The use of additional information in problem-oriented learning environments

Self-directed learning with authentic and complex problems (problem-oriented learning) requires that learners observe their own learning and use additional information when it is appropriate – e.g. hypertextual information in computer-supported learning environments. Research results indicate that learners in problem-oriented learning environments often have difficulties using additional information adequately, and that they should be supported. Two studies with a computer-supported problem-oriented learning environment in the domain of medicine analyzed the effects of strategy instruction on the use of additional information and the quality of the problem representation. In study 1, an expert model was used for strategy instruction. Two groups were compared: one group with strategy modeling and one group without. Strategy modeling influenced the frequency of looked-up hypertextual information, but did not influence the quality of learners' problem representations. This could be explained by difficulties in applying the general hypertext information to the problem. In study 2, the additional information was presented in a more contextualized way as graphical representation of the case and its relevant concepts. Again, two groups were compared: one with a strategy instruction text and one without. Strategy instruction texts supported an adequate use of this graphical information by learners and had an effect on the quality of their problem representations. These findings are discussed with respect to the design of additional help systems in problem-oriented learning environments

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Modelling human teaching tactics and strategies for tutoring systems

One of the promises of ITSs and ILEs is that they will teach and assist learning in an intelligent manner. Historically this has tended to mean concentrating on the interface, on the representation of the domain and on the representation of the student’s knowledge. So systems have attempted to provide students with reifications both of what is to be learned and of the learning process, as well as optimally sequencing and adjusting activities, problems and feedback to best help them learn that domain. We now have embodied (and disembodied) teaching agents and computer-based peers, and the field demonstrates a much greater interest in metacognition and in collaborative activities and tools to support that collaboration. Nevertheless the issue of the teaching competence of ITSs and ILEs is still important, as well as the more specific question as to whether systems can and should mimic human teachers. Indeed increasing interest in embodied agents has thrown the spotlight back on how such agents should behave with respect to learners. In the mid 1980s Ohlsson and others offered critiques of ITSs and ILEs in terms of the limited range and adaptability of their teaching actions as compared to the wealth of tactics and strategies employed by human expert teachers. So are we in any better position in modelling teaching than we were in the 80s? Are these criticisms still as valid today as they were then? This paper reviews progress in understanding certain aspects of human expert teaching and in developing tutoring systems that implement those human teaching strategies and tactics. It concentrates particularly on how systems have dealt with student answers and how they have dealt with motivational issues, referring particularly to work carried out at Sussex: for example, on responding effectively to the student’s motivational state, on contingent and Vygotskian inspired teaching strategies and on the plausibility problem. This latter is concerned with whether tactics that are effectively applied by human teachers can be as effective when embodied in machine teachers

Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector

Intuitive expertise in ICT graduate supervision

Intuitive expertise in the application of advanced interdisciplinary facilitation is the subject of this personal reflection on the graduate supervisory style of Professor David Squires in computers in education. This single‐case reflective study examines the characteristics of effective supervision observed during masters and doctoral supervision at King's College in the years 1990–9. Interdisciplinarity in ICT graduate studies particularly requires a fluency of supervisory expertise in enabling supervisees to combine multiple complex perspectives from a number of fields of knowledge. Intuitive combinatory aspects of supervision are highlighted in this reflection on the role carried out by an academic expert in facilitating student success. This is examined from a perspective incorporating affective as well as intellectual elements, informed by characteristics identified in professional sports and performing arts coaching/mentoring. Key characteristics comprising a model of intuitive expertise in ICT graduate supervision were outlined. The resultant portrait aims to complement existing literature on graduate supervision, with reference to the field of ICTI computers in education relating to student hypermedia composition

Failure is an option:an innovative engineering curriculum

PurposeAdvancements and innovation in engineering design are based on learning from previous failures but students are encouraged to ‘succeed’ first time and hence can avoid learning from failure in practice. The purpose of the study was to design and evaluate a curriculum to help engineering design students to learn from failure.Design/Methodology/ApproachA new curriculum design provided a case study for evaluating the effects of incorporating learning from failure within a civil engineering course. An analysis of the changes in course output was undertaken in relation to graduate destination data covering 2006 to 2016 and student satisfaction from 2012 to 2017 and a number of challenges and solutions for curriculum designers were identified.FindingsThe design and delivery of an innovative curriculum, within typical constraints, can provide opportunities for students to develop resilience to failure as an integral part of their learning in order to think creatively and develop novel engineering solutions. The key issues identified were: the selection of appropriate teaching methods, creating an environment for exploratory learning, group and team assessments with competitive elements where practicable, and providing students with many different pedagogical approaches to produce a quality learning experience.OriginalityThis case study demonstrates how to design and implement an innovative curriculum that can produce positive benefits of learning from failure. This model can be applied to other disciplines such as building surveying and construction management. This approach underpins the development of skills necessary in the educational experience to develop as a professional building pathologist

Exploring the Relationship Between Self-Regulated Learning and Reflection in Teacher Education

Literature on teacher learning has shown links between being a self-regulated learner, reflecting effectively on one’s own practice, and being described as an “adaptive expert”. For instance, the metacognitive skills needed for effective reflection on teaching practice are seen as critically important to developing adaptive expertise in the context of the highly complex classroom environment. Similarly, self-regulated learning is often defined, at least in part, in terms of using metacognitive skill to adapt one’s approach to complex learning situations or problems. Although there is rich literature on reflective practice in teacher education, less is known about measuring teachers’ self-regulated learning or the relationship between self-regulated learning and teacher reflections. This research examines reflective practice and self-regulated learning through pre-service teachers’ written reflections. The study makes a novel adaptation of a rubric designed to evaluate teacher education candidates’ reflections to measure self-regulated learning. Findings suggest that the rubric could also be useful in understanding the self-regulated practices of teacher education candidates

Innovation and failure in mechatronics design education

Innovative engineering design always has associated with it the risk of failure, and it is the role of the design engineer to mitigate the possibilities of failure in the final system. Education should however provide a safe space for students to both innovate and to learn about and from failures. However, pressures on course designers and students can result in their adopting a conservative, and risk averse, approach to problem solving. The paper therefore considers the nature of both innovation and failure, and looks at how these might be effectively combined within mechatronics design education

Fostering Innovation in Philanthropy

Innovation is a buzzword with growing resonance in the philanthropic community. But how are foundations going about adopting innovative practices? In this guide, you'll learn the definition of "innovation"; 8 approaches to philanthropic innovation; key practices of innovative funders; recommendations to become innovative and support innovation; and more