Designing and implementing a blended learning approach to executive SCM education:a case study from Ireland

The National Institute for Transport and Logistics (NITL) is Ireland’s centre of excellence for supply chain management (SCM). As part of its mission to promote the development of supply chain expertise in Irish business, it designs and delivers executive modular learning programmes. In 2004, as part of a drive to create more flexible learning opportunities for course participants, NITL designed and implemented an eLearning programme, which involved converting traditionally tutored modules to online modules. This paper describes the rationale behind this initiative and the significance of technology as an enabling tool for executive education, as well as detailing the design and implementation processes for the pilot module. The paper concludes with a critique of the expected and actual benefits realised, as well as future development considerations.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.

Inspiring lecturers: sharing e-learning practice through european case studies

What motivates a university lecturer to consider introducing a new e-learning approach to their educational practice? Accounts of e-learning practice can invite discussion and reflection on the approaches taken, reinforcement of a particular model, connection with the experience of others, vicarious learning opportunities and glimpses into tacit knowledge. If these examples provoke thinking, could they have the ‘sticky qualities’, the memorable inspiration and ideas that move us to action, when we observe the practice of others? (Szulanski, 2003) “Case studies have the capacity to inspire but also to provoke and to challenge.” (JISC, 2004) This paper will discuss a process followed for sharing best practices of e-learning. It will explain how good practices were identified and gathered by the EUNIS E-Learning Task Force collaboration, using a database and a weblog (EUNIC, 2008). It will examine the methods used for the developing and compiling of the practices and the communication of these. Actual examples of some of the case studies gathered will be included in an appendix. Suggestions of ways to develop this process further and the tangible benefits identified will be examined to ask if effective practice can also become embedded practice.

Content-based VLE designs improve learning efficiency in constructivist statistics education

Background: We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives: The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods: Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results: The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content-based design outperforms the traditional VLE-based design. © 2011 Wessa et al.

Peer mentoring and experiential learning:the pathway to success

An analysis of the value of peer mentoring as an experiential learning approach

Experimenting with supply chain learning (SCL):supplier diversity and ethnic minority businesses

This paper reports on an innovative UK-based ‘Supply Chain Learning’ (SCL) initiative to encourage the corporate sector to consider supplier diversity in respect of ethnic minority businesses. This follows academic and policy interest in programmes to empower ethnic minority enterprises to achieve breakout to mainstream markets and business growth. The first phase of the initiative, entitled Supplier Development East Midlands (SDEM) is examined. By adopting an inter-organisational action learning approach, some of the key attributes of the programme are delineated, focusing on the recurrent action-reflection cycle taking place in a learning group comprising SDEM, LPOs (Large Purchasing Organisations) and small EMSs (Ethnic Minority Suppliers).

Practice based learning approaches in collaborative design and engineering education:a case study investigation into the benefits of a crossdisciplinary practice based learning strategy

This study explores the ongoing pedagogical development of a number of undergraduate design and engineering programmes in the United Kingdom. Observations and data have been collected over several cohorts to bring a valuable perspective to the approaches piloted across two similar university departments while trialling a number of innovative learning strategies. In addition to the concurrent institutional studies the work explores curriculum design that applies the principles of Co-Design, multidisciplinary and trans disciplinary learning, with both engineering and product design students working alongside each other through a practical problem solving learning approach known as the CDIO learning initiative (Conceive, Design Implement and Operate) [1]. The study builds on previous work presented at the 2010 EPDE conference: The Effect of Personality on the Design Team: Lessons from Industry for Design Education [2]. The subsequent work presented in this paper applies the findings to mixed design and engineering team based learning, building on the insight gained through a number of industrial process case studies carried out in current design practice. Developments in delivery also aligning the CDIO principles of learning through doing into a practice based, collaborative learning experience and include elements of the TRIZ creative problem solving technique [3]. The paper will outline case studies involving a number of mixed engineering and design student projects that highlight the CDIO principles, combined with an external industrial design brief. It will compare and contrast the learning experience with that of a KTP derived student project, to examine an industry based model for student projects. In addition key areas of best practice will be presented, and student work from each mode will be discussed at the conference.

Developments in assessment and teaching methodologies in modern languages in England and France in response to educational reform (1975-1985)

This comparative study considers the main causative factors for change in recent years in the teaching of modern languages in England and France and seeks to contribute, in a general sense, to the understanding of change in comparable institutions. In England by 1975 the teaching of modern languages in the comprehensive schools was seen to be inappropriate to the needs of children of the whole ability-range. A combination of the external factor of the Council of Europe initiative in devising a needs-based learning approach for adult learners, and the internal factor of teacher-based initiatives in developing a graded-objectives learning approach for the less-able, has reversed this situation to some extent. The study examines and evaluates this reversal, and, in addition, assesses teachers' attitudes towards, and understanding of, the changes involved. In France the imposition of `la reforme Haby' in 1977 and the creation of `le college unique' were the main external factors for change. The subsequent failure of the reform and the socialist government's support of decentralisation policies returning the initiative for renewal to schools are examined and evaluated, as are the internal factors for changes in language-teaching - `groupes de niveau' and the creation of `equipes pedagogiques'. In both countries changes in the function of examinations at 15/16 plus are examined. The final chapter compared the changes in both education systems.

Engineering education for the 21st century:scholarship, synergy and student success

Starting with the question “How can University level Engineering Education be developed in such a way so as to enhance the quality of the student learning experience?”, this discussion paper proposes an approach to engineering education developed by a senior engineering educator working alongside a pedagogical researcher in an attempt to engage colleagues in contemporary debates about the issues currently faced across the Sector. Such issues include difficulties with recruiting students onto programmes as well as high levels of student attrition and failure. Underpinned by three distinctive concepts: Synergy, Variety & Relationships (S+V+R), the approach brings together pedagogic and engineering epistemologies in an empirically grounded framework in such a way so as to provide an accessible and relevant learning approach that, if followed, engenders student success [S2]. Specifically developed with the intention of increasing retention and positively impacting student success [S2], the S+V+R=S2 approach provides a scholarly and Synergetic (S) approach to engineering education that is both innovative and exciting. Building on the argument that Variety (V) in education is pivotal to promoting originality and creativity in learning and teaching, this paper shows how, by purposefully developing a range of learning and teaching approaches, student engagement and thus success can be increased. It also considers the importance of Relationships (R) in higher education, arguing that belonging and relationships are crucial factors impacting student experiences. When taken together (Synergy, Variety and Relationships) and applied within an Engineering Education context, students are provided with a unique learning environment – one that both promotes individual success and improves organisational effectiveness. The uniqueness of the approach is in the synthesis of these three concepts within an Engineering Education epistemology.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

Cultural diversity and team performance:the role of team member goal orientation

As workforce diversity increases, knowledge of factors influencing whether cultural diversity results in team performance benefits is of growing importance. Complementing and extending earlier research, we develop and test theory about how achievement setting readily activates team member goal orientations that influence the diversity-performance relationship. In two studies, we identify goal orientation as a moderator of the performance benefits of cultural diversity and team information elaboration as the underlying process. Cultural diversity is more positive for team performance when team members' learning approach orientation is high and performance avoidance orientation is low. This effect is exerted via team information elaboration.

Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

Stretching the life of Twitter classifiers with time-stamped semantic graphs

Social media has become an effective channel for communicating both trends and public opinion on current events. However the automatic topic classification of social media content pose various challenges. Topic classification is a common technique used for automatically capturing themes that emerge from social media streams. However, such techniques are sensitive to the evolution of topics when new event-dependent vocabularies start to emerge (e.g., Crimea becoming relevant to War Conflict during the Ukraine crisis in 2014). Therefore, traditional supervised classification methods which rely on labelled data could rapidly become outdated. In this paper we propose a novel transfer learning approach to address the classification task of new data when the only available labelled data belong to a previous epoch. This approach relies on the incorporation of knowledge from DBpedia graphs. Our findings show promising results in understanding how features age, and how semantic features can support the evolution of topic classifiers.

Resisting the final word:challenging stale media and policy representations of students’ performative technological encounters in university education

This article explores powerful, constraining representations of encounters between digital technologies and the bodies of students and teachers, using corpus-based Critical Discourse Analysis (CDA). It discusses examples from a corpus of UK Higher Education (HE) policy documents, and considers how confronting such documents may strengthen arguments from educators against narrow representations of an automatically enhanced learning. Examples reveal that a promise of enhanced ‘student experience’ through information and communication technologies internalizes the ideological constructs of technology and policy makers, to reinforce a primary logic of exchange value. The identified dominant discursive patterns are closely linked to the Californian ideology. By exposing these texts, they provide a form of ‘linguistic resistance’ for educators to disrupt powerful processes that serve the interests of a neoliberal social imaginary. To mine this current crisis of education, the authors introduce productive links between a Networked Learning approach and a posthumanist perspective. The Networked Learning approach emphasises conscious choices between political alternatives, which in turn could help us reconsider ways we write about digital technologies in policy. Then, based on the works of Haraway, Hayles, and Wark, a posthumanist perspective places human digital learning encounters at the juncture of non-humans and politics. Connections between the Networked Learning approach and the posthumanist perspective are necessary in order to replace a discourse of (mis)representations with a more performative view towards the digital human body, which then becomes situated at the centre of teaching and learning. In practice, however, establishing these connections is much more complex than resorting to the typically straightforward common sense discourse encountered in the Critical Discourse Analysis, and this may yet limit practical applications of this research in policy making.

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder

Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.