999 resultados para Learning Landscapes


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Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies.

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Student learning research literature has shown that students' learning approaches are influenced by the learning context (Evans, Kirby, & Fabrigar, 2003). Of the many contextual factors, assessment has been found to have the most important influence on the way students go about learning. For example, assessment that is perceived to required a low level of cognitive abilities will more likely elicit a learning approach that concentrate on reproductive learning activities. Moreover, assessment demand will also interact with learning approach to determine academic performance. In this paper an assessment specific model of learning comprising presage, process and product variables (Biggs, 2001) was proposed and tested against data obtained from a sample of introductory economics students (n=434). The model developed was used to empirically investigate the influence of learning inputs and learning approaches on academic performances across assessment types (essay assignment, multiple choice question exam and exam essay). By including learning approaches in the learning model, the mechanism through which learning inputs determine academic performance was examined. Methodological limitations of the study will also be discussed.

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Economics education research studies conducted in the UK, USA and Australia to investigate the effects of learning inputs on academic performance have been dominated by the input-output model (Shanahan and Meyer, 2001). In the Student Experience of Learning framework, however, the link between learning inputs and outputs is mediated by students' learning approaches which in turn are influenced by their perceptions of the learning contexts (Evans, Kirby, & Fabrigar, 2003). Many learning inventories such as Biggs' Study Process Questionnaires and Entwistle and Ramsden' Approaches to Study Inventory have been designed to measure approaches to academic learning. However, there is a limitation to using generalised learning inventories in that they tend to aggregate different learning approaches utilised in different assessments. As a result, important relationships between learning approaches and learning outcomes that exist in specific assessment context(s) will be missed (Lizzio, Wilson, & Simons, 2002). This paper documents the construction of an assessment specific instrument to measure learning approaches in economics. The post-dictive validity of the instrument was evaluated by examining the association of learning approaches to students' perceived assessment demand in different assessment contexts.

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Knowledge intensive services are the fastest growing segment of the international economy and the digital creative industries are a key segment therein. Australia is well positioned to exploit this opportunity but has a skills shortage in the digital content industries in terms of commercial ready graduates. We report on a solution to this problem, in the form of an online creative community of practice – www.60Sox.org - where new graduates are mentored by Australian industry leaders - the 2bobmob. We describe this community of practice as a virtual creative ecology and discuss networks, peer feedback and mentoring as key elements of post-tertiary learning, in the context of portfolio career progression.

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In the study of student learning literature, the traditional view holds that when students are faced with heavy workload, poor teaching, and content that they cannot relate to – important aspects of the learning context, they will more likely utilise the surface approach to learning due to stresses, lack of understanding and lack of perceived relevance of the content (Kreber, 2003; Lizzio, Wilson, & Simons, 2002; Ramdsen, 1989; Ramsden, 1992; Trigwell & Prosser, 1991; Vermunt, 2005). For example, in studies involving health and medical sciences students, courses that utilised student-centred, problem-based approaches to teaching and learning were found to elicit a deeper approach to learning than the teacher-centred, transmissive approach (Patel, Groen, & Norman, 1991; Sadlo & Richardson, 2003). It is generally accepted that the line of causation runs from the learning context (or rather students’ self reported data on the learning context) to students’ learning approaches. That is, it is the learning context as revealed by students’ self-reported data that elicit the associated learning behaviour. However, other research studies also found that the same teaching and learning environment can be perceived differently by different students. In a study of students’ perceptions of assessment requirements, Sambell and McDowell (1998) found that students “are active in the reconstruction of the messages and meanings of assessment” (p. 391), and their interpretations are greatly influenced by their past experiences and motivations. In a qualitative study of Hong Kong tertiary students, Kember (2004) found that students using the surface learning approach reported heavier workload than students using the deep learning approach. According to Kember if students learn by extracting meanings from the content and making connections, they will more likely see the higher order intentions embodied in the content and the high cognitive abilities being assessed. On the other hand, if they rote-learn for the graded task, they fail to see the hierarchical relationship in the content and to connect the information. These rote-learners will tend to see the assessment as requiring memorising and regurgitation of a large amount of unconnected knowledge, which explains why they experience a high workload. Kember (2004) thus postulate that it is the learning approach that influences how students perceive workload. Campbell and her colleagues made a similar observation in their interview study of secondary students’ perceptions of teaching in the same classroom (Campbell et al., 2001). The above discussions suggest that students’ learning approaches can influence their perceptions of assessment demands and other aspects of the learning context such as relevance of content and teaching effectiveness. In other words, perceptions of elements in the teaching and learning context are endogenously determined. This study attempted to investigate the causal relationships at the individual level between learning approaches and perceptions of the learning context in economics education. In this study, students’ learning approaches and their perceptions of the learning context were measured. The elements of the learning context investigated include: teaching effectiveness, workload and content. The authors are aware of existence of other elements of the learning context, such as generic skills, goal clarity and career preparation. These aspects, however, were not within the scope of this present study and were therefore not investigated.

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The result of a forum on community engagement held in November 2008 at Bond University, Community Engagement in Contemporary Legal Education is a compilation of papers presented at the forum by academics and professionals throughout Australia. Although found initially to be a topic of legal interest, it was not until the reviewer came across the Council of Australian Law Deans (CALD) “Standards for Australian Law Schools” (adopted 17 November 20093) then the full importance and potential of this book was revealed. Clause 2.2.4 of the CALD Standards recognises the importance of “experiential learning opportunities” for law students and cites examples such as clinical programs, internships, practical experience and pro-bono work. Clause 2.3.3 acknowledges the need to develop professional ethics and again cites pro-bono obligations as an example. Clause 9.6.2 encourages interaction of law schools with the profession and the community and again, pro-bono community service is identified as one method of doing so. Yet nowhere in the document are there any uniform standards or binding obligations that law schools must commit to. In the current climate where the importance of practical experience is continually emphasised and student numbers exceed the number of available paid legal positions, there should be more focus on the details of how these commitments should be converted to be included in a law school’s curriculum.

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The role of intangible firm capabilities as a source of competitive advantage has come into prominence in marketing strategy literature, due to the Resource Based View. This paper applies the Resource Based View and hypothesizes that strategic flexibility and organisation learning, conceptualised as capabilities, positively effect e-business adoption and competitive advantage. Partial Lease Squares analysis suggest that theoretical constructs function as hypothesised and explain a significant variation on e-business adoption and competitive advantage. Firms adopting e-business should develop capabilities such as strategic flexibility and organisation learning and that vendor firms may segment their potential clients based on these capabilities.

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RatSLAM is a biologically-inspired visual SLAM and navigation system that has been shown to be effective indoors and outdoors on real robots. The spatial representation at the core of RatSLAM, the experience map, forms in a distributed fashion as the robot learns the environment. The activity in RatSLAM’s experience map possesses some geometric properties, but still does not represent the world in a human readable form. A new system, dubbed RatChat, has been introduced to enable meaningful communication with the robot. The intention is to use the “language games” paradigm to build spatial concepts that can be used as the basis for communication. This paper describes the first step in the language game experiments, showing the potential for meaningful categorization of the spatial representations in RatSLAM.

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Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

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Optical flow (OF) is a powerful motion cue that captures the fusion of two important properties for the task of obstacle avoidance − 3D self-motion and 3D environmental surroundings. The problem of extracting such information for obstacle avoidance is commonly addressed through quantitative techniques such as time-to-contact and divergence, which are highly sensitive to noise in the OF image. This paper presents a new strategy towards obstacle avoidance in an indoor setting, using the combination of quantitative and structural properties of the OF field, coupled with the flexibility and efficiency of a machine learning system.The resulting system is able to effectively control the robot in real-time, avoiding obstacles in familiar and unfamiliar indoor environments, under given motion constraints. Furthermore, through the examination of the networks internal weights, we show how OF properties are being used toward the detection of these indoor obstacles.

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To promote and support informed discussion, we look here at the experiences of some services in the national trial of the draft Early Years Learning Framework, and the more recent trial of the supporting draft Educator's Guide. Reflecting on these experiences, the paper offers some examples of how a service can 'get started' with the EYLF.

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An Interactive Installation with holographic 3D projections, satellite imagery, surround sound and intuitive body driven interactivity. Remnant (v.1) was commissioned by the 2010 TreeLine ecoArt event - an initiative of the Sunshine Coast Council and presented at a remnant block of subtropical rainforest called ‘Mary Cairncross Scenic Reserve’ - located 100kms north of Brisbane near the township of Maleny. V2 was later commissioned for KickArts Gallery, Cairns, re-presenting the work in a new open format which allowed audiences to both experience the original power of the work and to also understand the construction of the work's powerful illusory, visual spaces. This art-science project focused upon the idea of remnant landscapes - isolated blocks of forest (or other vegetation types) typically set within a patchwork quilt of surrounding farmed land. Participants peer into a mysterious, long tunnel of imagery whilst navigating entirely through gentle head movements - allowing them to both 'steer' in three dimensions and also 'alight', as a butterfly might, upon a sector of landscape - which in turn reveals an underlying 'landscape of mind'. The work challenges audiences to re-imagine our conceptions of country in ways that will lead us to better reconnect and sustain today’s heavily divided landscapes. The research field involved developing new digital image projection methods, alternate embodied interaction and engagement strategies for eco-political media arts practice. The context was the creation of improved embodied and improvisational experiences for participants, further informed by ‘eco-philosophical’ and sustainment theories. By engaging with deep conceptions of connectivity between apparently disparate elements, the work considered novel strategies for fostering new desires, for understanding and re-thinking the requisite physical and ecological links between ‘things’ that have been historically shattered. The methodology was primarily practice-led and in concert with underlying theories. The work’s knowledge contribution was to question how new media interactive experience and embodied interaction might prompt participants to reflect upon appropriate resources and knowledges required to generate this substantive desire for new approaches to sustainment. This accentuated through the power of learning implied by the works' strongly visual and kinaesthetic interface (i.e. the tunnel of imagery and the head and torso operated navigation). The work was commissioned by the 2010 TreeLine ecoArt event - an initiative of the Sunshine Coast Council and the second version was commissioned by Kickarts Gallery, Cairns, specifically funded by a national optometrist chain. It was also funded in development by Arts Queensland and reviewed in Realtime.

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This paper details the development of a machine learning system which uses the helicopter state and the actions of an instructing pilot to synthesise helicopter control modules online. Aggressive destabilisation/restabilisation sequences are used for training, such that a wide state space envelope is covered during training. The performance of heading, roll, pitch, height and lateral velocity control learning is presented using our Xcell 60 experimental platform. The helicopter is demonstrated to be stabilised on all axes using the “learning from a pilot” technique. To our knowledge, this is the first time a “learning from a pilot” technique has been successfully applied to all axes.

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Historically, distance education consisted of a combination of face-to-face blocks of time and surface mailed packages. However, advances in information technology literacy and the abundance of personal computers has placed e-learning in increased demand. The authors describe the planning, implementation, and evaluation of the blending of e-learning with face-to-face education in the postgraduate nursing forum. Experiences of this particular student group are also discussed.