they are better able to set agendas for their supervision meetings and provide their supervisor with a unique record of their achievements, skills and attributes which help them writing effective references for them. They make the most of their learning experience in general. They also enhance their transferable skills and employability overall. The iLearn e-Portfolio prepares them for the workplace including continuing professional development. Users are aware of their transferable skills, evidence of the skills and skill level, including award or accreditation, and their personal reflection on their transferable skills. It is beneficial for them to be aware of their transferable skills, to produce evidence of the skills and skills level such as award and accreditation, and to record their personal reflection on their transferable skills. Finally, the innovative use of mobile digital technology in iLearn e-Portfolio for developing reflective portfolios for PDP will improve their employability.

Doctoral supervision of colleagues: peeling off the veneer of satisfaction and competence

The nexus of teaching, administration and research activities engaged in by academic staff in higher education means that each individual plays a multitude of roles in relation to colleagues, producing inevitable tensions. One role relationship that epitomizes this extraordinary juggling task is that of doctoral supervisor/supervisee, when both are academic staff in the same institution. The last 10 years has seen an upsurge of research interest in doctoral research students, and government and funding bodies have imposed ever more stringent requirements on supervisors. However, staff pairings have been ignored in this literature and research. This article reports on an exploration that seeks to redress this omission by giving voice to the participants (colleague supervisor or research student), allowing them to articulate constructs about what may be unique in the interaction, thus highlighting factors that support or impede success in the enterprise.

Doctoral supervision of colleagues: peeling off the veneer of satisfaction and competence

The nexus of teaching, administration and research activities engaged in by academic staff in higher education means that each individual plays a multitude of roles in relation to colleagues, producing inevitable tensions. One role relationship that epitomizes this extraordinary juggling task is that of doctoral supervisor/supervisee, when both are academic staff in the same institution. The last 10 years has seen an upsurge of research interest in doctoral research students, and government and funding bodies have imposed ever more stringent requirements on supervisors. However, staff pairings have been ignored in this literature and research. This article reports on an exploration that seeks to redress this omission by giving voice to the participants (colleague supervisor or research student), allowing them to articulate constructs about what may be unique in the interaction, thus highlighting factors that support or impede success in the enterprise.

Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning

This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Neural networks for power systems alarm handling

A multi-layered architecture of self-organizing neural networks is being developed as part of an intelligent alarm processor to analyse a stream of power grid fault messages and provide a suggested diagnosis of the fault location. Feedback concerning the accuracy of the diagnosis is provided by an object-oriented grid simulator which acts as an external supervisor to the learning system. The utilization of artificial neural networks within this environment should result in a powerful generic alarm processor which will not require extensive training by a human expert to produce accurate results.

Cooperative task support for the control room

The National Grid Company plc. owns and operates the electricity transmission network in England and Wales, the day to day running of the network being carried out by teams of engineers within the national control room. The task of monitoring and operating the transmission network involves the transfer of large amounts of data and a high degree of cooperation between these engineers. The purpose of the research detailed in this paper is to investigate the use of interfacing techniques within the control room scenario, in particular, the development of an agent based architecture for the support of cooperative tasks. The proposed architecture revolves around the use of interface and user supervisor agents. Primarily, these agents are responsible for the flow of information to and from individual users and user groups. The agents are also responsible for tackling the synchronisation and control issues arising during the completion of cooperative tasks. In this paper a novel approach to human computer interaction (HCI) for power systems incorporating an embedded agent infrastructure is presented. The agent architectures used to form the base of the cooperative task support system are discussed, as is the nature of the support system and tasks it is intended to support.

Situation assessment through multi-modal sensing of dynamic environments to support cognitive robot control

Awareness of emerging situations in a dynamic operational environment of a robotic assistive device is an essential capability of such a cognitive system, based on its effective and efficient assessment of the prevailing situation. This allows the system to interact with the environment in a sensible (semi)autonomous / pro-active manner without the need for frequent interventions from a supervisor. In this paper, we report a novel generic Situation Assessment Architecture for robotic systems directly assisting humans as developed in the CORBYS project. This paper presents the overall architecture for situation assessment and its application in proof-of-concept Demonstrators as developed and validated within the CORBYS project. These include a robotic human follower and a mobile gait rehabilitation robotic system. We present an overview of the structure and functionality of the Situation Assessment Architecture for robotic systems with results and observations as collected from initial validation on the two CORBYS Demonstrators.