The Networks of Learning in Technological Innovation : The Emergence of Collaboration Across Fields of Expertise

This study addresses four issues concerning technological product innovations. First, the nature of the very early phases or "embryonic stages" of technological innovation is addressed. Second, this study analyzes why and by what means people initiate innovation processes outside the technological community and the field of expertise of the established industry. In other words, this study addresses the initiation of innovation that occurs without the expertise of established organizations, such as technology firms, professional societies and research institutes operating in the technological field under consideration. Third, the significance of interorganizational learning processes for technological innovation is dealt with. Fourth, this consideration is supplemented by considering how network collaboration and learning change when formalized product development work and the commercialization of innovation advance. These issues are addressed through the empirical analysis of the following three product innovations: Benecol margarine, the Nordic Mobile Telephone system (NMT) and the ProWellness Diabetes Management System (PDMS). This study utilizes the theoretical insights of cultural-historical activity theory on the development of human activities and learning. Activity-theoretical conceptualizations are used in the critical assessment and advancement of the concept of networks of learning. This concept was originally proposed by the research group of organizational scientist Walter Powell. A network of learning refers to the interorganizational collaboration that pools resources, ideas and know-how without market-based or hierarchical relations. The concept of an activity system is used in defining the nodes of the networks of learning. Network collaboration and learning are analyzed with regard to the shared object of development work. According to this study, enduring dilemmas and tensions in activity explain the participants' motives for carrying out actions that lead to novel product concepts in the early phases of technological innovation. These actions comprise the initiation of development work outside the relevant fields of expertise and collaboration and learning across fields of expertise in the absence of market-based or hierarchical relations. These networks of learning are fragile and impermanent. This study suggests that the significance of networks of learning across fields of expertise becomes more and more crucial for innovation activities.

Building personas of students accessing a peer-facilitated support for learning program

The modern student represents a change from the traditional learner. More than ever before, additional resources are available online and yet personalised learning and peer-assistance programs are becoming an essential part of tertiary education delivery. This paper presents the first stage in a user-centred design approach to the analysis of the completeness and efficacy of such a personalised, peer-based support for learning program. This approach used an iterative design methodology based on contextual interview, workshops and focus groups to develop personas representing students visiting the program. Initial uses of these developed personas have included training of new personnel as well as the evaluation of the program. Overall the use of this user-centred approach and iterative persona development methodology has yielded an invaluable resource for the design of support for learning programs across the higher education industry within Australia and beyond.

Can teacher collaboration overcome barriers to interdisciplinary learning in a disciplinary university? A case study using climate change

A teacher network was formed at an Australian university in order to better promote interdisciplinary student learning on the complex social-environmental problem of climate change. Rather than leaving it to students to piece together disciplinary responses, eight teaching academics collaborated on the task of exposing students to different types of knowledge in a way that was more than the summing of disciplinary parts. With a part-time network facilitator providing cohesion, network members were able to teach into each other’s classes, and share material and student activities across a range of units that included business, zoology, marine science, geography and education. Participants reported that the most positive aspects of the project were the collegiality and support for teaching innovation provided by peers. However, participants also reported being time-poor and overworked. Maintaining the collaboration beyond the initial one year project proved difficult because without funding for the network facilitator, participants were unable to dedicate the time required to meet and collaborate on shared activities. In order to strengthen teacher collaboration in a university whose administrative structures are predominantly discipline-based, there is need for recognition of the benefits of interdisciplinary learning to be matched by recognition of the need for financial and other resources to support collaborative teaching initiatives.

Editorial - TL Forum 2015: Teaching and learning uncapped

The authors discuss the teaching and learning forum and the number of submissions to its staff from 2006-2015.

Transforming teaching practice through virtual classrooms: A study of staff and student views of synchronous learning

Australia is a vast land and access to quality higher education is challenging for many Australians that live outside the larger metropolitan areas. In 2010, the School of Education at an Australian university (Curtin University in Western Australia) moved to flexible delivery of a fully online Bachelor of Education degree for their rural students. The new model of delivery allows access for students from any location provided they have a computer and an internet connection.A number of teaching staff had previously used an asynchronous environment to deliver learning modules housed within a learning management system (LMS) but had not used synchronous software with their students. To enhance the learning environment and to provide high quality learning experiences to students learning at a distance, the adoption of synchronous software (Elluminate Live) was introduced. This software is a real-time virtual classroom environment that allows for communication through Voice over Internet Protocol (VoIP) and video conferencing, alongside a large number of collaboration tools to engage learners.This research paper reports on the integration of a live e-learning solution into the current Learning Management System (LMS) environment. Staff were interviewed about their perceptions and a questionnaire was administered to a sample of students to identify their experience with the synchronous software in order to inform future practice.

Interview with Barbara Comber in "Chapter 3 : Critical Literacy" of "Making Literacy Real : Theories and Practices for Learning and Teaching [2nd. Ed.]"

One of the so-called ‘wicked problems’ confronting most nations is poverty, or the unequal distribution of resources. This problem is perennial, but how, where and with which physical, psychological, social and educational effects, and for which students (and their teachers), needs continual scrutiny. Poverty is relative. Entire populations may be poor or groups of people and individuals within nations may be poor. Poverty results from injustice. Not only the un- and under-employed are living in poverty, but also the ‘working poor’. Now we see affluent societies with growing pockets of persistent poverty. While there are those who dispute the statistics on the rise of poverty because different nations use different measures (for example see Biddle, 2013; http://theconversation.com/factcheck-is-poverty-on-the-rise-in-australia-17512), there seems to be little dispute that the gaps between the richest and the poorest are increasing (see http://www.stanford.edu/group/scspi/sotu/SOTU_2014_CPI.pdf)...

Video-stimulated recall in cross-cultural research in education: A case study in Vietnam

This paper examines incorporating video-stimulated recall (VSR) as a data collection technique in cross-cultural research. With VSR, participants are invited to watch video-recordings of particular events that they are involved in; they then recall their thoughts in relation to their observations of their behaviour in relation the event. The research draws on a larger PhD project completed at an Australian university that explored Vietnamese lecturers’ beliefs about learner autonomy. In cross-cultural research using the VSR technique provided significant challenges including time constraints of participants, misunderstandings of the VSR protocol and the possibility of participants’ losing face when reflecting on their teaching episodes. Adaptations to the VSR technique were required to meet the cultural challenges specific to this population, indicating a need for flexibility and awareness of the cultural context for research.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Teaching about deliberative politics: Case studies of classroom–community learning projects in four nations

Theories of deliberative politics position grass-roots community members as more than spectators of politics, and instead recognize their capacity for political engagement by discussing and evaluating options in order to make decisions about issues affecting community life. The processes and products of journalism can assist deliberative politics by providing community members with information resources that are vital for understanding the root causes of problems, weighing up competing claims, forming networks around shared concerns, reaching decisions and undertaking action. This article presents the findings of case studies of four community–classroom projects--one each from Australia, New Zealand, the United States and South Africa--that develop the capacity of journalism students to be effective contributors to deliberative politics. The research points to the importance of learning activities that prepare students to work in diverse communities, map significant community places and structures, identify leaders and stakeholders, engage in respectful dialogue about problems and perspectives, and appreciate community frames and values.

The Art of Studio Teaching

This project began in 2013, with the award of an internal QUT Teaching and Learning grant. The task we wished to undertake was to document and better understand the role of studio teaching practice in the Creative Industries Faculty. While it was well understood that the Faculty had long used studio pedagogies as a key part of its teaching approach, organizational and other changes made it productive and timely to consider how the various study areas within the Faculty were approaching studio teaching. Chief among these changes were innovations in the use of technology in teaching, and at an organizational level the merging of what were once two schools within different faculties into a newly-structured Creative Industries Faculty. The new faculty consists of two schools, Media, Entertainment and Creative Art (MECA) and Design. We hoped to discover more about how studio techniques were developing alongside an ever-increasing number of options for content delivery, assessment, and interaction with students. And naturally we wanted to understand such developments across the broad range of nineteen study areas now part of the Creative Industries Faculty. This e-book represents the first part of our project, which in the main consisted in observing the teaching practices used in eight units across the Faculty, and then interviews with the unit coordinators involved. In choosing units, we opted for a broad opening definition of ‘studio’ to include not only traditional studios but also workshops and tutorials in which we could identify a component of studio teaching as enumerated by the Australian Learning and Teaching Council’s Studio Teaching Project: • A culture, a creative community created by a group of students and studio teachers working together for periods of time • A mode of teaching and learning where students and studio teachers interact in a creative and reflective process • A program of projects and activities where content is structured to enable ‘learning in action’ • A physical space or constructed environment in which the teaching and learning can take place (Source: http://www.studioteaching.org/?page=what_is_studio) The units we chose to observe, and which we hoped would represent something of the diversity of our study areas, were: • Dance Project 1 • Furniture Studies • Wearable Architecture • Fashion Design 4 • Industrial Design 6 • Advanced Writing Practice 3 • Introduction to Creative Writing • Studio Art Practice 2 Over the course of two semesters in 2013, we attended classes, presentations, and studio time in these units, and then conducted interviews that we felt would give further insight into both individual and discipline-specific approaches to studio pedagogies. We asked the same questions in each of the interviews: • Could you describe the main focus and aims of your unit? • How do you use studio time to achieve those aims? • Can you give us an example of the kind of activities you use in your studio teaching? • What does/do these example(s) achieve in terms of learning outcomes? • What, if any, is the role of technology in your studio teaching practice? • What do you consider distinctive about your approach to studio teaching, or the approach taken in your discipline area? The unit coordinators’ responses to these questions form some of the most interesting and valuable material in this book, and point to both consistencies in approach and teaching philosophies, as well as areas of difference. We believe that both can help to raise our critical awareness of studio teaching, and provide points of comparison for the future development of studio pedagogy in the Creative Industries. In each of the following pages, the interviews are placed alongside written descriptions of the units, their aims and outcomes, assessment models, and where possible photographs and video footage, as well as additional resources that may be useful to others engaged in studio teaching.

Student perception of a new integrated anatomy practical program: Does students' prior learning make a difference?

While there is evidence that science and non-science background students display small differences in performance in basic and clinical sciences, early in a 4-year, graduate entry medical program, this lessens with time. With respect to anatomy knowledge, there are no comparable data as to the impact previous anatomy experience has on the student perception of the anatomy practical learning environment. A study survey was designed to evaluate student perception of the anatomy practical program and its impact on student learning, for the initial cohort of a new medical school. The survey comprised 19 statements requiring a response using a 5-point Likert scale, in addition to a free text opportunity to provide opinion of the perceived educational value of the anatomy practical program. The response rate for a total cohort of 82 students was 89%. The anatomy practical program was highly valued by the students in aiding their learning of anatomy, as indicated by the high mean scores for all statements (range: 4.04-4.7). There was a significant difference between the students who had and had not studied a science course prior to entering medicine, with respect to statements that addressed aspects of the course related to its structure, organization, variety of resources, linkage to problem-based learning cases, and fairness of assessment. Nonscience students were more positive compared to those who had studied science before (P levels ranging from 0.004 to 0.035). Students less experienced in anatomy were more challenged in prioritizing core curricular knowledge. © 2011 Wiley-Liss, Inc.

Discriminative learning of Bayesian networks via factorized conditional log-likelihood

We propose an efficient and parameter-free scoring criterion, the factorized conditional log-likelihood (ˆfCLL), for learning Bayesian network classifiers. The proposed score is an approximation of the conditional log-likelihood criterion. The approximation is devised in order to guarantee decomposability over the network structure, as well as efficient estimation of the optimal parameters, achieving the same time and space complexity as the traditional log-likelihood scoring criterion. The resulting criterion has an information-theoretic interpretation based on interaction information, which exhibits its discriminative nature. To evaluate the performance of the proposed criterion, we present an empirical comparison with state-of-the-art classifiers. Results on a large suite of benchmark data sets from the UCI repository show that ˆfCLL-trained classifiers achieve at least as good accuracy as the best compared classifiers, using significantly less computational resources.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

A New Iterative FIR Filter for Image and Video Restoration

Image and video filtering is a key image-processing task in computer vision especially in noisy environment. In most of the cases the noise source is unknown and hence possess a major difficulty in the filtering operation. In this paper we present an error-correction based learning approach for iterative filtering. A new FIR filter is designed in which the filter coefficients are updated based on Widrow-Hoff rule. Unlike the standard filter the proposed filter has the ability to remove noise without the a priori knowledge of the noise. Experimental result shows that the proposed filter efficiently removes the noise and preserves the edges in the image. We demonstrate the capability of the proposed algorithm by testing it on standard images infected by Gaussian noise and on a real time video containing inherent noise. Experimental result shows that the proposed filter is better than some of the existing standard filters

Fuzzy inference based data preprocessing for VBR video traffic prediction

Prediction of variable bit rate compressed video traffic is critical to dynamic allocation of resources in a network. In this paper, we propose a technique for preprocessing the dataset used for training a video traffic predictor. The technique involves identifying the noisy instances in the data using a fuzzy inference system. We focus on three prediction techniques, namely, linear regression, neural network and support vector regression and analyze their performance on H.264 video traces. Our experimental results reveal that data preprocessing greatly improves the performance of linear regression and neural network, but is not effective on support vector regression.