Network of Australiasian Tertiary Associations: a space for discussion, collaboration and advocacy in tertiary education

This presentation explores the development of a network focused on enhancing network leadership in tertiary education associations. The Network of Australasian Tertiary Associations (NATA) is an Office for Learning and Teaching (OLT) project that aims at facilitating a sustainable collaborative network between established higher education associations. NATA provides a space for discussion, action and advocacy on key issues pertinent to the Australasian tertiary environment. Members of NATA comprise Australasian Society for Computers in Learning in Tertiary Education (ascilite), Australasian Council on Open, Distance and e-learning (ACODE), The Higher Education Research and Development Society of Australasia, (HERDSA), The Council of Australian Directors of Academic Development, (CADAD), Open and Distance Learning Association of Australia (ODLAA), Australian Academic and Research Network (AARNet) and Netspot. Networks are important hubs for the development of new ideas and are discussion and dissemination spaces for individuals and communities. The project is now focused on progressing achieving the NATA's key objectives through three strategic activities. These comprise: ● Disseminating the ALTC Good Practice Reports through the development of asynchronous 'E' Resources, completed in partnership with report authors ● Conducting research into the network and network leadership through interviews, focus groups and surveys ● Supporting partner associations to engage in small-scale projects aligned with the key objectives of both the NATA and their association to provide value to the sector and strengthen communication and engagement of NATA partners. Through the creation of collaborative connected spaces for discourse and action, the NATA aspires to develop a model that will influence policy, research and learning and teaching in the Australasian tertiary environment

Unsupervised Neural Network for the Control of a Mobile Robot

This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.Sloan Fellowship (BR-3122); Air Force Office of Scientific Research (F49620-92-J-0499

A Real-Time Unsupervised Neural Network for the Low-Level Control of a Mobile Robot in a Nonstationary Environment

This article introduces a real-time, unsupervised neural network that learns to control a two-degree-of-freedom mobile robot in a nonstationary environment. The neural controller, which is termed neural NETwork MObile Robot Controller (NETMORC), combines associative learning and Vector Associative Map (YAM) learning to generate transformations between spatial and velocity coordinates. As a result, the controller learns the wheel velocities required to reach a target at an arbitrary distance and angle. The transformations are learned during an unsupervised training phase, during which the robot moves as a result of randomly selected wheel velocities. The robot learns the relationship between these velocities and the resulting incremental movements. Aside form being able to reach stationary or moving targets, the NETMORC structure also enables the robot to perform successfully in spite of disturbances in the enviroment, such as wheel slippage, or changes in the robot's plant, including changes in wheel radius, changes in inter-wheel distance, or changes in the internal time step of the system. Finally, the controller is extended to include a module that learns an internal odometric transformation, allowing the robot to reach targets when visual input is sporadic or unreliable.Sloan Fellowship (BR-3122), Air Force Office of Scientific Research (F49620-92-J-0499

Professional discourse, quality assurance and a practice integrated pre-service teacher education course: The Open University PGCE

The Open University (UK) Postgraduate Certificate in Education (PGCE) programme is a distance learning pre-service course in teacher education which integrates learning in the practice setting with university-based learning. This programme, which has flexible start and finish points and either training or assessment only routes, uses a web-based Needs Analysis process to reflect on prior experience and to determine individualized university and practice-based curriculum and assessment and is set in the context of an external regulatory framework which demands that teacher education courses in England fulfil certain national requirements and that student-teachers meet identified standards or competences. These requirements and standards are inspected by the Office for Standards in Education (OfSTED) and the outcomes of inspection lead to a 'Quality Grade' which determines government funding. This PGCE course, therefore, presents a radically flexible, practice integrated programme which faces both internal, University based quality assurance processes and procedures and 'high stakes' external inspection. This paper reflects on the tensions between quality compliance and quality assurance in practice integrated learning and suggests that quality assurance processes which open up a discourse of personal and professional development and which might support the exploration of dissonance between and within practices can improve, rather than merely maintain, programme quality

Neural Controller for a Mobile Robot in a Nonstationary Enviornment

Recently it has been introduced a neural controller for a mobile robot that learns both forward and inverse odometry of a differential-drive robot through an unsupervised learning-by-doing cycle. This article introduces an obstacle avoidance module that is integrated into the neural controller. This module makes use of sensory information to determine at each instant a desired angle and distance that causes the robot to navigate around obstacles on the way to a final target. Obstacle avoidance is performed in a reactive manner by representing the objects and target in the robot's environment as Gaussian functions. However, the influence of the Gaussians is modulated dynamically on the basis of the robot's behavior in a way that avoids problems with local minima. The proposed module enables the robot to operate successfully with different obstacle configurations, such as corridors, mazes, doors and even concave obstacles.Air Force Office of Scientific Research (F49620-92-J-0499

Neural Representations for Sensory-Motor Control I: Head-Centered 3-D Target Positions from Opponent Eye Commands

This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This representation implicitly defines a cyclopean coordinate system whose variables approximate the binocular vergence and spherical horizontal and vertical angles with respect to the observer's head. Various psychophysical data concerning binocular distance perception and reaching behavior are clarified by this representation. The representation provides a foundation for learning head-centered and body-centered invariant representations of both foveated and non-foveated 3-D target positions. It also enables a solution to be developed of the classical motor equivalence problem, whereby many different joint configurations of a redundant manipulator can all be used to realize a desired trajectory in 3-D space.Air Force Office of Scientific Research (URI 90-0175); Defense Advanced Research Projects Agency (AFOSR-90-0083); National Science Foundation (IRI-87-16960, IRI-90-24877

Spreading Awareness and Job Opportunities Through Odl

Distance Education has done miracles in the field of education, it caters to those students who study and work on their own at home or at the office and communicate with faculty and other students via e-mail, electronic forums, video conferencing, chat rooms, boards, instant messaging and varieties of other forms of computer-based communication. Distance learning makes it much easier for some students to complete a degree or get additional job-training while balancing work and family commitments. This article elaborates upon the significance of Distance Education discussing various job oriented courses offered by Open universities to aspirants seeking degrees for a better resume and for career enhancements

New means of distance education information technology mathematics destination

In article we are introduced a new conception of distance learning: mobile Eoffice (based on PocketPC and E-book). Due to distant learning the information technologies of mathematical purpose was designed a mobile version of CAS Maxima. Described a frontier facility for testing students’ achievements in mobile E-office: student response systems.У статті ми ввели нову концепцію дистанційного навчання: мобільний Eoffice (на основі персонального ПК й електронної книги). Завдяки дистанційному навчанню інформаційні технології математичного призначення була розроблена мобільна версія CAS Maxima. Описано центр для тестування досягнень учнів в області мобільних Eoffice: студентська система реагування