Functional neuroimaging of emotional learning and autonomic reactions

This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

LEARNING FROM NEAR MISSES IN MEDICATION ERRORS: A BAYESIAN APPROACH

Medical errors originating in health care facilities are a significant source of preventable morbidity, mortality, and healthcare costs. Voluntary error report systems that collect information on the causes and contributing factors of medi- cal errors regardless of the resulting harm may be useful for developing effective harm prevention strategies. Some patient safety experts question the utility of data from errors that did not lead to harm to the patient, also called near misses. A near miss (a.k.a. close call) is an unplanned event that did not result in injury to the patient. Only a fortunate break in the chain of events prevented injury. We use data from a large voluntary reporting system of 836,174 medication errors from 1999 to 2005 to provide evidence that the causes and contributing factors of errors that result in harm are similar to the causes and contributing factors of near misses. We develop Bayesian hierarchical models for estimating the log odds of selecting a given cause (or contributing factor) of error given harm has occurred and the log odds of selecting the same cause given that harm did not occur. The posterior distribution of the correlation between these two vectors of log-odds is used as a measure of the evidence supporting the use of data from near misses and their causes and contributing factors to prevent medical errors. In addition, we identify the causes and contributing factors that have the highest or lowest log-odds ratio of harm versus no harm. These causes and contributing factors should also be a focus in the design of prevention strategies. This paper provides important evidence on the utility of data from near misses, which constitute the vast majority of errors in our data.

Place for video games : a theoretical and pedagogical framework for multiliteracies learning in English studies

Students are now involved in a vastly different textual landscape than many English scholars, one that relies on the “reading” and interpretation of multiple channels of simultaneous information. As a response to these new kinds of literate practices, my dissertation adds to the growing body of research on multimodal literacies, narratology in new media, and rhetoric through an examination of the place of video games in English teaching and research. I describe in this dissertation a hybridized theoretical basis for incorporating video games in English classrooms. This framework for textual analysis includes elements from narrative theory in literary study, rhetorical theory, and literacy theory, and when combined to account for the multiple modalities and complexities of gaming, can provide new insights about those theories and practices across all kinds of media, whether in written texts, films, or video games. In creating this framework, I hope to encourage students to view texts from a meta-level perspective, encompassing textual construction, use, and interpretation. In order to foster meta-level learning in an English course, I use specific theoretical frameworks from the fields of literary studies, narratology, film theory, aural theory, reader-response criticism, game studies, and multiliteracies theory to analyze a particular video game: World of Goo. These theoretical frameworks inform pedagogical practices used in the classroom for textual analysis of multiple media. Examining a video game from these perspectives, I use analytical methods from each, including close reading, explication, textual analysis, and individual elements of multiliteracies theory and pedagogy. In undertaking an in-depth analysis of World of Goo, I demonstrate the possibilities for classroom instruction with a complex blend of theories and pedagogies in English courses. This blend of theories and practices is meant to foster literacy learning across media, helping students develop metaknowledge of their own literate practices in multiple modes. Finally, I outline a design for a multiliteracies course that would allow English scholars to use video games along with other texts to interrogate texts as systems of information. In doing so, students can hopefully view and transform systems in their own lives as audiences, citizens, and workers.

Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Kostenorientiertes Controlling von E-Learning-Plattformen mit dem TCO-Konzept

Zur administrativen Unterstützung von Lehr- und Lernprozessen werden E-Learning-Plattformen eingesetzt, die auf der Grundlage des Internet Funktionen zur Distribution von Lehr- und Lernmaterialien und zur Kommunikation zwischen Lehrenden und Lernenden anbieten. Zahlreiche wissenschaftliche Beiträge und Marktstudien beschäftigen sich mit der multikriteriellen Evaluation dieser Softwareprodukte zur informatorischen Fundierung strategischer Investitionsentscheidungen. Demgegenüber werden Instrumente zum kostenorientierten Controlling von E-Learning-Plattformen allenfalls marginal thematisiert. Dieser Beitrag greift daher das Konzept der Total Cost of Ownership (TCO) auf, das einen methodischen Ansatzpunkt zur Schaffung von Kostentransparenz von E-Learning-Plattformen bildet. Aufbauend auf den konzeptionellen Grundlagen werden Problembereiche und Anwendungspotenziale für das kostenorientierte Controlling von LMS identifiziert. Zur softwaregestützten Konstruktion und Analyse von TCO-Modellen wird das Open Source-Werkzeug TCO-Tool eingeführt und seine Anwendung anhand eines synthetischen Fallbeispiels erörtert. Abschließend erfolgt die Identifikation weiterführender Entwicklungsperspektiven des TCO-Konzepts im Kontext des E-Learning. Die dargestellte Thematik ist nicht nur von theoretischem Interesse, sondern adressiert auch den steigenden Bedarf von Akteuren aus der Bildungspraxis nach Instrumenten zur informatorischen Fundierung von Investitions- und Desinvestitionsentscheidungen im Umfeld des E-Learning.

E-Learning 2.0 in hydraulic engineering education

In this contribution the experiences with e-Learning 2.0 applications by using a Wiki for the education in hydraulic engineering are shown. Up to now important information for the students has been prepared by the instructor. For this project the students were asked to collaborate and search on their own for the information they needed. Therefore a Wiki-system was used. For the engineering practice a self dependent realisation of tasks is an important requirement which students should be prepared for. With the help of online communication there should be shown the possibilities for students for working together in an interdisciplinary team. The positive experiences as well as the results of the evaluation of this project plead for a continuation of the application of e-Learning 2.0 for education. The comparison of results of tests without using Wiki and with using Wiki shows a qualitative tendency of better marks. In this contribution we present the application of Wiki in hydraulic engineering but the results can also be used for other engineering disciplines.

A Socioeconomic Approach to the Development of E-Learning

A multitude of products, systems, approaches, views and notions characterize the field of e-learning. This article attempts to disentangle the field by using economic and sociological theories, theories of marketing management and strategy as well as practical experience gained by the author while working with leading edge suppliers of e-learning. On this basis, a distinction between knowledge creation e-learning and knowledge transfer e-learning is made. The various views are divided into four different ideal-typical paradigms, each with its own characteristics and limitations. Selecting the right paradigm to use in the development of an e-learning strategy may prove crucial to success. Implications for the development of an e-learning strategy in businesses and educational institutions are outlined.

Action Research and Learning Analytics in Higher Education

Teaching is a dynamic activity. It can be very effective, if its impact is constantly monitored and adjusted to the demands of changing social contexts and needs of learners. This implies that teachers need to be aware about teaching and learning processes. Moreover, they should constantly question their didactical methods and the learning resources, which they provide to their students. They should reflect if their actions are suitable, and they should regulate their teaching, e.g., by updating learning materials based on new knowledge about learners, or by motivating learners to engage in further learning activities. In the last years, a rising interest in ‘learning analytics’ is observable. This interest is motivated by the availability of massive amounts of educational data. Also, the continuously increasing processing power, and a strong motivation for discovering new information from these pools of educational data, is pushing further developments within the learning analytics research field. Learning analytics could be a method for reflective teaching practice that enables and guides teachers to investigate and evaluate their work in future learning scenarios. However, this potentially positive impact has not yet been sufficiently verified by learning analytics research. Another method that pursues these goals is ‘action research’. Learning analytics promises to initiate action research processes because it facilitates awareness, reflection and regulation of teaching activities analogous to action research. Therefore, this thesis joins both concepts, in order to improve the design of learning analytics tools. Central research question of this thesis are: What are the dimensions of learning analytics in relation to action research, which need to be considered when designing a learning analytics tool? How does a learning analytics dashboard impact the teachers of technology-enhanced university lectures regarding ‘awareness’, ‘reflection’ and ‘action’? Does it initiate action research? Which are central requirements for a learning analytics tool, which pursues such effects? This project followed design-based research principles, in order to answer these research questions. The main contributions are: a theoretical reference model that connects action research and learning analytics, the conceptualization and implementation of a learning analytics tool, a requirements catalogue for useful and usable learning analytics design based on evaluations, a tested procedure for impact analysis, and guidelines for the introduction of learning analytics into higher education.

Learning Analytics: Challenges and Future Research Directions

In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.

Student2Student als Organisationsmodell für die Entwicklung von E-Learning-Ressourcen

Die E-Learning-Plattform VBA@HfTL unterstützt das Erlernen von grundlegenden Programmierkonzepten mithilfe der Programmiersprache Visual Basic for Applications (VBA). Diese Plattform wurde von Studierenden für Studierende der Fachrichtung Wirtschaftsinformatik entwickelt, so dass ein Student2Student (S2S)-Ansatz umgesetzt wurde. Der Beitrag führt die konzeptionellen Grundlagen dieses Ansatzes ein und erläutert die organisatorischen sowie technischen Rahmenbedingungen des Entwicklungsprojekts als Forschungsfallstudie. Das Projektergebnis zeigt, dass Studierende selbstorganisiert E-Learning-Ressourcen entwickeln und sich dabei interdisziplinäre Fachinhalte der Wirtschaftsinformatik aneignen können. Die resultierende E-Learning-Plattform liefert aufgrund der hohen Resonanz nicht nur einen wertvollen Beitrag zur Unterstützung von Lernprozessen in der Aus- und Weiterbildung, sondern bietet der Hochschule auch eine Möglichkeit zur Profilierung des Bildungsangebots im Rahmen der Öffentlichkeitsarbeit.

Learning Curves of Temporary Workers in Manual Order Picking Activities

Person-to-stock order picking is highly flexible and requires minimal investment costs in comparison to automated picking solutions. For these reasons, tradi-tional picking is widespread in distribution and production logistics. Due to its typically large proportion of manual activities, picking causes the highest operative personnel costs of all intralogistics process. The required personnel capacity in picking varies short- and mid-term due to capacity requirement fluctuations. These dynamics are often balanced by employing minimal permanent staff and using seasonal help when needed. The resulting high personnel fluctuation necessitates the frequent training of new pickers, which, in combination with in-creasingly complex work contents, highlights the im-portance of learning processes in picking. In industrial settings, learning is often quantified based on diminishing processing time and cost requirements with increasing experience. The best-known industrial learning curve models include those from Wright, de Jong, Baloff and Crossman, which are typically applied to the learning effects of an entire work crew rather than of individuals. These models have been validated in largely static work environments with homogeneous work contents. Little is known of learning effects in picking systems. Here, work contents are heterogeneous and individual work strategies vary among employees. A mix of temporary and steady employees with varying degrees of experience necessitates the observation of individual learning curves. In this paper, the individual picking performance development of temporary employees is analyzed and compared to that of steady employees in the same working environment.

The Position of xMOOCs in Educational Systems

The idea of xMOOCs initially aimed at fundamentally changing the US tertiary education system by providing open mass education. This attempt failed for a number of reasons. They include: the ignorance of the importance and benefits of face-to-face instruction, the high workload imposed on students by xMOOCs, the consequences of current xMOOC didactics, the financing of the high costs, and the difficulties of integration into the teaching organization. As a consequence, xMOOCs are turning into methods for professional continuing education including a business model that covers the institution’s cost.