667 resultados para Structure learning


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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 structure of the 1:1 proton-transfer compound from the reaction of L-tartaric acid with the azo-dye precursor aniline yellow [4-(phenylazo)aniline], 4-(phenyldiazenyl)anilinium hydrogen 2R,3R-tartrate C12H12N3+ . C4H6O6- has been determined at 200 K. The asymmetric unit of the compound contains two independent phenylazoanilinium cations and two hydrogen L-tartrate anions. The structure is unusual in that all four phenyl rings of both cations have identical 50% rotational disorder. The two hydrogen L-tartrate anions form independent but similar chains through head-to-tail carboxylic O--H...O~carboxyl~ hydrogen bonds [graph set C7] which are then extended into a two-dimensional hydrogen-bonded sheet structure through hydroxyl O--H...O hydrogen-bonding links. The anilinium groups of the phenyldiazenyl cations are incorporated into the sheets and also provide internal hydrogen-bonding extensions while their aromatic tails layer in the structure without significant interaction except for weak \p--\p interactions [minimum ring centroid separation, 3.844(3) \%A]. The hydrogen L-tartrate residues of both anions have the common short intramolecular hydroxyl O--H...O~carboxyl~ hydogen bonds. This work has provided a solution to the unusual disorder problem inherent in the structure of this salt as well as giving another example of the utility of the hydrogen tartrate in the generation of sheet substructures in molecular assembly processes.

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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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The application of near-infrared and infrared spectroscopy has been used for identification and distinction of basic Cu-sulphates that include devilline, chalcoalumite and caledonite. Near-infrared spectra of copper sulphate minerals confirm copper in divalent state. Jahn-Teller effect is more significant in chalcoalumite where 2B1g ® 2B2g transition band shows a larger splitting (490 cm-1) confirming more distorted octahedral coordination of Cu2+ ion. One symmetrical band at 5145 cm-1 with shoulder band 5715 cm-1 result from the absorbed molecular water in the copper complexes are the combinations of OH vibrations of H2O. One sharp band at around 3400 cm-1 in IR common to the three complexes is evidenced by Cu-OH vibrations. The strong absorptions observed at 1685 and 1620 cm-1 for water bending modes in two species confirm strong hydrogen bonding in devilline and chalcoalumite. The multiple bands in v3 and v4(SO4)2- stretching regions are attributed to the reduction of symmetry to the sulphate ion from Td to C2V. Chalcoalumite, the excellent IR absorber over the range 3800-500 cm-1 is treated as most efficient heat insulator among the Cu-sulphate complexes.

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This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.

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This paper presents a formulation of image-based visual servoing (IBVS) for a spherical camera where coordinates are parameterized in terms of colatitude and longitude: IBVSSph. The image Jacobian is derived and simulation results are presented for canonical rotational, translational as well as general motion. Problems with large rotations that affect the planar perspective form of IBVS are not present on the sphere, whereas the desirable robustness properties of IBVS are shown to be retained. We also describe a structure from motion (SfM) system based on camera-centric spherical coordinates and show how a recursive estimator can be used to recover structure. The spherical formulations for IBVS and SfM are particularly suitable for platforms, such as aerial and underwater robots, that move in SE(3).

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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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By incorporating ferrocene into the hydrophobic membrane of PEG-b-PCL polymersome nanoparticles it is possible to selectively visualize their core using Transmission Electron Microscopy (TEM). Two different sizes of ferrocene-loaded polymersomes with mean hydrodynamic diameters of approximately 40 and 90 nm were prepared. Image analysis of TEM pictures of these polymersomes found that the mean diameter of the core was 4–5 times smaller than the mean hydrodynamic diameter. The values obtained also allow the surface diameter and internal volume of the core to be calculated.

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Since the formal recognition of practice-led research in the 1990s, many higher research degree candidates in art, design and media have submitted creative works along with an accompanying written document or ‘exegesis’ for examination. Various models for the exegesis have been proposed in university guidelines and academic texts during the past decade, and students and supervisors have experimented with its contents and structure. With a substantial number of exegeses submitted and archived, it has now become possible to move beyond proposition to empirical analysis. In this article we present the findings of a content analysis of a large, local sample of submitted exegeses. We identify the emergence of a persistent pattern in the types of content included as well as overall structure. Besides an introduction and conclusion, this pattern includes three main parts, which can be summarized as situating concepts (conceptual definitions and theories); precedents of practice (traditions and exemplars in the field); and researcher’s creative practice (the creative process, the artifacts produced and their value as research). We argue that this model combines earlier approaches to the exegesis, which oscillated between academic objectivity, by providing a contextual framework for the practice, and personal reflexivity, by providing commentary on the creative practice. But this model is more than simply a hybrid: it provides a dual orientation, which allows the researcher to both situate their creative practice within a trajectory of research and do justice to its personally invested poetics. By performing the important function of connecting the practice and creative work to a wider emergent field, the model helps to support claims for a research contribution to the field. We call it a connective model of exegesis.