Locally weighted learning model predictive control for nonlinear and time varying dynamics

This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.

Process model comprehension : the effects of cognitive abilities, learning style, and strategy

Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.

Learning processes in creative service teams : towards a dynamic systems theory

The fastest-growing segment of jobs in the creative sector are in those firms that provide creative services to other sectors (Hearn, Goldsmith, Bridgstock, Rodgers 2014, this volume; Cunningham 2014, this volume). There are also a large number of Creative Services (Architecture and Design, Advertising and Marketing, Software and Digital Content occupations) workers embedded in organizations in other industry sectors (Cunningham and Higgs 2009). Ben Goldsmith (2014, this volume) shows, for example, that the Financial Services sector is the largest employer of digital creative talent in Australia. But why should this be? We argue it is because ‘knowledge-based intangibles are increasingly the source of value creation and hence of sustainable competitive advantage (Mudambi 2008, 186). This value creation occurs primarily at the research and development (R and D) and the marketing ends of the supply chain. Both of these areas require strong creative capabilities in order to design for, and to persuade, consumers. It is no surprise that Jess Rodgers (2014, this volume), in a study of Australia’s Manufacturing sector, found designers and advertising and marketing occupations to be the most numerous creative occupations. Greg Hearn and Ruth Bridgstock (2013, forthcoming) suggest ‘the creative heart of the creative economy […] is the social and organisational routines that manage the generation of cultural novelty, both tacit and codified, internal and external, and [cultural novelty’s] combination with other knowledges […] produce and capture value’. 2 Moreover, the main “social and organisational routine” is usually a team (for example, Grabher 2002; 2004).

Theorizing why in e-learning – a frontier for cognitive engagement

Asking why is an important foundation of inquiry and fundamental to the development of reasoning skills and learning. Despite this, and despite the relentless and often disruptive nature of innovations in information and communications technology (ICT), sophisticated tools that directly support this basic act of learning appear to be undeveloped, not yet recognized, or in the very early stages of development. Why is this so? To this question, there is no single satisfactory answer; instead, numerous plausible explanations and related questions arise. After learning something, however, explaining why can be revealing of a person’s understanding (or lack of it). What then differentiates explanation from information; and, explanatory from descriptive content? What ICT scaffolding might support inquiry instigated by why-questioning? What is the role of reflective practice in inquiry-based learning? These and other questions have emerged from this investigation and underscore that why-questions often propagate further questions and are a catalyst for cognitive engagement and dialogue. This paper reports on a multi-disciplinary, theoretical investigation that informs the broad discourse on e-learning and points to a specific frontier for design and development of e-learning tools. Probing why reveals that versatile and ambiguous semantics present the core challenge – asking, learning, knowing, understanding, and explaining why.

Scaffolding reflective inquiry - enabling why-questioning while e-Learning

This paper presents some theoretical and interdisciplinary perspectives that might inform the design and development of information and communications technology (ICT) tools to support reflective inquiry during e-learning. The role of why-questioning provides the focus of discussion and is guided by literature that spans critical thinking, inquiry-based and problem-based learning, storytelling, sense-making, and reflective practice, as well as knowledge management, information science, computational linguistics and automated question generation. It is argued that there exists broad scope for the development of ICT scaffolding targeted at supporting reflective inquiry duringe-learning. Evidence suggests that wiki-based learning tasks, digital storytelling, and e-portfolio tools demonstrate the value of accommodating reflective practice and explanatory content in supporting learning; however, it is also argued that the scope for ICT tools that directly support why-questioning as a key aspect of reflective inquiry is a frontier ready for development.

Opening digital learning to deeper inquiry

This chapter presents an historical narrative on the recent evolution of information and communications technology (ICT) that has been, and is, utilized for purposes of learning. In other words, it presents an account of the development of e-learning supported through the Web and other similar virtual environments. It does not attempt to present a definitive account; as such an exercise is fraught with assumptions, contextual bias, and probable conjecture. The concern here is more with contextualizing the role of inquiry in learning and the evolving digital tools that enable interfaces that promote and support it. In tracking this evolution, both multi-disciplinary and trans-disciplinary research has been pursued. Key historical developments are identified as well as interpretations of the key drivers of e-learning over time and into what might be better described as digital learning. Innovations in the development of digital tools are described as dynamic and emergent, evolving as a consequence of multiple, sometimes hidden drivers of change. But conflating advancements in learning technologies with e-learning seems to be pervasive. As is the push for the “open” agenda – a growing number of initiatives and movements dominated by themes associated with access, intellectual property, public benefit, sharing and technical interoperability. Openness is also explored in this chapter, however, more in terms of what it means when associated with inquiry. By investigating opportunities for the stimulation and support of questioning online – in particular, why-questioning – this chapter is focused on “opening” content – not just for access but for inquiry and deeper learning.

Objectifying the Subjective : Assessment and Feedback in Creative Arts Studio Learning and Teaching

This paper examines the Assessment and Feedback aspects of Studio Teaching as Creative Arts pedagogy. Prompted by USQ’s newly offered Bachelor of Creative Arts (BCA), the author has developed an Assessment Matrix specifically designed to satisfy a number of imperatives, including: • ‘objectifying’ the subjective aspects of creative practice as assessable coursework/research • providing the means by which accurate, detailed, personalised and confidential feedback may be provided to students individually • providing consistent, accurate, meaningful assessment records for student, lecturer, and institution • ensuring consistency, continuity, and transparency of assessment processes and records to satisfy quality audits • minimising marking and assessment time, whilst maximising assessment integrity and depth • requiring only basic level skills and knowledge of a computer application already in common use (Microsoft Excel) • adaptability to a range of creative courses ‐ across disciplines This Assessment Matrix has been in development (and trialled) since January 2009.

Contemporary challenges in e-learning

Technology is impacting on most elements of organisations today and workforce development professionals have been some of the leading proponents of embracing technologies and the benefits they offer. E-learning has emerged as at least a complementary offering to face-to-face training, and in some cases has totally replaced more traditional forms of workforce development. This chapter explores the use of learning technologies and the benefits and drawbacks of their use. In particular it focuses on further exploring the issue of a perceived lack of interaction in some e-learning offerings; a factor identified as critical to address in order to ensure effective e-learning. The chapter discusses the issues of interaction and social presence to address feelings of isolation and offers some key considerations for those considering integrating technology into workforce development.

Using cost-effective multimedia to create engaging learning experiences : Resources Manual

A guide to utilising multi-media for teaching and learning.

Technological tools for science classrooms : choosing and using for productive and sustainable teaching and learning experiences

In this age of rapidly evolving technology, teachers are encouraged to adopt ICTs by government, syllabus, school management, and parents. Indeed, it is an expectation that teachers will incorporate technologies into their classroom teaching practices to enhance the learning experiences and outcomes of their students. In particular, regarding the science classroom, a subject that traditionally incorporates hands-on experiments and practicals, the integration of modern technologies should be a major feature. Although myriad studies report on technologies that enhance students’ learning outcomes in science, there is a dearth of literature on how teachers go about selecting technologies for use in the science classroom. Teachers can feel ill prepared to assess the range of available choices and might feel pressured and somewhat overwhelmed by the avalanche of new developments thrust before them in marketing literature and teaching journals. The consequences of making bad decisions are costly in terms of money, time and teacher confidence. Additionally, no research to date has identified what technologies science teachers use on a regular basis, and whether some purchased technologies have proven to be too problematic, preventing their sustained use and possible wider adoption. The primary aim of this study was to provide research-based guidance to teachers to aid their decision-making in choosing technologies for the science classroom. The study unfolded in several phases. The first phase of the project involved survey and interview data from teachers in relation to the technologies they currently use in their science classrooms and the frequency of their use. These data were coded and analysed using Grounded Theory of Corbin and Strauss, and resulted in the development of a PETTaL model that captured the salient factors of the data. This model incorporated usability theory from the Human Computer Interaction literature, and education theory and models such as Mishra and Koehler’s (2006) TPACK model, where the grounded data indicated these issues. The PETTaL model identifies Power (school management, syllabus etc.), Environment (classroom / learning setting), Teacher (personal characteristics, experience, epistemology), Technology (usability, versatility etc.,) and Learners (academic ability, diversity, behaviour etc.,) as fields that can impact the use of technology in science classrooms. The PETTaL model was used to create a Predictive Evaluation Tool (PET): a tool designed to assist teachers in choosing technologies, particularly for science teaching and learning. The evolution of the PET was cyclical (employing agile development methodology), involving repeated testing with in-service and pre-service teachers at each iteration, and incorporating their comments i ii in subsequent versions. Once no new suggestions were forthcoming, the PET was tested with eight in-service teachers, and the results showed that the PET outcomes obtained by (experienced) teachers concurred with their instinctive evaluations. They felt the PET would be a valuable tool when considering new technology, and it would be particularly useful as a means of communicating perceived value between colleagues and between budget holders and requestors during the acquisition process. It is hoped that the PET could make the tacit knowledge acquired by experienced teachers about technology use in classrooms explicit to novice teachers. Additionally, the PET could be used as a research tool to discover a teachers’ professional development needs. Therefore, the outcomes of this study can aid a teacher in the process of selecting educationally productive and sustainable new technology for their science classrooms. This study has produced an instrument for assisting teachers in the decision-making process associated with the use of new technologies for the science classroom. The instrument is generic in that it can be applied to all subject areas. Further, this study has produced a powerful model that extends the TPACK model, which is currently extensively employed to assess teachers’ use of technology in the classroom. The PETTaL model grounded in data from this study, responds to the calls in the literature for TPACK’s further development. As a theoretical model, PETTaL has the potential to serve as a framework for the development of a teacher’s reflective practice (either self evaluation or critical evaluation of observed teaching practices). Additionally, PETTaL has the potential for aiding the formulation of a teacher’s personal professional development plan. It will be the basis for further studies in this field.

A cognitive processing framework for learning analytics

Incorporating a learner’s level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom’s taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course.

Tablets (iPad) for M-Learning in the context of social constructivism to institute an effective learning environment

With the proliferation of mobile devices, educational institutions have experimented with various mobile devices to implement mobile learning (M-Learning). Mobile devices have been used to facilitate, support, and enhance and extend the reach of teaching and learning. Although there are very few empirically evaluated studies on M-Learning projects, these studies reported that mobile devices brought a transformation to the educational process. To be able to view M-Learning as a rich, collaborative and conversational experience, whether in the classroom or outside we need good mobile applications. Studies have revealed that effective learning happens when teachers and learners are actively participating in the knowledge building process. Therefore, there is a need for applications that create effective learning environments which are learner-centred, knowledge-centred, assessment-centred and community-centred.

Learning routines used by firms during construction of infrastructure projects using the alliance procurement method

Collaborative contracting has emerged over the past 15 years as an innovative project delivery framework that is particularly suited to infrastructure projects. Australia leads the world in the development of project and program alliance approaches to collaborative delivery. These approaches are considered to promise superior project results. However, very little is known about the learning routines that are most widely used in support of collaborative projects in general and alliance projects in particular. The literature on absorptive capacity and dynamic capabilities indicates that such learning enhances project performance. The learning routines employed at corporate level during the operation of collaborative infrastructure projects in Australia were examined through a large survey conducted in 2013. This paper presents a descriptive summary of the preliminary findings. The survey captured the experiences of 320 practitioners of collaborative construction projects, including public and private sector clients, contractors, consultants and suppliers (three per cent of projects were located in New Zealand, but for brevity’s sake the sample is referred to as Australian). The majority of projects identified used alliances (78.6%); whilst 9% used Early Contractor Involvement (ECI) contracts and 2.7% used Early Tender Involvement contracts, which are ‘slimmer’ types of collaborative contract. The remaining 9.7% of respondents used traditional contracts that employed some collaborative elements. The majority of projects were delivered for public sector clients (86.3%), and/or clients experienced with asset procurement (89.6%). All of the projects delivered infrastructure assets; one third in the road sector, one third in the water sector, one fifth in the rail sector, and the rest spread across energy, building and mining. Learning routines were explored within three interconnected phases: knowledge exploration, transformation and exploitation. The results show that explorative and exploitative learning routines were applied to a similar extent. Transformative routines were applied to a relatively low extent. It was also found that the most highly applied routine is ‘regularly applying new knowledge to collaborative projects’; and the least popular routine was ‘staff incentives to encourage information sharing about collaborative projects’. Future research planned by the authors will examine the impact of these routines on project performance.

Product feature taxonomy learning based on user reviews

In recent years, the Web 2.0 has provided considerable facilities for people to create, share and exchange information and ideas. Upon this, the user generated content, such as reviews, has exploded. Such data provide a rich source to exploit in order to identify the information associated with specific reviewed items. Opinion mining has been widely used to identify the significant features of items (e.g., cameras) based upon user reviews. Feature extraction is the most critical step to identify useful information from texts. Most existing approaches only find individual features about a product without revealing the structural relationships between the features which usually exist. In this paper, we propose an approach to extract features and feature relationships, represented as a tree structure called feature taxonomy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature taxonomy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that our proposed approach is able to capture the product features and relations effectively.

A state-wide systems approach to embedding the learning and teaching of sustainability in teacher education

Education systems have a key role to play in preparing future citizens to engage in sustainable living practices and help create a more sustainable world. Many schools throughout Australia have begun to develop whole-school approaches to sustainability education that are supported by national and state policies and curriculum frameworks. Preservice teacher education, however, lags behind in building the capacity of new teachers to initiate and implement such approaches (ARIES, 2010). This proposed project seeks to develop a state-wide systems approach to embedding Education for Sustainability (EfS) in teacher education that is aligned with the Australian National Curriculum and the aspirations for EfS in the Melbourne Declaration and other national documents. Representatives from all teacher education institutions and other agents of change in the Queensland education system will be engaged in a multilevel systems approach, involving collaboration at the state, institutional and course levels, to develop curriculum practices that reflect a shared vision of EfS.