Managing large-enrollment courses in hybrid instruction mode

This essay addresses the hitches and glitches in the hybrid instruction system of teaching and learning for large-enrollment courses. This new instructional methodology asks facilitators to redesign their entire traditional teaching and learning practices. The nature of subject to be taught via the hybrid mode further affects the success rate of the modules from the time of inception to launch to actual delivery and completion of the course. The entire process involves undoing the old habits and methodologies and instructors picking up new skills, along with the right motivation to take up the task. The course planning and delivery require a substantial commitment in terms of hours from the instructors catering to large-enrollment courses, along with pursuing their routine roles at the campuses. From the pupil’s perspective, the response varies, as hybrid learning seeks self-discipline and time management skills from the learner. After the initial roadblocks, students enjoy hybrid learning if the course structure and instructions are simple and the course content flexible and varied. We will study the problems and possible solutions to the success of the hybrid teaching–learning system at each stage where large number of students enrolled for a specific course.

Perceptions of physical versus virtual design studio education

While the studio environment has been promoted as an ideal educational setting for project-based disciplines associated with the art and design, few qualitative studies have been undertaken in a comprehensive way, with even fewer giving emphasis to the teachers and students and how they feel about changing their environment. This situation is problematic given the changes and challenges facing higher education, including those associated with new technologies such as online learning. In response, this paper describes a comparative study employing grounded theory to identify and describe teachers’ and students’ perceptions of the physical design studio (PDS) as well as the virtual design studio (VDS) of architectural students in an Australian university. The findings give significance to aspects of design education activities and their role in the development of integrated hybrid learning environments.

Case Study 4: Education Doctoral Student - "An Exploratory Study of Online Social Networking within a Doctorate of Education Program"

Introduction The professional doctorate is specifically designed for professionals investigating real-world problems and relevant issues for a profession, industry, and/or the community. The focus is scholarly research into professional practices. The research programme bridges academia and the professions, and offers doctoral candidates the opportunity to investigate issues relevant to their own practices and to apply these understandings to their professional contexts. The study on which this article is based sought to track the scholarly skill development of a cohort of professional doctoral students who commenced the course in January 2008 at an Australian university. Because they hold positions of responsibility and are time-poor, many doctoral students have difficulty transitioning from professional practitioner to researcher and scholar. The struggle many experience is in the development of a theoretical or conceptual standpoint for argumentation (Lesham, 2007; Weese et al., 1999). It was thought that the use of a scaffolded learning environment that drew upon a blended learning approach incorporating face to face intensive blocks and collaborative knowledge-building tools such as wikis would provide a data source for understanding the development of scholarly skills. Wikis, weblogs and similar social networking software have the potential to support communities to share, learn, create and collaborate. The development of a wiki page by each candidate in the 2008 cohort was encouraged to provide the participants and the teaching team members with textual indicators of progress. Learning tasks were scaffolded with the expectation that the candidates would complete these tasks via the wikis. The expectation was that cohort members would comment on each other’s work, together with the supervisor and/or teaching team member who was allocated to each candidate. The supervisor is responsible for supervising the candidate’s work through to submission of the thesis for examination and the teaching team member provides support to both the supervisor and the candidate through to confirmation. This paper reports on the learning journey of a cohort of doctoral students during the first seven months of their professional doctoral programme to determine if there had been any qualitative shifts in understandings, expectations and perceptions regarding their developing knowledge and skills. The paper is grounded in the literature pertaining to doctoral studies and examines the structure of the professional doctoral programme. Following this is a discussion of the qualitative study that helped to unearth key themes regarding the participants’ learning journey.

Experiments on three-dimensional wire-frame object recognition

Some experimental results on the recognition of three-dimensional wire-frame objects are presented. In order to overcome the limitations of a recent model, which employs radial basis functions-based neural networks, we have proposed a hybrid learning system for object recognition, featuring: an optimization strategy (simulated annealing) in order to avoid local minima of an energy functional; and an appropriate choice of centers of the units. Further, in an attempt to achieve improved generalization ability, and to reduce the time for training, we invoke the principle of self-organization which utilises an unsupervised learning algorithm.

Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

Using self-organising feature maps for the control of artificial organisms

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.

Medical data classification using interval type-2 fuzzy logic system and wavelets

This paper introduces an automated medical data classification method using wavelet transformation (WT) and interval type-2 fuzzy logic system (IT2FLS). Wavelet coefficients, which serve as inputs to the IT2FLS, are a compact form of original data but they exhibits highly discriminative features. The integration between WT and IT2FLS aims to cope with both high-dimensional data challenge and uncertainty. IT2FLS utilizes a hybrid learning process comprising unsupervised structure learning by the fuzzy c-means (FCM) clustering and supervised parameter tuning by genetic algorithm. This learning process is computationally expensive, especially when employed with high-dimensional data. The application of WT therefore reduces computational burden and enhances performance of IT2FLS. Experiments are implemented with two frequently used medical datasets from the UCI Repository for machine learning: the Wisconsin breast cancer and Cleveland heart disease. A number of important metrics are computed to measure the performance of the classification. They consist of accuracy, sensitivity, specificity and area under the receiver operating characteristic curve. Results demonstrate a significant dominance of the wavelet-IT2FLS approach compared to other machine learning methods including probabilistic neural network, support vector machine, fuzzy ARTMAP, and adaptive neuro-fuzzy inference system. The proposed approach is thus useful as a decision support system for clinicians and practitioners in the medical practice. copy; 2015 Elsevier B.V. All rights reserved.

Lernen mit einer Hybride aus Lernendem Klassifizierendem System und Selbstorganisierender Karte

Im Forschungsgebiet der Künstlichen Intelligenz, insbesondere im Bereich des maschinellen Lernens, hat sich eine ganze Reihe von Verfahren etabliert, die von biologischen Vorbildern inspiriert sind. Die prominentesten Vertreter derartiger Verfahren sind zum einen Evolutionäre Algorithmen, zum anderen Künstliche Neuronale Netze. Die vorliegende Arbeit befasst sich mit der Entwicklung eines Systems zum maschinellen Lernen, das Charakteristika beider Paradigmen in sich vereint: Das Hybride Lernende Klassifizierende System (HCS) wird basierend auf dem reellwertig kodierten eXtended Learning Classifier System (XCS), das als Lernmechanismus einen Genetischen Algorithmus enthält, und dem Wachsenden Neuralen Gas (GNG) entwickelt. Wie das XCS evolviert auch das HCS mit Hilfe eines Genetischen Algorithmus eine Population von Klassifizierern - das sind Regeln der Form [WENN Bedingung DANN Aktion], wobei die Bedingung angibt, in welchem Bereich des Zustandsraumes eines Lernproblems ein Klassifizierer anwendbar ist. Beim XCS spezifiziert die Bedingung in der Regel einen achsenparallelen Hyperquader, was oftmals keine angemessene Unterteilung des Zustandsraumes erlaubt. Beim HCS hingegen werden die Bedingungen der Klassifizierer durch Gewichtsvektoren beschrieben, wie die Neuronen des GNG sie besitzen. Jeder Klassifizierer ist anwendbar in seiner Zelle der durch die Population des HCS induzierten Voronoizerlegung des Zustandsraumes, dieser kann also flexibler unterteilt werden als beim XCS. Die Verwendung von Gewichtsvektoren ermöglicht ferner, einen vom Neuronenadaptationsverfahren des GNG abgeleiteten Mechanismus als zweites Lernverfahren neben dem Genetischen Algorithmus einzusetzen. Während das Lernen beim XCS rein evolutionär erfolgt, also nur durch Erzeugen neuer Klassifizierer, ermöglicht dies dem HCS, bereits vorhandene Klassifizierer anzupassen und zu verbessern. Zur Evaluation des HCS werden mit diesem verschiedene Lern-Experimente durchgeführt. Die Leistungsfähigkeit des Ansatzes wird in einer Reihe von Lernproblemen aus den Bereichen der Klassifikation, der Funktionsapproximation und des Lernens von Aktionen in einer interaktiven Lernumgebung unter Beweis gestellt.

Reflective practice at the intersection of the arts, science, and engineering: Ethnographic beginnings of a youth program in transition

Thesis (Master's)--University of Washington, 2016-06

e-Tutor : papel e intervenção na aprendizagem colaborativa em ambientes híbridos

Relatório de estágio apresentado à Escola Superior de Educação de Santarém para cumprimento dos requisitos necessários à obtenção do grau de mestre em Educação e Comunicação Multimédia

e-Tutor : papel e intervenção na aprendizagem colaborativa em ambientes híbridos

Relatório de estágio apresentado à Escola Superior de Educação de Santarém para cumprimento dos requisitos necessários à obtenção do grau de mestre em Educação e Comunicação Multimédia

Technological barriers to learning : designing hybrid pedagogy to minimise cognitive load and maximise understanding

Information and Communication Technologies (ICTs) provide great promise for the future of education. In the Asia-Pacific region, many nations have started working towards the comprehensive development of infrastructure to enable the development of strong networked educational systems. In Queensland there have been significant initiatives in the past decade to support the integration of technology in classrooms and to set the conditions for the enhancement of teaching and learning with technology. One of the great challenges is to develop our classrooms to make the most of these technologies for the benefit of student learning. Recent research and theory into cognitive load, suggests that complex information environments may well impose a barrier on student learning. Further, it suggests that teachers have the capacity to mitigate against cognitive load through the way they prepare and support students engaging with complex information environments. This chapter compares student learning at different levels of cognitive load to show that learning is enhanced when integrating pedagogies are employed to mitigate against high-load information environments. This suggests that a mature policy framework for ICTs in education needs to consider carefully the development of professional capacities to effectively design and integrate technologies for learning.

Determinants of knowledge transfer and learning in hybrid public private alliances

This paper uses the case study of a hybrid public-private strategic alliance as data to complement and contrast with the traditional views on knowledge transfer and learning between alliance partners. In particular, the paper explores whether the concept of competitive collaboration conceptualized by Hamel (1991) in his seminal work holds true for all forms of strategic alliances. Conceptualizing the knowledge boundaries of organisations in alliances as a ‘collaborative membrane’, we focus attention on the permeability of these boundaries rather than the actual location of the boundaries. In this vein, we present a case study of a major public sector organization that illustrates how these principles have allowed it to start rebuilding its internal capabilities adopting a more collaborative stance and ensuring their knowledge boundaries are highly porous as they move more major projects into hybrid public private alliance contracts.

From bricks to clicks : hybrid commercial spaces in the landscape of early literacy and learning

In their quest for resources to support children’s early literacy learning and development, parents encounter and traverse different spaces in which discourses and artifacts are produced and circulated. This paper uses conceptual tools from the field of geosemiotics to examine some commercial spaces designed for parents and children which foreground preschool learning and development. Drawing on data generated in a wider study I discuss some of the ways in which the material and virtual commercial spaces of a transnational shopping mall company and an educational toy company operate as sites of encounter between discourses and artifacts about children’s early learning and parents of preschoolers. I consider how companies connect with and ‘situate’ people as parents and customers, and then offer pathways designed for parents to follow as they attempt to meet their very young children’s learning and development needs. I argue that these pathways are both material and ideological, and that are increasingly tending to lead parents to the online commercial spaces of the world wide web. I show how companies are using the online environment and hybrid offline and online spaces and flows to reinforce an image of themselves as authoritative brokers of childhood resources for parents that is highly valuable in a policy climate which foregrounds lifelong learning and school readiness.

Towards visualising people’s ecology of hybrid personal learning environments

Ambient media architecture can provide place-based collaborative learning experiences and pathways for social interactions that would not be otherwise possible. This paper is concerned with ways of enhancing peer-to-peer learning affordances in library spaces; how can the library facilitate the community of library users to learn from each other? We report on the findings of a study that employed a participatory design method where participants were asked to reflect and draw places, social networks, and activities that they use to work (be creative, productive), play (have fun, socialize, be entertained), and learn (acquire new information, knowledge, or skills). The results illustrate how informal learning – learning outside the formal education system – is facilitated by a personal selection of physical and socio-cultural environments, as well as online tools, platforms, and networks. This paper sheds light on participants’ individually curated ecologies of their work, play, and learning related networks and the hybrid (physical and digital) nature of these places. These insights reveal opportunities for ambient media architecture to increase awareness of and connections between people’s hybrid personal learning environments.