An Adaptive Machine Learning Decision System for Flexible Predictive Maintenance

Process monitoring and Predictive Maintenance (PdM) are gaining increasing attention in most manufacturing environments as a means of reducing maintenance related costs and downtime. This is especially true in industries that are data intensive such as semiconductor manufacturing. In this paper an adaptive PdM based flexible maintenance scheduling decision support system, which pays particular attention to associated opportunity and risk costs, is presented. The proposed system, which employs Machine Learning and regularized regression methods, exploits new information as it becomes available from newly processed components to refine remaining useful life estimates and associated costs and risks. The system has been validated on a real industrial dataset related to an Ion Beam Etching process for semiconductor manufacturing.

An evaluation of the Socrative (personal response system) app for increasing student engagement and learning in an undergraduate psychology curriculum.

Personal response systems using hardware such as 'clickers' have been around for some time, however their use is often restricted to multiple choice questions (MCQs) and they are therefore used as a summative assessment tool for the individual student. More recent innovations such as 'Socrative' have removed the need for specialist hardware, instead utilising web-based technology and devices common to students, such as smartphones, tablets and laptops. While improving the potential for use in larger classrooms, this also creates the opportunity to pose more engaging open-response questions to students who can 'text in' their thoughts on questions posed in class. This poster will present two applications of the Socrative system in an undergraduate psychology curriculum which aimed to encourage interactive engagement with course content using real-time student responses and lecturer feedback. Data is currently being collected and result will be presented at the conference.
The first application used Socrative to pose MCQs at the end of two modules (a level one Statistics module and level two Individual Differences Psychology module, class size N≈100), with the intention of helping students assess their knowledge of the course. They were asked to rate their self-perceived knowledge of the course on a five-point Likert scale before and after completing the MCQs, as well as their views on the value of the revision session and any issues that had with using the app. The online MCQs remained open between the lecture and the exam, allowing students to revisit the questions at any time during their revision.
This poster will present data regarding the usefulness of the revision MCQs, the metacognitive effect of the MCQs on student's judgements of learning (pre vs post MCQ testing), as well as student engagement with the MCQs between the revision session and the examination. Student opinions on the use of the Socrative system in class will also be discussed.
The second application used Socrative to facilitate a flipped classroom lecture on a level two 'Conceptual Issues in Psychology' module, class size N≈100). The content of this module requires students to think critically about historical and contemporary conceptual issues in psychology and the philosophy of science. Students traditionally struggle with this module due to the emphasis on critical thinking skills, rather than simply the retention of concrete knowledge. To prepare students for the written examination, a flipped classroom lecture was held at the end of the semester. Students were asked to revise their knowledge of a particular area of Psychology by assigned reading, and were told that the flipped lecture would involve them thinking critically about the conceptual issues found in this area. They were informed that questions would be posed by the lecturer in class, and that they would be asked to post their thoughts using the Socrative app for a class discussion. The level of preparation students engaged in for the flipped lecture was measured, as well as qualitative opinions on the usefulness of the session. This poster will discuss the level of student engagement with the flipped lecture, both in terms of preparation for the lecture, and engagement with questions posed during the lecture, as well as the lecturer's experience in facilitating the flipped classroom using the Socrative platform.

A content analysis method to measure critical thinking in face-to-face and computer supported group learning

This paper gives a detailed account of the content analysis method developed at Queen's University Belfast to measure critical thinking during group learning, as used in our controlled comparisons between learning in face-to-face and computer conference seminars. From Garrison's 5 stages of critical thinking, and Henri's cognitive skills needed in CMC, we have developed two research instruments: a student questionnaire and this content analysis method. The content analysis relies on identifying, within transcripts, examples of indicators of obviously critical and obviously uncritical thinking, from which several critical thinking ratios can be calculated.

Learning outcomes tracking system (L.O.T.S):seeing student progress as term progresses

At QUB we have constructed a system that allows students to self-assess their capability on the fine grained learning outcomes for a module and to update their record as the term progresses. In the system each of the learning outcomes are linked to the relevant teaching session (lectures and labs) and to [online] resources that students can access at any time. Students can structure their own learning experience to their needs to attain the learning outcomes. The system keeps a history of the student’s record, allowing the lecturer to observe how the students’ abilities progress over the term and to compare it to assessment results. The system also keeps of any of the resource links that student has clicked on.

Is Our Students Learning - QuestionMark: Extending E-Assessment Systems for Adapative Marking and Feedback

Our key contribution is a flexible, automated marking system that adds desirable functionality to existing E-Assessment systems. In our approach, any given E-Assessment system is relegated to a data-collection mechanism, whereas marking and the generation and distribution of personalised per-student feedback is handled separately by our own system. This allows content-rich Microsoft Word feedback documents to be generated and distributed to every student simultaneously according to a per-assessment schedule.

The feedback is adaptive in that it corresponds to the answers given by the student and provides guidance on where they may have gone wrong. It is not limited to simple multiple choice which are the most prescriptive question type offered by most E-Assessment Systems and as such most straightforward to mark consistently and provide individual per-alternative feedback strings. It is also better equipped to handle the use of mathematical symbols and images within the feedback documents which is more flexible than existing E-Assessment systems, which can only handle simple text strings.

As well as MCQs the system reliably and robustly handles Multiple Response, Text Matching and Numeric style questions in a more flexible manner than Questionmark: Perception and other E-Assessment Systems. It can also reliably handle multi-part questions where the response to an earlier question influences the answer to a later one and can adjust both scoring and feedback appropriately.

New question formats can be added at any time provided a corresponding marking method conforming to certain templates can also be programmed. Indeed, any question type for which a programmatic method of marking can be devised may be supported by our system. Furthermore, since the student’s response to each is question is marked programmatically, our system can be set to allow for minor deviations from the correct answer, and if appropriate award partial marks.

Implementation of Content Centric Networks Through Domain Name System

Content Centric Network (CCN) is a proposed future internet architecture that is based on the concept of contents name instead of the hosts name followed in the traditional internet architecture. CCN architecture might do changes in the existing internet architecture or might replace it completely. In this paper, we present modifications to the existing Domain Name System (DNS) based on the CCN architecture requirements without changing the existing routing architecture. Hence the proposed solution achieves the benefits of both CCN and existing network infrastructure (i.e. content based routing, independent of host location, caching and content delivery protocols).